The C.I.S. Blog Presents- “DALL-E Art Gallery”

University of Pennsylvania, by Beeple (prompt generated by Yuxin Meng)

So far in this semester, our department blog has talked about the growths in our labs and our faculty members careers. We have touched on the incredible seminars that have been taking place as well as the exciting research projects that our students are involved in. The blog’s overall purpose is to showcase the technological strides that Penn Engineering is making as well as the significant academic achievements of our faculty and student body. The C.I.S. blog is also a platform that strives to implement humanity and relatability to those who are a part of the Penn community and those outside of the University.

As many of you may know, DALL-E 2 developed by OpenAI was launched in April of this year and has just recently been made available to anyone. You get an allowance of free credits that enable you to type in a detailed description of anything that comes to mind and the machine learning models generate digital images that reflect the prompt. We were interested in the combination between artificial intelligence and the ability to generate realistic images using human ingenuity.

DALL-E is a great example of AI and human collaboration working to break barriers and expand horizons through artistic creativity. This platform also gives people the ability to play and be as out there and imaginative as they want. All in all, DALL-E gives us the opportunity to have fun and explore our hobbies, interests, and studies in the form of art. To showcase this AI system and what it can do I had asked all students from the C.I.S. department, from Undergrad to Ph.D., to send in the descriptions that they prompted and to have fun with it.

With that being said, this Gallery of DALL-E generated art was made possible by some of our wonderful students in the C.I.S. Department!


Ani Petrosyan, she/her
Computer Science major, 2026

Purple mountains with Armenian waterfalls

"I am an international student from Armenia. It's a very mountainous country, with waterfalls and wonderful nature. One fun fact about me: most of the dreams I see have purple color in them, so I am dreaming of my country and seeing it in purple.

Edward Hu, he/him
Ph.D. in Robot Learning

A. Bob Ross in the style of Picasso uncanny unreal engine

"Bob Ross is an iconic painter, so I would like AI painters to pay homage to him."

B. Darth Vader cooking in Hell's Kitchen

"Hell's Kitchen is one of my favorite shows. I think Darth Vader's past with high heat and pressure scenarios would make him an excellent contestant."

Yuxin Meng, she/her
MCIT, 2024

A. Hacker, another dimension, digital art

"This one was intended to be "software engineer..." or "coding in..." but these keywords seemed to be less instructive compared to "hacker". I wanted to see us working on the same thing in another universe."

B. Bionic sheep, blueprints

"Love the book: Do Androids Dream of Electric Sheep? Electric sheep in the book look like real sheep, so I guess bionic is proper."

C. In lab, machine reading brain, codes on computer science, digital, by Beeple

"Not so much what I pictured in my mind. I've been obsessed with Pantheon (science fiction drama) recently. Briefly, I expected a picture of machine scanning human brain as code."

Rotem Dror, she/her
Postdoc in the Cognitive Computation Group

Two computers compete in a running competition

"I needed an image for my job talk presentation that would show two models competing who are going to be state of the art. My research involves developing statistical methods for comparing NLP models to determine which is better."

Hannah Gonzalez, she/her
MSE and BSE in Computer Science, 2023

A. A red fox surfing The Great Wave off Kanagawa by Katsushika Hokusai

B. Huskies sledding in Alaska by Monet

C. Macro 35mm film photography of a floating otter wearing a space suit with the Van Gogh "Starry Night" painted background

D. An Andy Warhol style painting of a corgi winking

Gaoxiang Luo, he/him
Ph.D. in Machine Learning

"I generated an image using my hobbies as keywords: cat, guitar, and latte art. I was very impressed and surprised that the AI considered the cat element as latte art!"

C.I. S. and Penn Engineering Halloween Celebration 2022

Penn Engineering’s Halloween, Fall 2022

This year’s Halloween celebration for Penn Engineering was a great success! Held in Quain Courtyard this past Monday, October 31, students, staff, and faculty gathered for trick or treating, hot apple cider and hot chocolate, and a costume contest. There was a great turn out of students coming in between classes and during their lunch break. In addition, incredibly decorated tables from each department covered the courtyard and there was wonderful staff participation. Even some faculty members came out in costume! It was a great experience interacting with students for some spooky and relaxing fun!

Scroll down to see the department tables and awesome costumes that came out for another fun year of Halloween festivities!

C.I.S. Department Chair and Staff
C.I.S. Department Director of Administrative Operations, Jackie Caliman, and student

In the Spotlight: Osbert Bastani and Integrating Machine Learning into Real-world Settings

Osbert Bastani, Assistant Professor in the Computer and Information Science Department in the School of Engineering, University of Pennsylvania

Many students and faculty alike may recognize the face above as Osbert Bastani. Well that’s because this Assistant Professor is not a new member of the Penn Engineering team. Osbert joined the Computer and Information Science Department as a Research Assistant Professor in 2018 specializing in programming languages and machine learning.

“Penn has a great group of faculty working on interesting research problems, and they are all incredibly supportive of junior faculty. I’ve been fortunate enough to collaborate with Penn CIS faculty in a range of disciplines, from programming languages to NLP to theory, and I hope to have the chance to collaborate with many more.” (Osbert Bastani)

Osbert actually began his research career in programming languages. This major challenge in this research is “verifying correctness properties for software systems deployed in safety-critical settings.” He explains that because machine learning is progressively being incorporated into these systems, it has become a greater challenge facing verification. In his research, he is tackling this overarching question; “How can one possibly hope to verify that a neural network guiding a self-driving car correctly detects all obstacles?” While there has been progress made in trustworthy machine learning, there is still a long road ahead to finding solid solutions.

