CS Seminars

"Why Do Students Think They're Bad at Programming? Towards Intelligent Systems to Support Motivation and Learning in CS1"

Abstract

In this talk, I will introduce a surprising motivational challenge in the domain of computer science education: students often think they're bad at programming, even when they are performing well. I will present a series of studies showing that students in introductory courses assess their own programming ability frequently, using criteria that are often misaligned with best practices (e.g. "I should be able to debug quickly based off a first glance"; "I shouldn't have to sit there and think"). Then, I will show how we can use these self-assessment criteria as a lens to better understand student experiences and the ways they approach learning. Finally, I will present research exploring the design of intelligent programming environments that can automatically detect potential self-assessment moments and provide feedback to help students re-frame these experiences. Through this body of work, I will demonstrate the value of conducting research that crosses the boundaries of human-computer interaction and the learning sciences to deeply understand learning contexts and inform the design of novel learning environments.

Biography

Eleanor O'Rourke is an Assistant Professor in Computer Science and the Learning Sciences at Northwestern University, where she co-directs the interdisciplinary Delta Lab. Her research explores the design of novel computational systems to support motivation and learning in STEM domains. Recent projects include studying student beliefs about programming ability in introductory computer science courses, designing game mechanics that encourage students to practice effective problem-solving skills, and developing web inspection tools that allow novice developers to learn directly from authentic professional websites. Her interventions have been used by over 100,000 students online, adopted by companies, and integrated into classrooms. Her work has been recognized through an NSF CAREER Award, a Google Systems Research Award, and best paper awards and nominations at SIGCSE, UIST, and CHI.

Zoom Link: https://northwestern.zoom.us/j/96480997253?pwd=Y1E1aS80S1NZZXpaV2J0dDdLVXNzUT09

Panopto: https://northwestern.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=39549fbf-0bc0-4487-a00e-b09a00fa3f20

"Reshaping Computer Systems for the New Hardware Landscape"

Abstract

Modern computer systems have been built on foundations that were devised decades ago. However, computer hardware has changed significantly since then, as have the demands of users. Many of these foundational concepts still serve us well. On several occasions, though, the decades-old customary practice prevents us from realizing better figures of merit, such as higher performance, lower power, lower energy consumption or easier programming. CMOS transistors have served us well for six decades, but severely constrain us today; emerging devices offer exciting new opportunities. Memory systems were conceptualized in the ‘60s, but struggle to harness the capabilities of contemporary technologies; sophisticated users and hardware already go to great lengths to circumvent their aged abstractions. Parallel programming is still a formidable endeavor, but no system today, not even a single core, can deliver more than half its peak performance without it. In this talk, I will discuss our efforts to rethink some of the aspects of present-day computer systems and reshape them for the new hardware landscape.

Biography

Nikos Hardavellas is an associate professor of Computer Science and Computer Engineering at Northwestern University, where he directs the Parallel Architecture Group at Northwestern (PARAG@N, http://paragon.cs.northwestern.edu/). His research interests are at the intersection of computer architecture and nanophotonics, parallel systems, microarchitecture, design for dark silicon, and quantum computer systems. Nikos is the recipient of the June and Donald Brewer Chair at Northwestern University (2009), an NSF CAREER award (2015), a Faculty Service award (2022), was included in the Associated Student Government Faculty Honor Roll (2022), was a keynote speaker at IEEE ISPDC (2010), and became a Fellow of the Searle Center for Teaching Excellence in 2012. He received best paper awards, nominations and test-of-time awards at HPCA (2022), ISLPED (2021), EDBT (2019) and ICDE (2006), an IEEE Micro Top Picks Award (2010), an IEEE Micro Top Picks Honorable Mention (2023), and a Technical Award for Contributions to the Alpha Microprocessor (2000). Prior to joining Northwestern University, he contributed to the design of several generations of Alpha microprocessors and high-end multiprocessor servers at Digital Equipment Corp. (DEC), Compaq, and Hewlett-Packard. Nikos received a Ph.D. in Computer Science from Carnegie Mellon University.

Zoom Link: https://northwestern.zoom.us/j/95896781741?pwd=eUc2bGVmcGFGZ1o2K2tacjgxWXlOQT09

Panopto: https://northwestern.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=283ecdf8-2214-446a-afb1-b09a010e39c3

Research Interests/Area
Computer architecture, nanophotonics, parallel systems, microarchitecture, design for dark silicon, memory-oriented systems, and quantum computer systems.

"Fortifying Cloud Data Privacy: Achieving Fault Tolerance and High Performance in Oblivious Databases"

Abstract

Over 94% of today's enterprises, including 83% of healthcare organizations, have embraced cloud services for their infrastructure and data storage needs. They opt for third-party cloud providers due to the cost and resource savings compared to maintaining on-premise storage and computing systems. However, entrusting plaintext application data to these providers can expose sensitive information to potentially untrustworthy entities. While data encryption is the initial step in ensuring data privacy, a growing array of attacks exploit user access patterns on encrypted data to reveal the plaintext content.

