housing assignment stanford

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Pre-Assignment

Students apply for university theme houses through the Pre-Assignment process. Some of Stanford's on-campus residences offer special academic, cultural, social, or leadership programs, while other residences are co-ops. Co-ops offer a space where  the cooking and cleaning for residents is performed by the students who live in the house.

Application Timeline

• Monday, April 1:  Pre-Assignment applications for University Theme Houses open (1:00 p.m. PST)
• Wednesday, April 10:  Pre-Assignment applications close (1:00 p.m. PST)
• Wednesday, May 15:  University Theme House pre-assignment placements announced

More About Pre-Assignment

One of the core tenets of the housing assignments process is to support these unique residential programs through the University Theme House Pre-Assignment process.

Students who want to live in a residence with a University Theme House can come together with other students to create a community committed to exploring a topic, lifestyle, or culture.

To learn more about Pre-Assignment, please explore the following links. 

Application Process

Here you'll find information detailing the process of applying for pre-assignment. 

Participating Houses

Explore the different types of houses that participate in Pre-Assignment, find out about open houses, and more. 

Frequently Asked Questions

We've set up this FAQ to help clarify the pre-assignment process for all who are interested.

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The United States has a major shortage of affordable housing. While surveys have shown that most people support building more affordable housing, these projects often face strong local opposition from groups that don’t necessarily represent the neighborhood as whole.

“When you look at broad, national surveys, people often say, ‘We like affordable housing!’ but the reality is that local opposition by the public at city meetings is still a large barrier,” said Sarah Billington , professor of civil and environmental engineering at Stanford. “So we wanted to understand more about what was shaping opinions to see how we might motivate positive action.”

In a recent study, Billington and her fellow researchers explored the factors that predict support for affordable housing at the neighborhood level. Their work , published in the Journal of Planning Education and Research , shows that people’s emotional responses to affordable housing may play a significant role in shifting hypothetical support of affordable housing to specific opposition to local construction. The researchers point out that these reactions may be rooted in unconscious biases, such as racism or classism, and that addressing them could potentially help garner support for affordable housing developments.

“We really wanted to see how this emotional response, which may be partly driven by unconscious racism or classism, paired with more conscious racism,” said Isabella Douglas , who led the research as part of her doctoral work in Billington’s lab. “There’s been a call in urban planning to grapple with people’s emotional responses to the built environment, and to recognize that these emotional responses – while they may be hard to understand and deal with – have a lot of impact.”

Predictors of opposition

According to the National Low Income Housing Coalition , there are only 34 affordable and available rental homes for every 100 extremely low-income households across the country. The U.S. would need an additional 7.3 million affordable homes to fill this gap.

“It’s a nationwide crisis,” said Deland Chan , a Stanford researcher with a background in urban planning and co-author on the paper. “The topic of affordable housing touches everyone, not just those in major cities, and we need more interdisciplinary perspectives and collaborations to make progress on these complex social issues.”

The researchers distributed an online survey to 534 participants around the U.S. They found that while the majority of participants supported affordable housing at the state, city, and neighborhood levels, the amount of opposition more than doubled at the neighborhood level.

“There’s a proximity effect, where as you get closer and closer to the person, their support levels go down,” said Douglas.

Many of their results were similar to what had been found in a previous study conducted a decade ago: People who made more money, lived in suburban neighborhoods, or were more conservative tended to be less supportive of affordable housing in their neighborhoods. People who had more trust in the federal government tended to be more supportive of it. The researchers also found several trends and correlations that had not been reported previously: People with higher levels of education or who lived in single-family homes were less supportive of affordable housing, and people who had lived in their neighborhood for longer than 10 years or who had personally interacted with affordable housing were more supportive.

The most significant predictors of opposition to affordable housing, though, were racism – as captured through the well-studied symbolic racism scale of beliefs – and negative emotional connotations associated with the idea of affordable housing. While the effects of symbolic racism have been documented, the finding that people’s initial emotional response, potentially arising from unconscious racism or other biases, may affect their views on affordable housing is new.

The researchers also found statistical evidence that these factors interacted with some demographic characteristics at the neighborhood level, potentially helping to explain the shift from support to opposition once real development proposals are on the table. For example, people living in suburban neighborhoods had more negative emotional connotations with affordable housing, so they tended to be more likely to oppose neighborhood developments. This finding was not linked with symbolic racism, highlighting the important role of emotional responses and the potential unconscious biases behind them.

Building housing and public support

It’s slightly unusual for civil engineers to be leading an interdisciplinary study on racism and emotional responses, but Billington and Douglas point out that if engineers want to successfully build more affordable housing, they can’t afford to ignore these biases.

“A lot of times, arguing over the buildings is used as a more socially acceptable way to protest affordable housing projects,” Douglas said. “We’re going to be dealing with the effects of racism in our projects and we need to be able to talk about that and address it.”

The researchers intend for this initial work to be a starting point in understanding how engineers can help increase support for affordable housing developments. People’s biases – both conscious and unconscious – will affect their perceptions of the built environment and shape their opinions on affordable housing. The researchers hope that by understanding these root causes, they can work more effectively to address them. They are continuing to investigate how the built environment affects public perceptions and are looking to work with partner organizations that explicitly focus on racial justice and equity to develop strategies that can improve local responses to affordable housing developments.

“Affordable housing impacts many aspects that are tied to both individual well-being and community well-being,” Billington said. “We need to work to change the narrative in the public’s mind about what affordable housing is and can be for society as a whole.”

Billington is the UPS Foundation Professor at Stanford, chair of the Department of Civil and Environmental Engineering, and a senior fellow of the Stanford Woods Institute for the Environment .

Additional co-author Lucy Zhang Bencharit is from California Polytechnic State University, San Luis Obispo. Isabella Douglas was a National Science Foundation (NSF) Graduate Fellowship recipient while conducting this research.

This work was funded by the UPS Endowment Fund and Stanford Impact Labs .

Related : Sarah Billington , professor of civil and environmental engineering 

Due: Sat May 25 11:59 pm Late submissions accepted until Sun May 26 11:59 pm

Assignment by Michael Chang & Julie Zelenski idea originated by Randal Bryant & David O'Hallaron (CMU). Modifications by Nick Troccoli, Brynne Hurst, Kathleen Creel and Jonathan Kula.

Learning Goals

This assignment focuses on understanding assembly code representations of programs. You will be building your skills with:

• reading and tracing assembly code
• understanding how data access, control structures, and function calls translate between C and assembly
• reverse-engineering
• understanding the challenges of writing secure and robust systems
• understanding privacy, trust, and the role of the ethical penetration tester
• mastering the gdb debugger!

You have been hired as a security expert for Stanford Bank (a fictional on-campus bank). They need you to investigate reports of infiltration and security issues and replicate the issues so that they can fix them.

There are three parts to this assignment, each of which can be completed independently:

• an ATM withdrawal program containing some vulnerabilities - you'll need to use your C and assembly skills to find and demonstrate how to exploit these vulnerabilities.
• A dataset that you will use to deanonymize bank users.
• The SecureVault program, a new product designed by the bank to provide increased security to the master vault. You'll be given an executable of the SecureVault program (no C code provided!) to show that it is possible to reverse engineer this program and break into the master vault without being told the passwords.

These problems are like C/assembly "puzzles" to solve, and we hope you enjoy solving them and exploring this material as much as we enjoyed creating them!

Note: check out our assignment overview video on Canvas ; it goes over the different parts of the assignment, what to expect, and tips and tricks! Note the overview video is from this quarter last year, but the assignment is the same (save for the fact that questions 2 and 3 are exchanged).

Spring 2024: Lecture 22 (Mon 5/20) is necessary to work on questions 3 and 4 in part 2 of this assignment.