His enthusiasm in working with the Ph.D. students on various topics and research projects is what he has looked forward to most as he entered into this new role in his teaching career at the start of this Fall semester. Since the school year began, he has been teaching Applied Machine Learning (CIS 4190/5190) with Department Chair, Zachary Ives. When asked about how the semester is going Osbert replied:

“I’ve been very fortunate to have strong students with very diverse interests, meaning I’ve had the opportunity to learn a great deal from them on a variety of topics ranging from convex duality for reinforcement learning to graph terms in linear logic. An incoming PhD student and I are now learning about diffusion models in deep learning, which are really exciting!” (Osbert Bastani)

While teaching, Osbert is also involved in several research projects that are dealing with trustworthy machine learning within real-world settings. One project that raises several questions about fairness and interpretability includes “building a machine learning pipeline to help allocate limited inventories of essential medicines to health facilities in Sierra Leone.” In addition, during a summer internship at Meta, one of Osbert’s students has been in the process of “developing deep reinforcement learning algorithms that can learn from very little data by pretraining on a huge corpus of human videos.”

Osbert Bastani wears many hats in the CIS Department. Not only is he involved in teaching and research projects with students, he is also a member of several groups within the department. Those include PRECISE, PRiML, PLClub, and the ASSET Center and he encourages all students to attend the seminars that each club holds and get the opportunity to learn about research in their areas or outside of their own.

Just as Osbert works to problem solve within the classroom and in his research, he does just about same outside of work as well! He expresses that he is an avid board game player and frequents the restaurant just down the street from Penn called “The Board and Brew”. He and his wife have played through the restaurant’s entire collection of the game “Unlock!”. The Board and Brew has great food and several hundred games to choose from. It is highly recommended by Osbert himself!

DSL and SIG Lab Renovations: Out with the Old, In with the New

As the School of Engineering and Applied Science grows, so do the rooms that house all of the creative minds within our departments. Just in time for the Fall 2022 semester, two labs that are a part of the C.I.S. Department and are located in the Moore Building have gotten a makeover this past summer and the faculty and students are thrilled. The Distributed Systems Laboratory (DSL) in Moore 100 and The SIG Center for Computer Graphics in Moore 103 have both undergone renovations for more student space to collaborate, create and liven up the space!

Cheryl Hickey, the Administrative/Event Coordinator in C.I.S., collaborated with the directors of the labs and a design team. She was tasked with choosing the furniture, color scheme, and layout that would best suit the space and the students. The Distributed Systems Lab received all new desks as well as a redone kitchen area for faculty and students. Jonathan M. Smith, Olga and Alberico Pompa Professor of C.I.S. said, “The DSL renovation allow for maximum flexibility in placement of student desks and experiments. Moving the network drops into the DSL machine room freed up space in the main areas for scholarly interaction and increased physical security.” The lab now encourages students to work together within the space better than ever before.

“The DSL renovation is nicely done and timely. I know many of our students really appreciate the new space. The new desks are superb. These days, when I walk past DSL, I’m pleased to see many students interacting with each other. The vibrancy and bustle are back in DSL! Our DSL seminars have also been packed with faculty and students listening to each other’s research. Nothing beats in-person interactions, and the best ideas happen when students talk and iterate through ideas in close proximity.” (Boon Thau Loo, Director of DSL)

Students have noticed the changes to the DSL lab as well since they began the semester just over a month ago. Jess Woods, a C.I.S. PhD being advised by Sebastian Angel, stated that, “It’s nice having our own functional cabinets/lockers. There are more desks and less clutter, which seems to encourage more people to come to campus to work, which makes the environment more collaborative and productive”. Having a space post-Covid that is inviting and open for all students to take advantage of is incredibly positive for the department.

While a part of the SIG Center for Computer Graphics is fully renovated as of this past summer, the lab is still continuing to grow. New technologies are in the works in addition to a couple of new faculty members who will be officially joining the department this coming Spring 2023 semester. Incoming assistant professor in Computer Graphics, Lingjie Liu, stated that there will be many upgrades to the space and equipment including GPU clusters and data storage space in support of research development.

Upon her arrival to Penn Engineering, Lingjie will “we will also purchase and set up a multi-view volumetric camera capture stage for capturing human motions and human-object interactions with multiple synchronized cameras (about 40 cameras).” This set of equipment will be an addition to the labs’ Vicon 16-camera motion capture system.

“The research focus of the new SIG Lab will be developing Artificial Intelligence (AI) technologies for perceiving, understanding, and interacting with 3D objects, people, and environments. Specifically, we will pursue three research goals: (1) High-quality reconstruction of real-world scenes from sparse RGB (camera) images; (2) Photo-realistic image synthesis of real-world scenes with 3D control; and (3) Large-scale 3D scene generation for 3D machine learning tasks.

Lingjie states that the SIG Lab’s new research focus will be “developing Artificial Intelligence (AI) technologies for perceiving, understanding, and interacting with 3D objects, people, and environments.” There are three research goals that the lab will pursue which include:

  1. High-quality reconstruction of real-world scenes from sparse RGB (camera) images
  2. Photo-realistic image synthesis of real-world scenes with 3D control
  3. Large-scale 3D scene generation for 3D machine learning tasks.

“We will approach these goals by designing new algorithms that incorporate AI advances into classical computer graphics methods. We believe that with the new research focus and the facilities upgrade, we will create new research achievements and continue the success of our SIG Lab.”