Oblivious databases are storage systems that conceal user access patterns to safeguard against such threats. However, most existing oblivious databases face issues such as single points of failure and high performance overheads. In this talk, I will introduce two solutions addressing these challenges: 1. QuORAM: the first replicated oblivious RAM-based datastore that offers both fault tolerance and high availability while efficiently safeguarding access patterns; and 2. Waffle: an oblivious datastore that grants the flexibility of tunable privacy, enabling intelligent trade-offs between privacy and performance.

Biography

Sujaya Maiyya is an Assistant Professor at University of Waterloo. She is part of the Data Systems Group and Cybersecurity and Privacy Institute at Waterloo. She received her PhD from UC Santa Barbara. Her research interests lie in the intersection of data management, distributed systems, and data privacy. She is a recipient of the NSERC Discovery Grant. During her PhD, Sujaya received IBM PhD Fellowship and Google PhD Fellowship (declined) awards for 2020-22, as well as being selected for the MIT EECS Rising Stars 2021. She is also a core member of Diversity & Inclusion in Databases initiative, striving for DEI efforts in the database community.

Zoom Link: https://northwestern.zoom.us/j/96094084202?pwd=NHhYc3hQNlRWYVdYeUY3SFF3NFF5QT09

Panopto: https://northwestern.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=d4eedb59-88a3-4262-a9a5-b0a1012a07c2

Research Interests/Area
distributed data systems and data privacy

"Computer Architectures for Neural Interfaces"

Abstract

Neural interfaces will help us treat brain disorders, augment the healthy brain, and shed light on how the brain as an organ gives rise to the mind. Delivering on this promise requires the design of computer systems that delicately balance the tight power, latency, and bandwidth trade-offs needed to decode brain activity, stimulate biological neurons, and control assistive devices most effectively.

This talk presents my group's design of a standardized and general computer architecture for future brain interfacing. Our design enables the treatment of several neurological disorders (most notably, epilepsy and movement disorders) and lays the groundwork for brain interfacing techniques that can help augment cognitive control and decision-making in the healthy brain.

Central to our design is end-to-end hardware acceleration, from the microarchitectural to the distributed system level. Key insights are undergirded via detailed physical synthesis models and chip tape-outs in a 12nm CMOS process.

Biography

Abhishek Bhattacharjee is a computer architect and a Professor of Computer Science at Yale University. His group's work has spanned the areas of memory management, the hardware/software interface, and most recently, computer systems for the brain sciences. Abhishek's work on address translation has been adopted in billions of real-world microprocessors and operating systems, for which he was the recipient of the 2023 ACM SIGARCH Maurice Wilkes Award.

Zoom Link: https://northwestern.zoom.us/j/94978708286?pwd=TmR0aHd0Ky9NbWVDdEQzeTdhSVVWQT09

Panopto: https://northwestern.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=cb0806e4-b9a4-4272-a8ff-b0a1012bddbc

Research Interests/Area
distributed data systems and data privacy

CS Department Events

CSPAC Tuesday Student Seminars

CSPAC is launching a student seminar series within the CS department. It will run on Tuesdays (12-1pm in 3514 with lunch, like the other seminars).  

The goal is to showcase student research in the department, and to give students an opportunity to give broad audience talks. You can find an overview of the format and goals here.

If you are a PhD student and you are interested in presenting, please reach out to (Vaidehi Srinivas, vaidehi@u.northwestern.edu) directly, and we can schedule a week that works for you.  A tentative schedule can be found here.

While the presenters will be PhD students, everyone in the CS department community (faculty, postdocs, students of all levels, etc.) are invited to attend!

What is CSPAC?

We are the CS PhD Advisory Council.  We are a PhD student-led organization, and our mandate is to interface between PhD students and faculty on academic issues.  Some examples of what we do include: identifying issues in the PhD program and providing input to faculty, and organizing events like the CS Open House and this student seminar series.  (Not to be confused with CSSI– the CS Social Initiative, another student-led organization that organizes social events for the department.)

We want to advocate for PhD students in the department, so if there is some way we can support you, please come talk to us.  We welcome PhD students to our weekly meetings on Tuesdays, 5-5:30pm, Mudd 3501 and/or zoom.  We also welcome anonymous concerns/feedback at any time via this form.  Anyone in the community can reach us at cspac@u.northwestern.edu.

TGI Bagel Thursday

Trust Perspectives in Machine Learning, Law, and Public Policy

RacketCon

Other Events & Opportunities

2023 IIN Symposium: Addressing Global Challenges Through Nanotechnology

CS News

NU News