A few reminders:

• The working on assignments page contains info about the assignment process.
• The collaboration policy page outlines permitted assignment collaboration, emphasizing that you are to do your own independent thinking, design, writing, and debugging. Even without any code being submitted, you should not be doing any joint debugging/development, sharing or copying written answers, sharing specific details about SecureVault behavior, etc. If you are having trouble completing the assignment on your own, please reach out to the course staff; we are here to help!

To get started on this assignment, clone the starter project using the command

View Full Starter File List

• vault : Your SecureVault executable program, custom-generated for each student.
• custom_tests : The file where you will add custom tests to reproduce vulnerabilities in the provided ATM withdrawal program.
• input.txt : A blank text file where you should add the passwords for each SecureVault level, one per line. See the section on SecureVault for more information.
• readme.txt : A file where you should add answers to short written questions for all three parts of the assignment.
• .gdbinit : A gdb configuration file you can optionally use to run certain gdb commands each time gdb launches. See the section on using GDB in SecureVault for more information.
• samples : A symbolic link to the shared directory for this assignment. It contains:
• atm : The executable ATM program, which you will explore for vulnerabilities.
• atm.c : The C source code for the ATM program, which you will explore for vulnerabilities. Note that you're not able to edit or recompile this code/executable.
• checkins.csv : A file containing public social media location check-in data for various locations on Stanford campus over the past three months.
• search_checkins : An executable program to search the check-in data.
• bank : a folder containing the following:
• customers.db : A file with the list of all users and balances for the ATM program.
• transactions.csv : A file with ATM transaction information from the past three months at the Stanford campus ATM.
• SANITY.INI and sanity.py : Files to configure and run sanity check. You can ignore these files.
• wordlist : A list of dictionary words used for SecureVault.
• tools : Contains symbolic links to the sanitycheck and submit programs for testing and submitting your work. ( codecheck is not needed on this assignment)

You will be using gdb frequently on this assignment. Here are essential resources as you work - note that you should make sure you have downloaded the CS107 GDB configuration file mentioned in the Getting Started Guide if you didn't previously do so.

Open Getting Started Guide Open GDB Guide Open Lab5 GDB Tips Open Lab6 GDB Tips

1. ATM Security

Stanford Bank recently updated the ATM software to a version with some additional features. The IT team reviewed the new code and thought it all looked good, but having now installed it in production, they are observing some suspicious activity. The bank has called you because your superior C and assembly skills are just what's needed to investigate and resolve these problems!

In the samples folder, they have provided you the code ( atm.c ) and compiled executable ( atm ), which you can examine/run but cannot recompile or edit (since they want to ensure you work with the same executable installed on the ATMs themselves). The ATM program is invoked with an amount and the credentials for a particular account. If the credential is authorized and the account has sufficient funds, the amount is withdrawn and dispersed in cash. Accounts must maintain a minimum balance of $50, and the ATM is supposed to maintain bank security by rejecting unauthorized access. Every time you run the program, it will print out information to the terminal about the transaction that took place, or the error that occurred, if any. For example, if you ask to withdraw $100 from your account balance of $107, it should be denied with an error message because that would bring your current $107 balance below the required minimum of $50. If you try to sneak cash from another account or use a fake name, your credential should get rejected as unauthorized.

Here are a few examples - try it out yourself! Note that $USER automatically acts as your SUNET ID, and every account balance is set to be $107. Also, each time you run the program anew, all balances return to their original starting levels. No money actually changes hands in this ATM, which is a blessing given its security flaws.

Expand ATM Sample Runs

The bank has identified three anomalies in the ATM program behavior that they need your help investigating. For each of the anomalies (a), (b), and (c) below, you will need to do the following:

• include a test case in your custom_tests file to showcase how to reproduce the vulnerability. Note that there may be more than one way to trigger a vulnerability.
• A concise description of the underlying defect in the code.
• An explanation of exactly how you constructed your test case to exploit it.
• Your recommendation for fixing it. The bank is not looking for a major rewrite/redesign, so in your proposed changes you should directly address the vulnerability with minimal other disruption. Note that there may be more than one possible remedy for fixing each issue. Also make sure you do not remove intended functionality of the bank program, and account for any potential additional security issues introduced by your proposed fix .

NOTE: when running your own custom tests, make sure to inspect the output to ensure your tests are causing the behavior you expect! The sanitycheck tool itself does not verify that the tests cause the specified exploits.

As you work through your investigation, you will need to review the source code for the atm program. The program is roughly 175 lines of C code of similar complexity to what you have been writing this quarter, and is decomposed and fairly readable, though sorely lacking in comments. You should find that the program's approach seems reasonable and the code is sincere in its attempt to operate correctly. As you're reading, take a minute to reflect on how far your awesome C skills have come to let you read through this provided program!

NOTE: when running the ATM program under GDB, make sure you are in the samples folder first before running gdb atm .

a) Negative Balances

A prior version of the ATM program restricted a withdrawal to be at most the full account balance, allowing the customer to drain their account to $0, but no further. The current version has changed the withdraw function to require a non-zero minimum balance. The expected behavior should be that all account balances stay above this minimum. However, the bank saw an (otherwise ordinary) withdrawal transaction that not only caused an account to go below the minimum, but also overdrew so far as to end up with a negative balance. Oops, that's definitely not supposed to happen! Review the C code for the withdraw function, specifically the changes from the old version. It seems to work in many cases, but apparently not all. Read carefully through this function to try and discover the flaw - your understanding of signed and unsigned integers will be useful here! Once you have found the vulnerability, determine a command to make a withdrawal as yourself that withdraws more money than is present in your account . Put this command in custom_tests , and answer the specified readme questions.

b) Unauthorized Account Access

The bank has also received a customer complaint about an unauthorized withdrawal from their account. It seems that another user with different credentials was able to successfully withdraw money from the aggrieved customer's account. Moreover, the credential used appears to be entirely fake - no such user exists in the database! A user should not be able to access a different customer's account and especially not by supplying a bogus credential! Review the C code for the find_account function that is responsible for matching the provided username to their account number. It seems to work properly when the username matches an existing account, but not when the username doesn't match an existing account. Trace through line by line how the function executes when called with an invalid username that is not in the database. What lines are executed? Once you do this, you'll find that the function appears to behave unpredictably. Your next task is to examine the generated assembly to determine precisely how the function will behave - your understanding of the %rax / %eax register will be useful here! Once you have found the vulnerability, determine a command with a designed bogus name credential to withdraw $40 from one of the CS107 staff member's accounts. Put this command in custom_tests , and answer the specified readme questions. (The samples/bank/customers.db file contains information about all valid users and their balances, and the first 15 users in the database are staff accounts.)

c) Accessing The Master Vault

The most worrisome issue is repeated illicit withdrawals from the master vault account, account number 0. The name on the master account is not an actual user, so this account cannot be accessed using the simple username-based credential. Instead, the user must specify two account arguments, the account's number and its secret passcode, as a form of heightened security, like this:

At first the bank thought the vault passcode had been leaked, but changing the passcode did nothing to thwart the attack. In a fit of desperation, the bank removed the vault passcode file altogether, figuring this would disable all access to the vault, yet the rogue user continues to make withdrawals from it! It seems that the high-security passcode authentication may have its own security flaw! The code that handles this authentication is in the lookup_by_number and read_secret_passcode functions. These functions work correctly in many situations, but fail in certain edge cases. Remember that it seems that in certain cases supplied credentials are accepted despite the lack of a saved passcode file . The vulnerability is subtle in the C code, so you should also use GDB to examine the code at the assembly level and diagram out the memory on the stack for these functions . This problem is similar to the stack diagramming/exploit problem from lab6 - revisit that problem if you need a refresher! Your exploit should not involve reading from any file. Once you have found the vulnerability, determine a command to withdraw $300 from the bank vault despite its disabled passcode . Put this command in custom_tests , and answer the specified readme questions.