The finished and fully furnished side of the SIG lab will now be filled with another incoming assistant professor of C.I.S. and ESE, Mingmin Zhao‘s students. “Working with the renovation and designer team was a pleasure, and the new lab is absolutely gorgeous. I am excited to attract and recruit more students and spend time with them in the new lab.”

While touring SIG lab earlier this month, there were several students hard at work and raved about how much they enjoy spending time in the space. One PhD student who is being advised by Mingmin, Gaoxiang Luo, said, “The renovation of Moore 103B is way beyond my expectation. The workspace shelves allow us to store electronic components, while the wall pegboard allows us to hang tools. While the space is large enough for us to conduct wireless experiments using radar with a certain distance, the ESD flooring further ensures our safety. It’s also worth mentioning that I love the ergonomic height-adjustable desk and chair, which is particularly useful for our health as we work with our computer frequently nowadays.”

It is incredible to see the impact that this renovation has had on the students and faculty. The department is looking forward to seeing the work and successes that come out of these two labs for this new generation of students in Penn Engineering!

The ASSET Center: Enabling Trust Between AI and its User

Picture this: you’re getting ready to watch a movie on Netflix, popcorn in hand, and several films pop up that have been curated just for you. What are you going to do: choose one from the list recommended by the underlying AI algorithm, or worry about how this list was generated and whether you should trust it? Now, think about when you are at the doctors’ office and the physician decides to consult an online system to figure out what dosage of medicine you as the patient should take. Would you feel comfortable having a course of treatment chosen for you by artificial intelligence? What will the future of medicine look like where the doctor is not involved at all in making the decision?

This is where the ASSET Center comes into play. This initiative, led by the C.I.S. Department in Penn Engineering, to focuses on the trustworthiness, explainability, and safety of AI-systems. The faculty members and students who are a part of this Center have tasked themselves with finding ways to achieve this trust between an AI-system and a user. Through new collaborations between departments all throughout Penn, innovative research projects, and student engagement, ASSET will be able to unlock AI abilities that have never been achieved before.

Rajeev Alur, Zisman Family Professor and inaugural director of ASSET

I recently spoke with Rajeev Alur, Zisman Family Professor in the C.I.S. Department and inaugural director of ASSET. He elaborated on our Netflix example to explain the trust between an AI-system and a user and when it is absolutely critical for the adoption of AI by society. Based on movies and shows that the user watches, Netflix is able to give several recommendations, and it is the user’s choice as to whether they will go for something new. While the recommendations may be decent picks to the user “there is no guarantee or assurance that what they are recommending is foolproof or safe”, says Rajeev. Although AI is found to be useful in the case of choosing what to watch, the user needs a higher level of assurance with the system in more critical applications. An example of this could be when a patient is receiving treatment from a doctor. This high assurance can become important in two cases. One is when the system is completely autonomous, or what is called a “closed loop system,” and the other case is when the system is making a recommendation to a physician who decides what course of action to take. For this latter case, the AI does not make the decision directly, but its recommendation may still be highly influential. In many clinical settings, there are AI-systems already in place that dole out courses of treatment that best suits the patient, and a physician consults and tweaks these choices. What ASSET is looking to implement in the medical field are autonomous AI-systems that are trustworthy and safe in their decision making for the users.

“The ultimate goal is to create trust between AI and its users. One way to do this is to have an explanation and the other one is to have higher guarantees that this decision the AI-system is making is going to be correct,” Rajeev explains.

Collaborations

For ASSET to succeed, the center must nurture connections throughout Penn Engineering and beyond its walls. Within C.I.S., machine learning and AI experts are working together with faculty members in formal methods and programming languages to come up with tools and ideas for AI safety. Outside of C.I.S., Rajeev explains that robotics faculty in ESE and MEAM are interested in designing control systems and software that uses AI techniques in the Center. Going beyond Penn Engineering, ASSET is dedicated to making connections with Penn’s Perelman School of Medicine. “There is a great opportunity because Penn Medicine is right here and there are lots of exciting projects going on. They all want to use AI for a variety of applications and we have started a dialogue with them…This will all be a catalyst to having new research collaborations”, says Rajeev.

Research Projects

F1Tenth Racing Car that is used in competitions
F1Tenth Racing Car

In keeping with the idea of autonomous AI that was discussed earlier, one of ASSET’s flagship projects is called Verisig. The goal of this project involving the collaborative efforts of Rajeev Alur, Insup Lee, and George Pappas, is to “give verified guarantees regarding correct behaviors of AI-based systems” (Rajeev Alur). In a case study being performed by the Center, researchers have verified the controller of an autonomous F1/10 racing car to check the design and safety of the controller so that the car is guaranteed to avoid collisions. The purpose of this project is to further understand assured autonomy; if a controller of a small car can be found trustworthy and safe, these methods may eventually be generalized and used in AI applications within the medical field.

How to get involved

The best way for students to get involved with ASSET is engaging in the center’s Seminar Series. They happen every Wednesday in Levine 307 from noon to 1pm, and the great thing about them is that any Penn student can join. There are incredible speakers lined up through the Fall and Spring semesters this school year, so instead of turning on Netflix and letting the system choose your next bingeworthy show, join ASSET every Wednesday for exciting talks about creating safe and trustworthy AI!

In the Spotlight: Eric Wong and Developing Debuggable AI-Systems

What happens when AI goes wrong? Probably not the Terminator or the Matrix – despite what Hollywood suggests – but rather, something that could still harm a human, such as a self-driving car that gets into an accident, or an algorithm that discriminates against certain people. Fortunately Penn has innovative researchers like Eric Wong, who build tools to make sure AI works correctly!

