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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!

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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!

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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.
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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.