2. Dataset Aggregation

Separate from the faulty ATM software, Stanford Bank believes that someone was able to gain access to their account logs and get a list of ATM transaction information for their Stanford campus ATM. The company believes that this poses little threat because the transaction logs have limited recorded data. However, you are concerned that this data can be combined with other available data in dangerous ways, such as to learn private information. For instance, knowing someone's history of large (or small) transactions might tell you about their financial situation; knowing memberships in clubs or organizations might tell you about social relationships and webs of networks. Your task is to combine this data with another dataset you have found of public location check-ins to show the harms of a potential data breach. To aid in investigating your concerns, the bank has made the ATM transaction data available to you in the samples/bank/transactions.csv file. This file has one account transaction per line, and each transaction occurred at the Stanford campus ATM. Each line has the following format:

For example, here is one line from the file that represents a withdrawal of $15 on 2/15/21 at 4:54PM:

Transactions with the same account identifier are guaranteed to be for the same bank account, but the identifier doesn't give any information about whose account it is (intentionally done by the bank to obfuscate the data).

You have already downloaded a publicly-available location checkins dataset from an online social network, in the file samples/checkins.csv . It is too large to read through manually, so you also already created a program search_checkins that displays that checkin data and lets you search through it more easily. Run the program ( samples/search_checkins ) for instructions on how to use it.

Show the risks of dataset aggregation and express your concerns to the bank managers by answering the following questions in your readme.txt . Note that you are not expected to create any additional programs to parse or otherwise process these datasets with code - the intent is for you to skim the transactions.csv file by hand and use it along with the search_checkins program to answer the following questions.

• a) The likely user who made multiple large transactions?
• b) Two (there may be more, but you must identify only two) likely members of the Stanford SecurityStars Club, which has a club meeting on the 15th of each month where people must bring $15 to pay their membership dues? (Assume they are procrastinators in withdrawing the money)
• How were you able to de-anonymize the transactions data?
• Beyond encrypting the data, what recommendations would you give to Stanford Bank to further anonymize or obfuscate the account data in the case of accidental data breaches?
• Use one or more of the four models of privacy discussed in lecture to explain why disclosure of the information that can be aggregated here is (or is not) a violation of privacy.

3. SecureVault

Stanford Bank is rolling out a new tool, SecureVault, to provide increased security at the master vault at each of their branches. Employees must enter four secret passwords into this program to gain access to the master vault. For extra security, the bank creates a different SecureVault program for each branch with different expected passwords; the bank headquarters does not give the source code to any of the branches; and the program triggers an alarm that notifies the central system each time an incorrect password is entered. They are confident that this means only someone who is told the password can get access, and any potential intruders will be detected by the alarm system. They have hired you to test this. Your task is to show that you can reverse engineer the program to gain access to the bank vault without being told the password, and without alerting central security.

Do not start by running SecureVault and entering passwords to "see what will happen" . You will quickly learn that what happens is the alarm goes off and it deducts points :-) When started, SecureVault waits for input and when you enter the wrong password, it will raise the alarm and notify the central system, deducting points. Thoroughly read the SecureVault information below before attempting to enter any passwords! There is a lot of information below, but it is included to help provide useful tips for you to work through this part of the assignment.

Without the original source code, all you know is that SecureVault has four "levels" of security, each with a different password. If the user enters the correct password, it deactivates the level and the program proceeds on. But given the wrong input, SecureVault raises an alarm by printing a message, alerting central security and terminating. To reach the master vault, one needs to successfully disarm each of its levels.

This is where the bank needs your help. Each of you is assigned a different generated SecureVault executable unique to you, generated just as they would be for each bank branch. Your mission is to apply your best assembly detective skills to reverse engineer the SecureVault executable to work out the input required to pass each level and reach the master vault, thus proving the insecurity of the bank's approach.

Specifically, you must fill in your input.txt file with the passwords to defuse each level in order, 1 per line, for each level you have solved. You must also answer the following questions in your readme.txt file. Make sure to verify your input.txt file (with appropriate protections!) to ensure proper formatting and that all lines are entered correctly before submitting! We will test by running ./vault input.txt on your submission, using the original SecureVault program generated for you. Here are the readme questions to work through as you go:

• What tactics did you use to suppress/avoid/disable alarms?
• level_1 contains an instruction near the start of the form mov $<multi-digit-hex-value>,%edi . Explain how this instruction fits into the operation of level_1 . What is this hex value and for what purpose is it being moved? Why can this instruction reference %edi instead of the full %rdi register?
• level_2 contains a jg that is not immediately preceded by a cmp or test instruction. Explain how a branch instruction operates when not immediately preceded by a cmp or test . Under what conditions is this particular jg branch taken?
• Explain how the loop in the winky function of level_3 is exited.
• Explain how the mycmp function is used in level_4 . What type of data is being compared and what ordering does it apply?
• How would you describe Stanford Bank’s trust model? (In other words: who among the bank headquarters, the bank branches, and you was trusted?) Justify your answer.

SecureVault Information

From the SecureVault assembly, you will work backwards to construct a picture of the original C source in a process known as reverse-engineering . Note that you don't necessarily need to recreate the entire C source; your goal is to work out a correct input to pass the level. This requires a fairly complete exploration of the code path you follow to deactivate the level, but any code outside that path can be investigated on a need-to-know basis. Once you understand what makes your SecureVault program "tick", you can supply each level with the password it requires to disarm it. The levels get progressively more complex, but the expertise you gain as you move up from each level increases as well. One confounding factor is that SecureVault raises an alarm whenever it is given invalid input. Each time the alarm goes off (except for a free pass the first time), it notifies central security (the CS107 staff) and points are deducted from your score. Thus, there are consequences to setting off the alarm -- you must be careful!

The bank has confirmed to you a few things about how the SecureVault programs operate:

• If you start SecureVault with no command-line argument, it reads input typed at the console.

If you give an argument to SecureVault, such as input.txt :

SecureVault will read all lines from that file and then switch over to reading from the console. This feature allows you to store inputs for solved levels in input.txt and avoid retyping them each time.

Alarms can be triggered when executing at the shell or within gdb. However, gdb offers you tools you can use to intercept the alarms, so your safest choice is to work under gdb and employ preventive measures.

• It is not possible to know for sure whether the central system (course staff) is notified about an alarm. You must use your investigative skills and best defensive measures!
• The central system will give you a free pass (no point deduction) the first time they are notified about an alarm.
• The SecureVault program in your repository was lovingly created just for you and is unique to your id. It is said that it can detect if an impostor attempts to run it and won't play along.
• The SecureVault program is designed for the myth computers (running on the console or logged in remotely). There is a rumor that it will refuse to run anywhere else.
• It seems as though the function names were left visible in the object code, with no effort to disguise them. Thus, a function name of initialize_vault or read_five_numbers can be a clue. Similarly, it seems to use the standard C library functions, so if you encounter a call to qsort or sscanf , it is the real deal.
• There is one important restriction: Do not use brute force!   You could write a program to try every possible input to find a solution. But this is trouble because a) you lose points on each incorrect guess which raises an alarm, b) trying all possible inputs will take an eternity and risk saturating the network, and c) part of your submission requires answering questions that show you understanding of the assembly code, which guessing will not provide :)

Using tools such as gdb , objdump and new tools nm and strings is critical to effectively investigating and disarming each level. Once you are familiar with the tools at your disposal, first work to reliably prevent alarms from triggering , then proceed with disarming each of the levels .