You may have already seen Eric on campus or perhaps teaching his advanced graduate class. Just like the Class of 2026 who are quickly learning their way around Levine Hall, Eric is one of the C.I.S. Department’s newest faculty members. An Assistant Professor who works in Machine Learning, Eric is a Carnegie Mellon Ph.D. graduate and a former MIT post-doctoral researcher in the Computer Science and Artificial Intelligence Lab.

As this semester is in full swing, Eric Wong is busy at work teaching course 7000-05: Debugging Data and Models. When asked what he is looking forward to most about teaching in Penn Engineering, Eric stated,

“One of the key skills that students will learn is how to tinker with AI systems in order to debug and identify their failure modes. I’m excited to see the new ways in which Penn Engineering students will break AI systems, as well as the innovations they come up with to repair them!”

The initiatives that Penn Engineering has launched in recent times are what drew Eric to the C.I.S. Department, specifically the ASSET Center. “Penn Engineering is well-situated to ensure that the tools and systems we develop as computer scientists actually satisfy the needs and requirements of those that want to use them.”, said Eric. He will be one of many faculty members working with ASSET to develop reliable and trustworthy AI-systems which coincides with his own research.

Some of Eric’s specialized interests in this field include “verifying safety properties of an AI-system, designing interpretable systems, and debugging the entire AI pipeline (i.e. the data, models, and algorithms).” His research goals are working towards debugging AI-systems so that the user is able to understand the decision process of a system and learn how to inspect its defects. Eric is also interested by the interdisciplinary work of connecting these methods to other fields outside of engineering. Collaborators in medicine, security, autonomous driving, and energy would “ensure that the fundamental methods we develop are guided by real-world issues with AI reliability.”

As AI is being developed and deployed at a rapid rate, Eric worries that, “it is only a matter of time before the ‘perfect storm’ induces a catastrophic accident for a deployed AI system.” In teaching methods of debugging AI-systems, he strives to give his students the tools and knowledge toward building safer and more trustworthy AI for the future. He hopes that with his research and teachings in the classroom, students take the time to “critically examine their own system” before sending them out into the world.

When Eric is not spending time making sure AI-systems are at the top tier of trustworthiness and reliability, he enjoys trying to recreate the recipes of meals that he orders at restaurants. Trying to “reverse engineer its creation process” is harder than it might seem. Eric mentioned that, “It does not always look the same as the original, nor does it always taste as good, but sometimes it works!”. Maybe someday that too will be something an AI can do (correctly)!

Welcome Back C.I.S. Students: Let’s See What’s New!

Melvin J. and Claire Levine Hall

The 2022-2023 academic year has kicked off last week and summer has officially come to a close. We would like to welcome back returning Computer and Information Science students as well as the Class of 2026! Penn Engineering is excited to have you on board.

With a new school year comes new changes for Penn Engineering and the CIS department. In the past year, we have hired an exceptional number of faculty, brought in new research initiatives, renovated our spaces, and broke ground on a state-of-the-art facility. We are also incredibly thankful to be able to see so many faces in person this year as the circumstances surrounding Covid-19 continues to improve and in-person activities can commence.

Faculty

Several brand new assistant professors have joined the department this semester, while the rest will arrive in January and next Fall. Rejoining the CIS department, in a new role as an Assistant Professor, is Osbert Bastani who develops innovative techniques for programming and building software that incorporate machine learning components. Two new faces to Penn Engineering features Danaë Metaxa, who works in areas of human-computer interaction and communications, and Eric Wong, who works on robust and reliable machine learning.

“We are delighted to welcome an unprecedented 10 new assistant professors arriving over the next year.  Each brings new innovations to the curriculum and more opportunities to get involved in undergraduate research projects.”, says Zachary Ives, Chair of the CIS Department.

Each new faculty member entering into Computer and Information Science has arrived to break barriers and help our students grow.

Space

As our department is growing, our spaces have been transforming as well. This summer, the Distributed Systems Lab (DSL) and the SIG Lab for Computer Graphics on the first floor of Moore have both undergone major renovations. On the second floor of Levine Hall, the brand new Penn Human-Computer Interaction Lab, led by Andrew Head and Danaë Metaxa, just opened.

“We couldn’t be more excited for the start of this year and the official launch of our group. We’re looking forward to teaching Penn’s first Human-Computer Interaction courses at all levels, welcoming our first cohort of PhD students and opening our physical space- the HCI Lab- in Levine 255. We welcome interested students to reach out to us!” -Danaë Metaxa, Assistant Professor, CIS Dept, University of Pennsylvania.

In addition to our growth in space, Penn Engineering is not stopping there. The construction of Amy Gutmann Hall has begun during the summer. The creation of new space, study rooms, and research labs is anticipated to be opening in September 2024.

Research Initiatives

Since the launch of this past year’s interdisciplinary research initiative, Innovation in Data Engineering and Science (IDEAS), the CIS Department announced the ASSET Center directed by Rajeev Alur. ASSET (AI-enabled Systems: Safe, Explainable, Trustworthy) focuses on implementing tools and science to guarantee AI systems do exactly what they are designed to do. Getting students involved in this new initiative is a top priority for the Center.

“The best way to get involved is to join our seminars. It’s every Wednesday at noon and we have a great line-up of speakers. There is a number of faculty from our department, other Penn faculty, and also outside speakers. Some of the topics will include applications to healthcare, explainablility, and safety.” -Rajeev Alur, Director of ASSET, University of Pennsylvania.

With every new faculty member, space renovation, and research initiative; all of these things are implemented to give students the best opportunities for success. We have another exciting year just beginning at Penn Engineering. Let’s make it count.

