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.
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.
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 â have contributed to this outcome.
However, according to Department of Computer and Information Science Professor Andreas Haeberlen, one of the main reasons contact tracing wasnât relatively more successful is simple: people donât’ feel comfortable sharing their information.
âIt’s really scary to think of people knowing all the things that you type in your phone,â said Haeberlen. âLike 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.â
Haeberlen, whose research centers distributed systems, networking, security, and privacy, believes that differential privacy could be the solution.
âDifferential privacy is a way to purpose private information so that you can really guarantee that somebody canât later learn something sensitive from this information,â said Haeberlen. â[It] has a very solid mathematical foundation.â
The National Institute of Science and Technology defines differential privacy in terms of mathematical qualification. âIt is not a specific process, but a property that a process can have,â said NIST on their website. âFor example, it is possible to prove that a specific algorithm âsatisfiesâ differential privacy.â
And so we might assert that, if an analysis of a database without Joe Citizenâs individual data and an analysis of a database with Joe Citizenâs individual data yield indistinguishable results, then differential privacy is satisfied. âThis implies that whoever sees the output wonât be able to tell whether or not Joeâs data was used, or what Joeâs data contained,â 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.
âFuzzi: A Three-Level Logic for Differential Privacy,â a paper by Haeberlen and fellow researchers Edo Roth, Hengchu Zhang, Benjamin C. Pierce and Aaron Roth, is one of many of Haeberlenâs 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 âis a novel sensitivity logic adapted from the linear-logic-inspired type system of Fuzz, a differentially private functional language,â according to the abstract.
Essentially, a researcher would input data into the tool, define what that data means, and specify what data output theyâre 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.
âThe way that we did that was by baking differential privacy into a programming language,â said Haeberlen. âAs a practitioner you don’t have to understand what differential privacy is, you also don’t have to be able to prove it.â
In the world of science, imprecision usually means error and gross miscalculation. However, in the more specific realm of differential privacy, imprecision equals security.
âImprecision is good because it causes the adversary to make mistakes,â said Haeberlen. In this case, the âadversaryâ 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.
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 Pennsylvaniaâs School of Engineering and Applied Science held a groundbreaking ceremony for its new data science building and unveiled the buildingâs official name, Amy Gutmann Hall, honoring Pennâs President. Amy Gutmann is the eighth and longest-serving President in Pennâs 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 Pennâs 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.
âI am thrilled Penn Engineeringâs new data science building will honor Dr. Gutmannâs remarkable legacy at Penn,â said Vijay Kumar, the Nemirovsky Family Dean of Penn Engineering. âHer Penn Compact and the principles of inclusion, innovation, and impact influenced the schoolâs 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.â
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 buildingâs 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.
âOur central mission is to integrate methods and ways of thinking from the computational and social sciences in the service of real-world applications,â said Lab Director and Stevens University Professor in the Department of Computer Science Duncan Watts. âWe 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. Iâm really looking forward to seeing what we can do.â
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 âdedicated to enhancing media transparency and accountability at the scale of the entire information ecosystem,â 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 Labâs Executive Director, Valery Yakubovich.
As a former professor at ESSEC Business School, Yakubovich is excited to bring his management expertise to the Lab.
âCreating 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,â said Yakubovich. âUnder the auspices of three professional schoolsâeach as renowned as it is independently-mindedâthis task is especially challenging but equally rewarding.â
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. Â
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 systemsâ 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.
âIn information extraction, knowing when to sample with real-time data makes a difference, says Saeedi Bidokhti. âIt 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.â
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."
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.”
It seems the Computer and Information Science department is in the business of cultivating students so fulfilled with their undergraduate experience, that they return to take on leadership roles in C.I.S. Earlier in the year, former C.I.S. undergrad and Associate Professor Joseph Devietti stepped into the role of Undergrad Chair. Now Lecturer Adam Mally, who graduated from C.I.S. in the Digital Media Design (DMD) Program, is stepping into the role of undergrad DMD Director.
“I started off in what’s now called the ESAP Summer Program, a summer program here at Penn Engineering were high school students can take a three-week long course in a particular subject,” said Mally.
When he applied to college the following winter, the DMD Program at C.I.S. was the only application he filled out.
“I loved that combination of technicality with the creativity that this provides.I needed to do DMD: this was so much fun.”
Currently, it’s fair to say that DMD’s biggest draw is gaming animation. Many, if not most, students join the program hoping to land jobs with large corporations within the games industry. Mally is excited to expand DMD’s reach: working with newcomers DanaĂ« Metaxa and Andrew Head, who are heading the incoming Penn HCI Group, is a top priority. There is much opportunity in the field of human computer interaction.
“So many DMDers go into the industry as technical directors or technical artists, where they’re developing tools that their teammates need to work with,” said Mally. “Pretty much any tool they developed needs to be usable by some other people and we don’t cover that aspect of software development at all right now.”
“It’s a pretty big field that we’re just not really getting too many people going through right now,” said Mally.“Integrating into existing classes, or at least a particular existing class: a look at how computer graphics can be used in medicine to visualize, or pre-visualize in some cases, scan data. Or even how people use augmented reality or virtual reality to do medical training.”
At the end of the day, Mally believes that the same things that lit his own DMD fire are essentially what will continue to attract new students year after year.
“They have a huge passion for for the creative aspects that DMD allows them to explore,” said Mally. “I want people to have the knowledge to be able to make games, but I want people to have the tools, the skill set to be able to branch out on their own.”
The Penn Center for Innovation (PCI) has put together a fall speaker series focused on resources available for Penn Engineering faculty and students, featuring C.I.S. Professor and GRASP Lab Director Mark Yim. All are welcome to register for each session separately at pci-seas.eventbrite.com.
Sept 21: Penn I-Corps with Mark Yim, PhD, ASA Whitney Professor of Mechanical Engineering, Director of GRASP Lab, Faculty Director for the Design Studio
Oct 13: Med Tech Devices with Katherine Reuther, Ph.D., MBA, Executive Director of the Penn Center for Health-Devices and Technology
Nov 10: Pennovation Works and Resources for Startups with Anish Kumar, Managing Director of Pennovation Works
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.
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.”