Step 1: Familiarity with Tools

Here are some helpful tools to gather general information:

• nm : use the nm utility ( nm vault ) to print what's called the "symbol table" of the executable, which contains the names of functions and global variables and their addresses. The names may give you a sense of the structure of the SecureVault program.
• strings : use the strings utility ( strings vault ) to print all the printable strings contained in the executable, including string constants. See if any of these strings seem relevant in determining the passwords.
• gdb lets you single-step by assembly instruction, examine (and change!) memory and registers, view the runtime stack, disassemble the object code, set breakpoints, and more. Live experimentation on the executing SecureVault program is the most direct way to become familiar in what's happening at the assembly level.
• Compiler Explorer : pull up tools like the Compiler Explorer interactive website from lab, or gcc on myth , to compile and explore the assembly translation of any code you'd like. For example, if you're unsure how to a particular C construct translates to assembly, how to access a certain kind of data, how break works in assembly, or how a function pointer is invoked by qsort , write a C program with the code in question and trace through its disassembly. Since you yourself wrote the test program, you also don't have to fear it setting off any alarms :-) You can compile directly on myth using a copy of a Makefile from any CS107 assignment/lab as a starting point, and then use gdb or objdump to poke around.

GDB Suggestions

GDB is absolutely invaluable on this assignment. Here are some suggestions on how to maximize your use of gdb in addition to the tips in lab5 and lab6 :

• Expand your gdb repertoire. The labs have introduced you to handy commands such as break , x , print , info , disassemble , display , watch , and stepi/nexti . Here are some additional commands that you might find similarly useful: jump , kill , and return . Within gdb, you can use help name-of-command to get more details about any gdb command. See the quick gdb reference card for a summary of many other neat gdb features.

Get fancy with your breakpoints. You can breakpoints by function name, source line, or address of a specific instruction. Use commands to specify a list of commands to be automatically executed whenever a given breakpoint is hit. These commands might print a variable, dump the stack, jump to a different instruction, change values in memory, return early from a function, and so on. Breakpoint commands are particularly useful for installing actions you intend to be automatically and infallibly completed when arriving at a certain place in the code. (hint!)

gdb kill workaround : gdb 9.2 (current version on myth as of 04/2021) has a bug when attempting to use kill in the commands sequence for a breakpoint that creates a cascade of problems --can cause gdb itself to crash or hang. The gdb command signal SIGKILL can be used as an alternate means to kill a program from a commands sequence that doesn't trip this bug.

Use a .gdbinit file . The provided file named .gdbinit in the assignment folder can be used to set a startup sequence for gdb. In this text file, you enter a sequence of commands exactly as you would type them to the gdb command prompt. Upon starting, gdb will automatically execute the commands from it. This will be a convenient place to put gdb commands to execute every time you start the debugger. Hint: wouldn't this be useful for creating breakpoints with commands that you want to be sure are always in place when running the SecureVault program? The .gdbinit file we give you in the starter repo has only one command to echo Successfully executing commands from .gdbinit in current directory . If you see this message when you start gdb, it confirms the .gdbinit file has been loaded. If you see an error message about auto-loading .gdbinit being declined when starting gdb, this means you haven't installed the CS107 GDB configuration file - see the top of this page for instructions.

• Custom gdb commands . Use define to add your own gdb "macros" for often-repeated command sequences. You can add defines to your .gdbinit file so you have access to them in subsequent gdb sessions as well.
• Fire up tui mode (maybe...). The command layout asm followed by layout reg will give you a split window showing disassembly and register values. This layout will display current values for all registers in the upper pane, the sequence of assembly instructions in the middle pane, and your gdb command line at the bottom. As you single-step with si , the register values will update automatically (those values that changed are highlighted) and the middle pane will follow instruction control flow. This is a super-convenient view of what is happening at the machine level, but sadly, you have to endure a number of quirks and bugs to use it. The tui mode can occasionally crash gdb itself, killing off gdb and possibly the SecureVault program while it's at it. Even when tui is seemingly working, the display has a habit of turning wonky, often fixable by the refresh command (use this early and often!) but not always. A garbled display could cause you to misunderstand the program state, misidentify where your SecureVault is currently executing, or accidentally execute a gdb command you didn't intend. Any alarm suppression mechanism that requires you, the fallible human, to take the right action at a critical time could easily be waylaid by interference, so don't attempt tui before you have invincible automatic protection against alarms. Selective use of auto-display expressions (introduced in lab6) is a great alternative with less disruption. You can exit tui using ctrl-x a and re-enter it again (this doesn't require leaving gdb and losing all your state).

Step 2: General Investigation and Preventing Alarms

Once you are familiar with the tools at your disposal, your next step is to gather general information about how the SecureVault program works to figure out how to reliably prevent alarms from triggering . There are simple manual blocks that give some measure of protection, but it is best to go further to develop an invincible guard. Feel free to use any technique at your disposal, such as leveraging gdb features, tweaking the global program state, modifying your setup, tricking the SecureVault program into running in a safe manner, etc. Avoiding the alarm entirely is one straightforward approach to ensure that we won't hear about it, but there are ways to selectively disable just the transmission portion to the central system (course staff) . Once you figure how to set up appropriate protection against alarms, you will then be free to experiment with the levels without worry. Note that the program can only trigger an alarm when it is "live", i.e., executing in shell or running with gdb .

Step 3: Disarming Levels

Your next task is to approach each level individually to figure out a password that disarms it. There may be more than one password for each level; your task is to enter your 4 passwords, one per line, starting with level 1, into your input.txt file. Here are key tips for how to approach your reverse engineering exploration:

• Run the program live in GDB (with appropriate alarm protections!) and step through to better understand its behavior. Reading and diagramming the assembly by hand is useful to an extent, but quickly becomes infeasible with larger programs.
• Break the assembly into chunks. For instance, if it calls any functions, that's a good stopping point to orient yourself and understand the assembly just up to that point.
• Use gdb to verify your hypotheses. Verify key assumptions you make about the vault behavior to ensure you're on the right track. One helpful trick is you can change register contents while running gdb. E.g. if you think "I believe if %rdi stored this, it would do that", then try it! You can do p $rdi = val to change register contents mid-program. Or if you think something is a char * , cast and print it out, e.g. p (char *)$rdi .
• Document your knowns and unknowns. If you run into a situation where you are stuck due to seemingly-conflicting assumptions, document them and re-verify them. If you have multiple conflicting assumptions, at least one must not be the case.
• Use compiler explorer to see what code looks like in assembly. If you think you happened upon e.g. a loop, if statement, etc. try using compiler explorer to type in some code quickly and see what that code looks like in assembly. If it resembles the assembly you're seeing, perhaps that can help you better understand its structure.
• Use library functions to your advantage. If you spot a call to what looks like a library function, it's the real deal. Use the man page for that function to learn about what parameters it takes in, what it does, and what it returns. This can give you key information about the types of data in different registers - e.g. if you see a call to strlen , then the value put into %rdi must be of type char * , and what's stored in %rax afterwards must be a size_t string length.
• When tracing an unknown function, before dissecting its behavior first learn about the input/output of the function and what role it plays. Does it return anything? What parameters does it take in? If it has a return value, is it checked to be something in particular? Going into a function with an idea of what must be returned for you to continue with the vault can help you focus on understanding how to achieve that.

Sanity Check

The default sanitycheck test cases are ATM inputs and one test case that reports the line count of your input.txt file. This sanitycheck is configured to only allow test cases for ATM in your custom_tests file. The SecureVault executable is not run by sanitycheck.