Computational Social Science Lab’s PennMAP to Expand Thanks to Leadership Gift

Stevens University Professor Duncan Watts, founder of the CSS Lab

The Wharton School and the University of Pennsylvania are delighted to announce the expansion of the Penn Media Accountability Project (PennMAP), an interdisciplinary, nonpartisan research project dedicated to enhancing media transparency and accountability. Its growth is made possible by a new leadership gift from Richard Jay Mack, W’89.

“Our goal at PennMAP is to detect and expose biased, misleading, and otherwise problematic content in media from across the political spectrum and spanning television, radio, social media, and the broader web,” says Duncan Watts, the Stevens University Professor and a Wharton professor of Operations, Information and Decisions who leads PennMAP. Watts also holds faculty appointments in the Annenberg School of Communication and in the Department of Computer and Information Science in the School of Engineering and Applied Science. He is a Faculty Fellow of Analytics at Wharton, the preeminent and first business school center focused on research, teaching, and corporate partnerships around analytics and their application in business, non-profits, and society.

“Clearly this is an ambitious goal that requires a substantial investment in research infrastructure as well as building collaborations with a diverse set of partners,” says Watts. “Richard Mack’s generous gift will allow us to significantly accelerate our efforts and increase our impact both in terms of research and the public conversation on these important issues. We are tremendously grateful for his support.”

PennMAP is a product of the University’s Computational Social Science Lab (CSSLab), a joint venture of the School of Engineering and Applied Science, the Annenberg School for Communication, and the Wharton School. The Lab seeks novel, replicable insights into societally relevant problems by applying computational methods to large-scale data.

This article originally appears on The Wharton School site. Click here to read it in full.

Happy Halloween! From CIS and Penn Engineering 👻🎃🦇

On Friday, October 29, each department of the School of Engineering and Applied Science gathered together on the West Towne Lawn in the spirit of Halloween celebration!

Students, staff and faculty were able to stop by each department’s station for delicious treats and candy, Penn Engineering swag, and fun Halloween stickers and toys.

Not only were costumes encouraged, but the Penn Engineering community is hosting a costume contest, with entries accepted until November 3!

Scroll down for some amazing photos of the day, which also included a photo backdrop and Halloween tunes!


Other CIS-affiliated Halloween events include:

  • The Penn Society of Women Engineers Meet and Greet – Levine Lobby, October 29, 4-5pm
    Come take a break from studying, meet other students and enjoy some arts and crafts and insomnia cookies.
  • CIS Faculty and Postdoctoral Fellow Halloween TGIF – Quain Courtyard, October 29, 5-8pm
    There will be a Halloween Costume Contest with gift card prizes for winners! There will also be a pumpkin carving event, food, and an expanded selection of alcoholic and non-alcoholic drinks.

Secure Imprecision: Professor Andreas Haeberlen speaks on the importance of Differential Privacy

Left: Andreas Haeberlen
Right: “Informal Definition of Differential Privacy,” courtesy of the National Institute of Standards and Technology
October is Cybersecurity Awareness Month. This article is one of a cybersecurity-focused series. 

Last year during the peak of the COVID-19 pandemic in the US, testing and contact tracing failed to quell the spread. Many circumstances — including a decades-old underfunding of state health departments, and slow workforce build – have contributed to this outcome.  

However, according to Department of Computer and Information Science Professor Andreas Haeberlen, one of the main reasons contact tracing wasn’t relatively more successful is simple: people don’t’ feel comfortable sharing their information. 

“It’s really scary to think of people knowing all the things that you type in your phone,” said Haeberlen. “Like what you’ve had for breakfast, or your medical information, or where you’ve been all day or who you’ve met. All of that data is super super sensitive.” 

Haeberlen, whose research centers distributed systems, networking, security, and privacy, believes that differential privacy could be the solution. 

“Differential privacy is a way to purpose private information so that you can really guarantee that somebody can’t later learn something sensitive from this information,” said Haeberlen. “[It] has a very solid mathematical foundation.” 

The National Institute of Science and Technology defines differential privacy in terms of mathematical qualification. “It is not a specific process, but a property that a process can have,” said NIST on their website. “For example, it is possible to prove that a specific algorithm ‘satisfies’ differential privacy.” 

And so we might assert that, if an analysis of a database without Joe Citizen’s individual data and an analysis of a database with Joe Citizen’s individual data yield indistinguishable results, then differential privacy is satisfied. “This implies that whoever sees the output won’t be able to tell whether or not Joe’s data was used, or what Joe’s data contained,” said NIST on their site. 

Haeberlen insists that, with widespread application of differential privacy, user trust is not only no longer a barrier, but that it is not necessarily required. Surrendering our sensitive information to large corporations such as Apple would no longer require a leap of faith. 

Building the tools

A popular industry standard of cybersecurity involves adding imprecision into results to purposefully skew them, and thus protect individual user data. Challenges to this application, according to Haeberlen, include the ongoing debate among experts about whether it satisfies differential privacy specifications, and its lack of scalability. 

Fuzzi: A Three-Level Logic for Differential Privacy,” a paper by Haeberlen and fellow researchers Edo Roth, Hengchu Zhang, Benjamin C. Pierce and Aaron Roth, is one of many of Haeberlen’s oeuvre that focuses on developing tools that can do the work for us. The paper presents a prototype called Fuzzi, whose top level of operational logic “is a novel sensitivity logic adapted from the linear-logic-inspired type system of Fuzz, a differentially private functional language,” according to the abstract. 

Essentially, a researcher would input data into the tool, define what that data means, and specify what data output they’re searching for. The tool would be able to state if that output satisfies differential privacy specifications, and, if not, what amount of imprecision would need to be added in order to meet specifications.  

“The way that we did that was by baking differential privacy into a programming language,” said Haeberlen. “As a practitioner you don’t have to understand what differential privacy is, you also don’t have to be able to prove it.” 

In the world of science, imprecision usually means error and gross miscalculation. However, in the more specific realm of differential privacy, imprecision equals security. 

“Imprecision is good because it causes the adversary to make mistakes,” said Haeberlen. In this case, the “adversary” is any person or system trying to gain access to sensitive information. 

All tools developed by Haeberlen and his team have been made available under open-source license, and companies such as Uber and Facebook are currently releasing data sets using differential privacy.  

Visit Professor Andreas Haeberlen’s page to learn more about his current projects and recent publications.  

New Penn Engineering Data Science Building named Amy Gutmann Hall


School of Engineering and Applied Science Dean Vijay Kumar, President Amy Gutmann, Trustee and naming donor Harlan M. Stone, and Penn Engineering Board Chair Rob Stavis at the October 1, 2021 groundbreaking for Amy Gutmann Hall to be located on the northeast corner of 34th and Chestnut Streets.
Courtesy of University of Penn Almanac site

On Friday, October 1, 2021, the University of Pennsylvania’s School of Engineering and Applied Science held a groundbreaking ceremony for its new data science building and unveiled the building’s official name, Amy Gutmann Hall, honoring Penn’s President. Amy Gutmann is the eighth and longest-serving President in Penn’s history, leading the University since 2004; her term will conclude at the end of this academic year.

Amy Gutmann Hall will serve as a hub for cross-disciplinary collaborations that harness expertise, research, and data across Penn’s 12 schools and numerous academic centers. Upon completion, it will centralize resources that will advance the work of scholars across a wide variety of fields while making the tools and concepts of data analysis more accessible to the entire Penn community.

“I am thrilled Penn Engineering’s new data science building will honor Dr. Gutmann’s remarkable legacy at Penn,” said Vijay Kumar, the Nemirovsky Family Dean of Penn Engineering. “Her Penn Compact and the principles of inclusion, innovation, and impact influenced the school’s strategic priorities from which the plan for a data science building emerged. This revolutionary new facility will create a centralized home for data science research and provide collaborative and accessible space for our faculty and students, as well as the Philadelphia community.”

The 116,000-square-foot, six-floor building will be located at the northeast corner of 34th and Chestnut Streets. Planned academic features include a data science hub, the translational and outreach arm of Penn Engineering in the area of data science and artificial intelligence; research centers for new socially aware data science methodologies and novel, bio-inspired paradigms for computing; and laboratories that will develop data-driven, innovative approaches for safer and more cost-effective health care. 

The impressive building is the design of executive architects Lake/Flato, with KSS Architects serving as associate architects. The building’s architecture will signify the future and the dynamic shift from the traditional to the digital. The facility is planned to be the first mass timber building in Philadelphia and will be designed sustainably.

Construction will begin in spring 2022 and is slated for completion in 2024.

This article originally appears on the University of Pennsylvania Almanac site. To read the full article, click here. 

The new Computational Social Science Lab aims to thrive on mass collaboration and open science

The School of Engineering and Applied Science, the Annenberg School for Communication and the Wharton School have joined together to form the Computational Social Science (CSS) Lab. Established in March 2021, the CSS Lab brings together a team of undergraduate, graduate and postdoc students from all three schools, as well as a dedicated staff, and researchers from other esteemed universities. 

“Our central mission is to integrate methods and ways of thinking from the computational and social sciences in the service of real-world applications,” said Lab Director and Stevens University Professor in the Department of Computer Science Duncan Watts. “We are also dedicated to building research infrastructure to support mass collaboration around shared data, and to facilitate open, transparent, and replicable science. We have a great team and a great set of initial projects. I’m really looking forward to seeing what we can do.” 

Some of those projects include a set of interactive data dashboards that utilize demographic and mobility data around COVID-19 to help inform decisions, as well as a project “dedicated to enhancing media transparency and accountability at the scale of the entire information ecosystem,” according to the Lab site.  

Among the team who will help bring the mission to fruition are Associate Research Scientist Homa Hosseinmardi, Research Data Engineer Yingquan Li, and the Lab’s Executive Director, Valery Yakubovich

As a former professor at ESSEC Business School, Yakubovich is excited to bring his management expertise to the Lab. 

“Creating a hub for cutting-edge research at the intersection of social science and high-tech requires genuine intrapreneurship, open and secure digital organization, and a functionally diverse team of staff speaking in one language,” said Yakubovich. “Under the auspices of three professional schools—each as renowned as it is independently-minded—this task is especially challenging but equally rewarding.”  

CIS looks forward to the exciting work the Lab will produce. Visit the CSS Lab site, and be sure to check our blog for important updates and research findings.  

Shirin Saeedi Bidokhti receives 2021 NSF CAREER Award

Shirin Saeedi Bidokhti (Illustration by Melissa Pappas, Courtesy of Penn Engineering Today)
This article originally appeared in Penn Engineering Today, written by Melissa Poppas.

Humans have never been more connected to one another, though the speed with which we can share with one another has its drawbacks. For example, the spread of COVID-19, as well as misinformation about it, have both been facilitated by our highly connected online and in-person networks. Fortunately, the branches of mathematics known as information theory and network theory can help us to understand how both systems work and how to control them.