Once you are finished working and have saved all your changes, check out the guide to working on assignments for how to submit your work. We recommend you do a trial submit in advance of the deadline to allow time to work through any snags. You may submit as many times as you would like; we will grade the latest submission. Submitting a stable but unpolished/unfinished version is like an insurance policy. If the unexpected happens and you miss the deadline to submit your final version, this previous submit will earn points. Without a submission, we cannot grade your work.

We would also appreciate if you filled out this homework survey to tell us what you think once you submit. We appreciate your feedback!

For this assignment, here is a tentative point breakdown (out of 119):

• custom_tests (24 points) Each successful attack test case earns 8 points. We will test by running tools/sanitycheck custom_tests on your submission. Your custom_tests should contain 3 test cases, one for each ATM attack.
• readme.txt (55 points) The written questions will be graded on the understanding of the issues demonstrated by your answers and the thoroughness and correctness of your conclusions.
• Input.txt (40 points) Each SecureVault level you have solved earns 10 points. We will test by running ./vault input.txt on your submission. The input.txt file in your submission should contain one line for each level you have solved, starting from level 1. Malformed entries in your input.txt or wrong line-endings will cause grading failures. To avoid surprises, be sure that you have verified your input.txt in the same way we will in grading (i.e., ./vault input.txt ).
• SecureVault alarms triggered (up to 6 points deducted) Each alarm notification (beyond the first one) that reaches the staff results in a 1 point deduction, capped at 6 points total.

Post-Assignment Check-in

How did the assignment go for you? We encourage you to take a moment to reflect on how far you've come and what new knowledge and skills you have to take forward. Once you finish this assignment, your assembly skills will be unstoppable, and you will have a better understanding of trust, privacy and security! You successfully found vulnerabilities in a program using its source and assembly, and reverse engineered a complex program without having access to its source at all. Rock on!

To help you gauge your progress, for each assignment/lab, we identify some of its takeaways and offer a few thought questions you can use as a self-check on your post-task understanding. If you find the responses don't come easily, it may be a sign a little extra review is warranted. These questions are not to be handed in or graded. You're encouraged to freely discuss these with your peers and course staff to solidify any gaps in you understanding before moving on from a task.

• What are some of the gdb commands that allow re-routing control in an executing program?
• What is the main indication that an assembly passage contains a loop?
• What makes someone a trustworthy fiduciary or guardian of personal data? How and why should an institution like a bank protect the privacy of its customers?
• Explain the difference between a function's return value and its return address.
• Consider the mechanics of function pointer work at the assembly level. How is a call through a function pointer the same/different when compared to an ordinary function call?
• For performance reasons, the compiler prefers storing local variables in registers whenever possible. What are some reasons that force the compiler to store a local variable on the stack instead?
• For the instruction sequence below, what must be true about values of op1 and op2 for the branch to be taken? What changes if ja is substituted for jg ? cmp op1,op2 jg target

This Map Lets You See How School Segregation Has Changed in Your Hometown

The new interactive tool accompanies a study of school enrollment data, which shows that segregation has worsened in recent decades

Daily Correspondent

Today marks the 70th anniversary of Brown v. Board of Education , the landmark Supreme Court ruling that marked the beginning of the end of school segregation. On May 17, 1954, the nine justices unanimously agreed that separating children on the basis of race in public schools was unconstitutional. Their decision ended the “ separate but equal ” doctrine that had applied since the mid-1890s.

But while American public schools are more integrated now than they were prior to 1954 , they’ve become increasingly racially and economically segregated in recent years, according to a new analysis: In the country’s 100 largest school districts, segregation between white and Black students has increased by 64 percent since 1988. Meanwhile, segregation by economic status has increased by roughly 50 percent since 1991.

The two co-authors, who presented their findings at a May 6 conference , also created an  interactive map that displays changes in racial and economic school segregation across the country between 1991 and 2022. 

The tool, called Segregation Explorer, breaks down demographic trends by state, county, metro area and school district. It also allows users to search for the names of specific schools, which then pop up alongside graphs and tables tracking the composition of the student body over time.

“School segregation levels are not at pre- Brown levels, but they are high and have been rising steadily since the late 1980s,” says co-author Sean Reardon , the faculty director of Stanford University’s Educational Opportunity Project , in a statement .

In many large school districts, segregation has gotten worse while  housing segregation and racial disparities in income have improved. According to the researchers, these trends suggest that educational and legal policy changes are to blame, rather than demographic changes.

“School systems became more segregated, but that increase in segregation isn’t because neighborhoods got more segregated,” Reardon tells  Education Week ’s Sarah D. Sparks. “It’s because school systems stopped trying to create schools that were more integrated than neighborhoods, and let them kind of revert to their neighborhood patterns.”

More specifically, the researchers point to two main factors: expanding school choice and declining court oversight.

Beginning in the 1960s, many school districts were placed under court orders that mandated integration. However, since the early 1990s, roughly two-thirds of those districts have been released from court oversight. The researchers estimate that school segregation would have increased by about 20 percent less if those court orders had remained in place, per the  Washington Post ’s Laura Meckler.

“Some districts have voluntary programs [that promote integration],” co-author Ann Owens , a sociologist at the University of Southern California, tells Education Week. However, the “real carrots and sticks” that accompany pressure from the courts “just aren’t available to districts anymore.”

In addition, school choice programs have allowed more parents to enroll their children in alternatives like charter schools, “whose numbers began to increase rapidly in the late 1990s,” writes Hechinger Report ’s Jill Barshay. “​​In many cases, either white or Black families flocked to different charter schools, leaving behind a less diverse student body in traditional public schools.” The researchers estimate that school segregation would have grown by roughly 14 percent less if not for the charter school boom.

Reardon and Owens suggest several measures that school districts could use to counteract these changes, such as voluntary integration programs and socioeconomic-based student assignment policies. These interventions could help reduce the opportunity and test score gaps that exist among predominantly Black and Hispanic schools, which tend to have  higher poverty rates than predominantly white schools.

“It’s not that sitting next to a student of a certain race makes the school good or bad,” Owens tells  Chalkbeat ’s Erica Meltzer. “But we’ve never done ‘separate but equal.’ Until we eliminate broader systemic underlying inequalities in our society, we haven’t shown an ability to actually serve kids equitably.”

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Sarah Kuta is a writer and editor based in Longmont, Colorado. She covers history, science, travel, food and beverage, sustainability, economics and other topics.

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Ilya A. Strebulaev

The David S. Lobel Professor of Private Equity

Additional administrative titles, research statement, research interests.

• Innovation Financing, Venture Capital, Corporate Innovation, Innovation Ecosystems, Private Equity
• Corporate Finance, Financial Decision Making

Teaching Statement

Ilya A. Strebulaev is The David S. Lobel Professor of Private Equity and Professor of Finance at Stanford Graduate School of Business, where he has been a faculty member since 2004, and a research associate at the National Bureau of Economic Research. He also is the founder and director of the Stanford GSB Venture Capital Initiative. He graduated from the London Business School with a doctorate in finance. He also holds degrees from Lomonosov Moscow State University (BSc Economics) and the New Economic School, Moscow (MA Economics). 

Professor Strebulaev is an expert in corporate finance, venture and angel capital, innovation financing, corporate innovation, private equity, and financial decision-making. His work has been widely published in leading academic journals, including   the  Journal of Finance,  the  Review of  Financial Studies,  and the  Journal of Financial Economics.  He has been awarded a number of prestigious academic awards, including the First Paper Prize of the Brattle Award for the best corporate paper published in the Journal of Finance, the Fama-DFA Prize for the best asset pricing paper published in the Journal of Financial Economics , and the Trefftzs Award by the Western Finance Association. His research has also been featured in a variety of media, including the  New York Times,  the  Wall Street Journal and Harvard Business Review .

His most recent research has examined many aspects of the venture capital industry. In the largest ever survey of VCs to date, he and his co-authors analyze all the aspects of decision-making by venture capitalists. He and his co-author developed a valuation framework of private VC-backed companies. In applying this framework to the valuation of highly valued VC-backed companies (called “unicorns”), hey found that these companies on average are overvalued by 50% and that many of the so-called unicorns lose their unicorn status once their fair value is taken into consideration. He has also recently researched the decision making and organizational structure of corporate VC units.

Professor Strebulaev teaches the MBA, MSx, PhD, and executive education programs, and has been awarded the Stanford MBA Distinguished Teaching Award, the Sloan Teaching Excellence Award, as well as the inaugural Masters in Management Best Teacher Award at the London Business School. He developed an MBA-level course on Angel and Venture Capital that he has been teaching for more than ten years. The course enables the students to study many aspects of innovation financing at various stages, including decision making, attracting venture and angel investments, negotiating contractual terms, valuing VC-backed companies, and analyzing the performance of venture capital funds. Recently, he also developed a course on the private equity industry that covers all aspects of the organization and design of PE firms and funds, as well as the relationship between general partners of these funds and their investors, limited partners.

Professor Strebulaev has also led many workshops and executive sessions on new innovation trends, venture capital, the ecosystem of Silicon Valley, corporate innovation, and strategic decision making for senior business and government leaders around the world. He also has been consulting companies and investors around the world on valuation of VC-backed companies, selection of VC investments and managers, and portfolio allocation. He also serves as an expert witness in litigation matters.

When not teaching or doing research, Ilya enjoys spending time with his family, reading, traveling, listening to classical music, and appreciating fine wine and art. 

Academic Degrees

• PhD in Finance, London Business School, 2004
• MA, New Economic School, 1999
• BSc, Lomonosov Moscow State University, 1997

Academic Appointments

• At Stanford University since 2004

Awards and Honors

• Shanahan Family Faculty Fellow for 2021–22
• Dhirubhai Ambani Faculty Fellow in Entrepreneurship for 2014-15
• Shanahan Family Faculty Scholar for 2013–14
• The Sloan Teaching Excellence Award, Stanford, 2013
• First Place, Fama-DFA Prize for Best Paper, Journal of Financial Economics, 2012
• The Masters in Management Inaugural Best Teacher Award, London Business School, 2010
• The MBA Distinguished Teacher Award, Stanford, 2009
• First Paper Prize, Brattle Award for Best Paper, Journal of Finance, 2007
• The Trefftzs Award for the Best Student Paper, WFA, 2004
• Award for Best Paper, Dimitris B. Chorafas Foundation, 2004

Academic Publications

Degree courses, executive education & other non-degree programs, stanford case studies, stanford gsb affiliations, service to the profession.

• Member, American Finance Association
• Member, American Economic Association
• Member, Western Finance Association
• Member, European Finance Association
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ResEd reopens application period for ‘anti-war’ co-op Columbae

Residential Education (ResEd) reopened pre-assign applications for Columbae on Thursday, reversing the University’s’ announcement on Tuesday that the social justice themed co-op would lose its theme next year, following a lack of interest in pre-assignment. 

A petition to save Columbae was circulated broadly, with a focus on outreach to current students and alumni. According to Jason Hu ’26, an incoming residential assistant (RA) at Columbae, the petition received around 1,800 signatures. 

Stanford will accept pre-assignment applications to Columbae until midnight on Sunday.

Hu said ResEd would contact people who signed a form circulated to current students. Respondents expressed interest in living in Columbae next fall. 

Vardaan Shah, an incoming RA at another co-op, Terra, wrote that other co-op residents and supporters will table at White Plaza  to protest the University’s lack of support to Columbae and other co-ops. “We’re hoping the university will see that interest is clearly present for Columbae and reinstate its co-op status and theme,” Shah wrote. 

But the group’s goals extend beyond Columbae. They hope the University will recognize that changes in housing policies and the pre-assignment process paint an incomplete picture of student interest in co-ops, Shah wrote.

“We’ve received no mass communication from admin acknowledging there is some kind of resistance to their choice,” Shah wrote. He criticized that the burden to save Columbae — and administrative effort to establish interest in the co-op — fell on students. “We’re still the ones handling all the administrative details of this. No communication is still the norm.”

According to Shah and some supporters who gathered at an emergency meeting to support Columbae, the University’s approach to housing is divorced from student’s desire for community. While ResEd hoped to emulate the residential college model at peer universities on the East Coast, this was incompatible with the Stanford campus, Shah wrote.

“What they miss is that Stanford is not situated in the same way as those places,” Shah wrote.

For instance, several East Coast universities are located near cities like Boston or New York, Shah wrote.  “Those places have cities near them, where students can find community and places to enjoy themselves, and [they] can go back to the campus to sleep and engage in intellectual life.”

As an expensive suburb, Palo Alto is not accessible to students, and co-ops like Columbae provide an important space to seek smaller, unconventional communities — as a result, Shah and others hope that the University will acknowledge the importance of co-ops. 

The Daily has reached out to the University for comment.

Kaushik Sampath is the sports managing editor. He is a junior from Fayetteville, Arkansas and a history major. You can catch him watching and ranting about his beloved Arkansas Razorbacks or hanging out with friends on campus. Contact him at sports 'at' stanforddaily.com.

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Stanford Health Policy is a joint effort of the Freeman Spogli Institute for International Studies and the Stanford School of Medicine

What Happens When Patients Lose Their Long-Term Opioid Treatment?

• Beth Duff-Brown

Chronic pain impacts more than one in four American adults over age 65 and is commonly managed by long-term opioid treatment. But as the opioid overdose epidemic spirals up in this country, more clinicians are turning down prescriptions for their use.

This means that millions of patients in chronic pain are also being removed from long-term opioid treatment (LTOT), often faster than recommended—raising concerns this is leading to undertreated pain, mental health crises and suicide. Others are losing their opioid treatments because their clinicians are leaving the workforce.

A new study led by SHP’s Adrienne Sabety , PhD, an assistant professor of health policy, a faculty research fellow at the National Bureau of Economic Research , and a faculty fellow at the Stanford Institute for Economic Policy Research , finds that a sudden loss of an opioid prescription due to a prescriber leaving the workforce can lead to an uptick in short-term mental health crises, such as suicide attempts and admissions to hospitals and emergency departments. The cessation, however, does not appear to lead to a significant change in the rate of overdose or mortality—and the immediate negative outcomes taper off after several months.

“Our paper shows that discontinuation from LTOT is far less harmful than previously thought,” said Sabety. “While some intermediary outcomes worsen—like mental health crises and hospital utilization—mortality does not increase.”

The study, published online at BMJ, moves beyond existing ones because the researchers used a method to account for patients being discontinued from opioids being different from those not discontinued. For example, a patient may be discontinued because prescribers suspect that patients are bordering on behavioral, substance use, or mental health disorders, whereas patients who continued LTOT are maintaining baseline.

“Without robust evidence that accounts for selection and confounding, clinical knowledge on the association between LTOT discontinuation and patient outcomes is incomplete, impeding both therapeutic management of LTOT and the development of opioid policy,” writes Sabety and her coauthors, Hannah Neprash of the University of Minnesota, Marema Gaye and Michael Barnett of Harvard University.

The cohort study used a 20% random sample of Medicare fee-for-service and Medicare Advantage beneficiaries from 2011 through 2018. They excluded cancer patients and data with missing racial status—accounting for less than 1% of the sample. They looked at 48,079 people receiving LTOT whose prescriber stopped providing office-based patient care or who had exited the workforce, perhaps through retirement or death. They then they looked at the same number of people whose prescriber did not exit the workforce.