NSF CAREER Award recipient Shirin Saeedi Bidokhti, Assistant Professor in Electrical and Systems Engineering, will use the grant to conduct research on both online social networks and COVID-19 contact tracing networks. As case studies, these real-word examples will inform networked systems’ theoretical foundations, as well as the design of learning and decision-making algorithms that help us to make sense of them. She will also use the funding to develop a new course module that brings information and network theory into practice for undergraduate students at Penn.

Using a combination of tools from information theory, network theory and machine learning, Saeedi Bidokhti aims to narrow the gap between theory and practice through algorithm-informed real-time data sampling, estimation and inference in networked systems. Her work aims to produce smarter algorithms that can extract information, infer about these systems, and ultimately provide more precise control of them.

While such algorithms are already improving our ability to understand complex networks, there is always a tradeoff that needs to be considered when it comes time to use that information.

“In information extraction, knowing when to sample with real-time data makes a difference, says Saeedi Bidokhti. “It helps us to know if we should act now or wait to sample, facing the tradeoff of gathering the most information while minimizing costs to most efficiently control the system.”

To read the full article, visit Penn Engineering Today.

Professor Susan Davidson honored with VLDB Women in Database Research Award

Professor Susan Davidson in Computer and Information Science (CIS), who has spent nearly 40 years teaching with the Department, has been awarded the 2021 Very Large Database (VLDB) Women in Database Research Award.

Sponsored non-profit organisation Very Large Database Endowment Inc., the award focuses on the cumulative lifetime work of the researcher. Davidson was specifically honored “for groundbreaking work in the areas of data integration, data provenance and her efforts in cross-disciplinary research, namely bridging databases and biology.”

“Really it was more that I was one of the early people to help define what interesting topics, there were in bioinformatics,” said Davidson.

The former Department Chair of CIS wrote an award acceptance speech titled “It’s not just Cookies and Tea” that blended the focal points of her life’s work — data integration, provenance and concurrencies — with personal life. The two are often inextricable.

“I talked about my parents and how they influenced where I am today: that was provenance,” said Davidson. “I talked about how i’ve built programs to recruit, retain and promote women in engineering, computer science. You have to integrate, as well as have cookies and tea.”

Davidson’s advocacy for other women, both within the engineering field and without, has also been a defining facet of her professional career. The Founder of Advancing Women in Engineering (AWE) at Penn was hoping her speech would also serve as a point of motivation.

“I was also really trying to encourage other women, “said Davidson. “I know that it’s been extremely hard for for women with young children during the pandemic.”

The Women in Database Research Award is one of many presented at the annual VLDB Conference, this year hosted in hybrid format, August 16-20 in Copenhagen, Denmark. According to the VLDB site, "this series is perhaps the most international (in terms of participation, technical content, organization, and location) among all comparable events."

The 2021 Ruth and Joel Spira Award for Excellence in Teaching: Professors Susan Davidson and Boon Thau Loo

Professors Susan Davidson and Boon Thau Loo have been awarded the 2021 Ruth and Joel Spira Awards for Excellence in Teaching. Sponsored by the Spira co-founded Lutron Electronics in 2019, the award specifically recognizes outstanding faculty within the C.I.S. department at Penn, and has corresponding awards at universities across the country.

Susan Davidson

Penn Engagement Days: Engineering In 100 Seconds: Susan Davidson
Courtesy of Penn NSOAI YouTube

For Professor Davidson, the Spira Award is the first teaching award she has received in her nearly 40-year career.

“I think it’s especially meaningful because it’s difficult for women in STEM fields,” said Davidson. “Women in STEM fields tend not to rate as highly as their counterparts, because of a certain amount of gender bias.”

The Founder of SEAS’ Advancing Women in Engineering (AWE) received her Spira Award “for her critical role in defining our initiatives in data science and databases, and especially for the outstanding job she has done teaching CIS 545 and 550,” according to Department Chair Zack Ives.

Davidson says that it was Professor Loo who pushed her to revamp her CIS 550 (Introduction to Database and Information Systems), and reform it so it could become a part of the MCIT Online curriculum. Doing so required the course to be broken down into smaller, punchier segments: more frequent quizzes, a normally 90-minute lecture efficiently split into bite-sized, twelve-minute fragments.

“It was Boon who basically talked me into it, by saying how much it had improved his course,” said Davidson. “The argument that he used was that his teaching ratings had jumped up quite a bit as a result of that.”

Right in the middle of recording the different aspects of CIS 550, fine-tuning and taking a closer look at how to make it a more immersive experience for students, work-from-home was imposed due to COVID-19. Without knowing it, Professor Davidson was preparing for a complete online transition.

“That’s the second reason I’m very thankful to Boon. he convinced me to do this and gave me the impetus to improve the course and, by doing so, I was very well prepared for the teaching during the pandemic,” said Davidson. “I know the students really appreciated the quality of the recordings: that’s recognition to the online MCIT staff and the program and how well they are able to produce or help us produce our lecture segments.”

Boon Thau Loo

“Boon Thau Loo – Programming Network Policies by Examples: Platform, Abstraction, and User Studies”
Courtesy of NetPL YouTube

Professor Boon Thau Loo holds his colleague and fellow Spira Award winner in the highest regard as well.

“Anytime you got an opportunity to win an award with Susan that’s a great honor,” said Loo. “She’s always the gold standard for me as far as being a good teacher, being very dedicated to teaching.”

According to Professor Ives, the Associate Dean for SEAS Grad Programs “was recognized for his superb teaching and mentoring of students, both inside and beyond the classroom.  Students praise his clarity of explanations, his passion and expertise, and his positivity.”

Professor Loo serves as an inspiration for those with a calling to teach, but who must overcome personal obstacles in order to excel in that calling. He confesses that he did not start his career as an effective teacher: he is not naturally a good public speaker, and his initial Penn course student reviews were horrible.