Because their findings differed from previous evidence that did not control for unobserved confounding, the consequences of LTOT discontinuation varies depending on the study methods used.

“Our paper underscores how the choice of methods can give different results, making it hard for patients and policymakers to manage the clinical and public health challenges of LTOT,” Sabety said. “This variation underscores the importance of randomized interventions to better understand how LTOT discontinuation can be managed safely and effectively.” 

Adrienne Sabety, PhD

Health currency: testing whether cash transfers alleviate housing insecurity, 5 questions with shp's adrienne sabety on health care access for undocumented immigrants, qaly ban could harm people with disabilities and chronic illness.

Applying with a Friend in The OAE Graduate Housing Lottery

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If you want to live on campus with one to three friends, you may apply for housing in a group. What's different about applying for graduate housing when a member of your group qualifies for The OAE Graduate Housing Lottery ?

Some Things Remain the Same

• All group members must submit an individual housing application in Axess with the group information, as described in Applying with Friends In Graduate Housing .
• Your  Assignment priority level  matters. You will not automatically be assigned along with the OAE student if your priority does not warrant the same type of assignment, or an assignment at all.
• Your group still gets a random lottery number.

How The OAE Graduate Housing Lottery Differs

• Each member of the group must submit their graduate housing application by  The OAE Lottery Deadline . Here's a link to the  The OAE Lottery Timeline . 
• Participating in The OAE Lottery means relinquishing your right to participate in the standard First Round Lottery. You may still take part in the Second Round Assignments or Rolling Assignments.
• Any disability-related accommodations approved for group member(s) registered with the OAE are specific to them and don't apply to you. In the same way that priority does not transfer between group members, neither do accommodations.
• Only the residential choices listed by  the student requiring the accommodations  will be used for assignment consideration; group retention level is not applicable.
• Single graduate students can apply as a group up to The OAE Lottery Deadline. No groups can be considered after that time.
• Your group could be assigned to a space (e.g., an apartment type or building) that is ranked lower on your list. How your housing assignment is determined in the OAE Lottery depends - first and foremost - on the approved disability-related accommodations. Check out the cards below.

The OAE Lottery

• OAE approved disability-related accommodations
• Your  assignment priority level
• Your group's random lottery number
• The housing choices listed by  the student requiring the accommodations

The Standard Lottery

• Your housing choices
• Your group retention level

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Community Coordinator

🔍 vice provost for student affairs, stanford, california, united states.

The Community Coordinator (CC) in Residential Education supports Resident Fellows, residential student staff, and students in creating an undergraduate residential experience that fosters diversity, equity and inclusion, health and well-being, belonging and community, and intellectual and personal growth. 

The CC manages a multitude of diverse and complex projects, tracks action items, deadlines, and deliverables, and collaborates with relevant parties on behalf of community constituents to ensure all programmatic responsibilities and financial obligations are met in the neighborhoods and houses they support. The CC works behind the scenes to identify solutions independently and proactively to problems and to meet the needs of the Resident Fellows, students, and colleagues in their assigned houses/neighborhoods. 

A successful candidate will have a strong background and proven track record in juggling competing demands and priorities with the highest degree of professionalism and accuracy. The CC must possess excellent project management, financial/accounting, and communication skills, exercise sound judgment in a variety of different situations, and handle confidential/private information with discretion. 

The Community Coordinator reports directly to a Neighborhood Program Director, and works closely with the Resident Fellows, residential student staff, Resident Directors, Academic Advising Directors, Housing staff, and Dining staff in their assigned neighborhoods. 

Job purpose:

• Administer, support, and manage programs or functions under general supervision.

In this role, you will:

• Independently implement, administer, and evaluate day-to-day activities and programs of assigned houses/neighborhoods by identifying and executing tasks and objectives, making recommendations that impact policies and programs, and assigning resources to achieve the goals of the houses/neighborhoods, Residential Education, and Student Affairs. This includes scheduling, organizing, and managing or supporting programs, activities, and events for assigned houses/neighborhoods; coordinating logistics; making arrangements with vendors; overseeing the production and distribution of materials; identifying appropriate funding sources; ensuring compliance with University, division, and department policies and procedures; and obtaining and sustaining the necessary resources and supplies.
• Collect and analyze data, create reports, review and explain trends; formulate and evaluate alternative solutions and/or recommendations to achieve the goals of the houses/neighborhoods, Residential Education, and Student Affairs. This includes reporting on the activities, programs, experiences, and spending of assigned houses/neighborhoods for the purposes of review, reflection, analysis, and identification of trends, patterns, and best practices.
• Analyze, uphold, and interpret policies; develop, revise and implement procedures for assigned houses/neighborhoods. Make recommendations to the cognizant Neighborhood Program Director to clarify and refine policies, streamline and simplify processes, and redesign systems to improve efficiency and effectiveness.
• Represent and advocate for assigned houses/neighborhoods as the key contact and subject matter expert in Residential Education. Serve as the primary liaison and point of contact between houses/neighborhoods and colleagues within and outside the department, such as the cognizant Neighborhood Program Director, Resident Director, Academic Advising Director, Housing staff, and Dining staff. Collaborate with colleagues to find solutions to problems and resolve issues. Commit resources and provide information and/or training to community constituents. May also represent assigned houses/neighborhoods to external/internal stakeholders and constituencies.
• Organize and/or participate in outreach activities that may include developing communications and training, and planning/promoting events for assigned houses/neighborhoods, Residential Education, and/or Student Affairs.
• Participate in development of budgets, monitor and approve expenditures, and process financial transactions for assigned houses/neighborhoods. Evaluate alignment of spending with goals of house/neighborhoods, Residential Education, and Student Affairs and suggest adjustments as necessary. Perform limited forecasting and provide recommendations that determine the budget.
• Work with the student staff of assigned houses/neighborhoods to effectively execute the functions and programs of each community, whether in student-led apartment or Row houses or under Resident Fellow leadership. This includes supporting neighborhood councils and dorm government where relevant and advising student financial managers and house treasurers on responsible stewardship of house funds. May guide and train residential student staff to perform various tasks and assignments related to their job responsibilities.
• *Other duties may also be assigned.

Minimum Qualifications:

Education & Experience:

Bachelor’s degree and three years of relevant experience, or combination of education and relevant experience.

Knowledge, Skills and Abilities:

• Demonstrated ability to follow through and complete routine tasks.
• Demonstrated ability to prioritize own work and multi-task.
• Demonstrated ability to take initiative and ownership of projects.
• Excellent organizational skills and attention to detail.
• Ability to communicate effectively both orally and in writing.
• Ability to routinely and independently exercise sound judgment in making decisions.
• Demonstrated experience working independently and as part of a team.
• Excellent customer service and interpersonal skills.
• Basic analytical and problem-solving skills.
• Proficient computer skills and experience with standard office software and email applications.

Preferred Qualifications:

• Passion for making administrative operations run efficiently, effectively, and transparently.
• Strong critical thinking; ability to analyze situations and identify and implement solutions within the context of understanding assigned houses/neighborhoods both individually and collectively.
• Flexibility and positive attitude in meeting changing demands of a large, complex, and fast-paced environment is essential.
• Ability to learn new processes and procedures and apply them to various situations.
• Willing and able to work independently and collaboratively with colleagues as needed to provide support for houses/neighborhoods.

Physical requirements:

• Constantly perform desk-based computer tasks.
• Frequently stand/walk, sitting, grasp lightly/fine manipulation.
• Occasionally use a telephone.
• Rarely lift/carry/push/pull objects that weigh 11-20 pounds. 

Working Conditions:

• Work evenings and weekends as needed.
• May establish a flexible work schedule with Neighborhood Program Director to accommodate house/neighborhood needs.

The expected pay range for this position is $69,100 to $108,500 per annum.

Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs.

At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website ( https://cardinalatwork.stanford.edu/benefits-rewards ) provides detailed information on Stanford’s extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process.

How to Apply:

We invite you to apply for this position, please submit your résumé and a one-page cover letter along with your online application.   Why Stanford is for You Imagine a world without search engines or social platforms. Consider lives saved through first-ever organ transplants and research to cure illnesses. Stanford University has revolutionized the way we live and enriches the world. Supporting this mission is our diverse and dedicated 17,000 staff. We seek talent driven to impact the future of our legacy. Our culture and unique perks empower you with:

• Freedom to grow . We offer career development programs, tuition reimbursement, or audit a course. Join a TedTalk, film screening, or listen to a renowned author or global leader speak.
• A caring culture . We provide superb retirement plans, generous time-off, and family care resources.
• A healthier you . Climb our rock wall or choose from hundreds of health or fitness classes at our world-class exercise facilities. We also provide excellent health care benefits.
• Discovery and fun . Stroll through historic sculptures, trails, and museums.
• Enviable resources . Enjoy free commuter programs, ridesharing incentives, discounts, and more  

The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned. Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring a reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources at [email protected] . For all other inquiries, please submit a contact form . Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

• Schedule: Full-time
• Job Code: 4121
• Employee Status: Regular
• Requisition ID: 103189
• Work Arrangement : Hybrid Eligible

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 Vice Provost for Student Affairs, Stanford, California, United States

📁 Administration

Post Date: Feb 16, 2024

Global Impact We believe in having a global impact

Climate and sustainability.

Stanford's deep commitment to sustainability practices has earned us a Platinum rating and inspired a new school aimed at tackling climate change.

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Stanford's Innovative Medicines Accelerator is currently focused entirely on helping faculty generate and test new medicines that can slow the spread of COVID-19.

From Google and PayPal to Netflix and Snapchat, Stanford has housed some of the most celebrated innovations in Silicon Valley.

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Through rigorous research, model training programs and partnerships with educators worldwide, Stanford is pursuing equitable, accessible and effective learning for all.

Working Here We believe you matter as much as the work

I love that Stanford is supportive of learning, and as an education institution, that pursuit of knowledge extends to staff members through professional development, wellness, financial planning and staff affinity groups.

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I get to apply my real-world experiences in a setting that welcomes diversity in thinking and offers support in applying new methods. In my short time at Stanford, I've been able to streamline processes that provide better and faster information to our students.

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AI and holography bring 3D augmented reality to regular glasses

Researchers in the emerging field of spatial computing have developed a prototype augmented reality headset that uses holographic imaging to overlay full-color, 3D moving images on the lenses of what would appear to be an ordinary pair of glasses. Unlike the bulky headsets of present-day augmented reality systems, the new approach delivers a visually satisfying 3D viewing experience in a compact, comfortable, and attractive form factor suitable for all-day wear.

“Our headset appears to the outside world just like an everyday pair of glasses, but what the wearer sees through the lenses is an enriched world overlaid with vibrant, full-color 3D computed imagery,” said  Gordon Wetzstein , an associate professor of electrical engineering and an expert in the fast-emerging field of spatial computing. Wetzstein and a team of engineers introduce their device in a new paper in the journal  Nature . Additional information about this advance is available at  this website , created by the research team.

Though only a prototype now, such a technology, they say, could transform fields stretching from gaming and entertainment to training and education – anywhere computed imagery might enhance or inform the wearer’s understanding of the world around them.

“One could imagine a surgeon wearing such glasses to plan a delicate or complex surgery or airplane mechanic using them to learn to work on the latest jet engine,”  Manu Gopakumar , a doctoral student in the Wetzstein-led  Stanford Computational Imaging lab  and co-first author of the paper said.

Barriers overcome

The new approach is the first to thread a complex maze of engineering requirements that have so far produced either ungainly headsets or less-than-satisfying 3D visual experiences that can leave the wearer visually fatigued, or even a bit nauseous at times.

“There is no other augmented reality system out there now with comparable compact form factor or that matches our 3D image quality,” said  Gun-Yeal Lee , a postdoctoral researcher in the Stanford Computational Imaging lab and co-first author of the paper.

To succeed, the researchers have overcome technical barriers through a combination of AI-enhanced holographic imaging and new nanophotonic device approaches. The first hurdle was that the techniques for displaying augmented reality imagery often require the use of complex optical systems. In these systems, the user does not actually see the real world through the lenses of the headset. Instead, cameras mounted on the exterior of the headset capture the world in real time and combine that imagery with computed imagery. The resulting blended image is then projected to the user’s eye stereoscopically.

“The user sees a digitized approximation of the real world with computed imagery overlaid. It’s sort of augmented virtual reality, not true augmented reality,” explained Lee.

These systems, Wetzstein explains, are necessarily bulky because they use magnifying lenses between the wearer’s eye and the projection screens that require a minimum distance between the eye, the lenses, and the screens, leading to additional size.

“Beyond bulkiness, these limitations can also lead to unsatisfactory perceptual realism and, often, visual discomfort,” said  Suyeon Choi , a doctoral student in the Stanford Computational Imaging lab and co-author of the paper.

To produce more visually satisfying 3D images, Wetzstein leapfrogged traditional stereoscopic approaches in favor of holography, a Nobel-winning visual technique developed in the late-1940s. Despite great promise in 3D imaging, more widespread adoption of holography has been limited by an inability to portray accurate 3D depth cues, leading to an underwhelming, sometimes nausea-inducing, visual experience.

The Wetzstein team used AI to improve the depth cues in the holographic images. Then, using advances in nanophotonics and waveguide display technologies, the researchers were able to project computed holograms onto the lenses of the glasses without relying on bulky additional optics.

A waveguide is constructed by etching nanometer-scale patterns onto the lens surface. Small holographic displays mounted at each temple project the computed imagery through the etched patterns which bounce the light within the lens before it is delivered directly to the viewer’s eye. Looking through the glasses’ lenses, the user sees both the real world and the full-color, 3D computed images displayed on top.

Life-like quality

The 3D effect is enhanced because it is created both stereoscopically, in the sense that each eye gets to see a slightly different image as they would in traditional 3D imaging, and holographically.

“With holography, you also get the full 3D volume in front of each eye increasing the life-like 3D image quality,” said  Brian Chao , a doctoral student in the Stanford Computational Imaging lab and also co-author of the paper.

The ultimate outcome of the new waveguide display techniques and the improvement in holographic imaging is a true-to-life 3D visual experience that is both visually satisfying to the user without the fatigue that has challenged earlier approaches.

“Holographic displays have long been considered the ultimate 3D technique, but it’s never quite achieved that big commercial breakthrough,” Wetzstein said. “Maybe now they have the killer app they’ve been waiting for all these years.”

Additional authors are from The University of Hong Kong and NVIDIA. Wetzstein is also member of  Stanford Bio-X , the  Wu Tsai Human Performance Alliance , and the  Wu Tsai Neurosciences Institute .

This research was funded by a Stanford Graduate Fellowship in Science and Engineering, the National Research Foundation of Korea (NRF) funded by the Ministry of Education, a Kwanjeong Scholarship, a Meta Research PhD Fellowship, the ARO PECASE Award, Samsung, and the Sony Research Award Program. Part of this work was performed at the  Stanford Nano Shared Facilities (SNSF)  and  Stanford Nanofabrication Facility (SNF) , supported by the National Science Foundation and the National Nanotechnology Coordinated Infrastructure.

Related : Gordon Wetzstein , associate professor of electrical engineering 

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