“I remember my first CIS 505 was a complete disaster. I don’t have a tremendous stage presence,” said Loo. “As a clueless Assistant Professor, it took awhile for me to learn how to teach. I tried incorporate a more personal touch, get to know the students well.”

Professor Loo’s main classroom philosophies boil down to practicality: he emphasizes the importance of group work and communication, and insists a complete educational experience means getting your hands dirty.

“You cannot learn operating systems just by reading a textbook. Students have to learn by doing,” said Loo. “I’m a big proponent of project-based learning. I don’t think, especially in software systems, you can learn just in isolation, by reading a textbook or from PowerPoint.”

Duncan Watts’ “Everyone’s an Influencer” receives the 2021 WSDM Test-of-Time Award

Stevens University Professor Duncan Watts has recently been awarded the 2021 Test-of-Time Award at the 14th ACM International WSDM Conference for his paper titled “Everyone’s an Influencer: Quantifying Influence on Twitter,” published in 2011.

Pronounced “wisdom,” the WSDM (Web Search and Data Mining) Conference is one of many presented by ACM (Association for Computing Machinery), and “publishes original, high-quality papers related to search and data mining on the Web and the Social Web, with an emphasis on practical yet principled novel models of search and data mining, algorithm design and analysis, economic implications, and in-depth experimental analysis of accuracy and performance,” according to their site.

Professor Watts, a PIK (Penn Integrates Knowledge) professor with multiple appointments in the School of Engineering and Applied Science, the Annenberg School for Communication, and the Wharton School, received the honor along with project teammates Eytan Bakshy, Jake M. Hofman and Winter A. Mason.

The paper’s motivation stems from a years-old debate in the fields of communication, marketing and sociology: do ordinary folk have the power to spread ideas in media? When Malcolm Gladwell’s “The Tipping Point,” released in 2000, asserted that a very specific portion of regular people were the most effective at spreading and magnifying ideas and products, Professor Watts took up academic arms.

“I had been arguing against this idea for some time,” said Watts. “Not that some people are not more influential than others, but just that there was any sort of magical effect, that you could sort of find some ordinary person and they would somehow trigger this massive cascade that would that would change the world. Which is really sort of the the promise of this book, and why everybody loved it so much. “

Professor Watts and team approached the debate with a foundational scientific perspective: if certain people are more influential, then computer science should be able to predict it.

“If it’s true that certain types of people, for whatever reason, happened to be disproportionately influential in the world and disproportionately good at getting other people to listen to them and to change their minds about some issue, you can do pretty well predicting how many retweets someone’s going to get just by looking at how many followers they have,” said Watts.

Right before the paper was published, Professor Watts recalls that mega influencer Kim Kardashian, with roughly 1 million followers, was charging around $10,000 to mention a product in one tweet. The paper proposal offers that focusing on one influencer with a huge amount of followers is not necessarily the most efficient strategy.

“Maybe you want to pay your $10,000 but you would rather find 1,000 people who have 1,000 followers each,” said Watts. “And they might do it for free. Or they might do it for $1. So then you pay $1,000, and you still reach a million people.”

The three main findings of the paper are as follows:
1. It is nearly impossible to predict, with accuracy, the efficacy of influence
2. To the extent that one could predict it, “it’s all baked into the past success of the person who seeds the information, and most of it is just how many followers you have,” said Watts

And the 3rd:

“Under a broad range of conditions, you’re actually better off going with a large number of people who have not that many followers, then a small number of people with a large number of followers,” said Watts. “And I think each of those findings has sort of reverberated.”

Professor Joe Devietti steps into the role of CIS Undergrad Chair

When Associate Professor Joseph Devietti was an undergrad in the Department of Computer and Information Science almost 20 years ago, the pace and scale of the department was drastically different.

“Everything has just gotten so professionalized and competitive. Computing has kind of exploded, across campus,” said Devietti. “Things like the second major from the college is really exciting. To be able to give people other ways into computer science, without having to be an engineer and take physics. Follow that kind of rigid path.”

Now the coding aficionado has come full circle as he takes on the role of CIS Undergrad Chair.

“I think the undergrads that we have at Penn, even back when I was here a long time ago, were really strong,” said Devietti. “I’m glad I don’t have to compete with the undergrads that are here now.”

After majoring in both English and Computer and Information Science at Penn, Professor Devietti went on to get both his Master’s and his Ph.D. in Computer Science and Engineering at the University of Washington. With a slew of honors, awards and publications under his belt, CIS Department Chair Zack Ives also notes he is “renowned for his research in using both hardware and software techniques to simplify multiprocessor programming, [and] has also been a successful entrepreneur and an amazing mentor to many undergraduate, Master’s, and PhD students.”

Professor Andreas Haeberlen, whose shoes Professor Devietti will be stepping into, did wonders while serving as chair.

“One of the things I found inspiring about what Andreas had done in his time as undergrad chair was that he had helped a lot with kind of smoothing out these internal business processes,” said Devietti.

In addition to digitizing many paper processes, Professor Ives says Haeberlen also “led curriculum reform across our multiple degree programs [and] personally developed important infrastructure, including the waitlist system that allows us to manage student demand in a fair way.”

With returning to campus and the subsequent readjustment as a top priority, and the nearly 1,000 undergrad students currently enrolled in CIS, Professor Devietti believes the key lies in continuing to focus on efficiency.

“We need to try to streamline things as much as possible,” said Devietti. “I’ve been talking with the advising staff. There are other kinds of opportunities to just help things work more smoothly.”