Upcoming CS Seminars

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"Video Data Management with VOCAL"

Abstract

The proliferation of inexpensive high-quality cameras coupled with recent advances in machine learning and computer vision have enabled new applications on video data. This in turn has renewed interest in video data management systems (VDMSs). In this talk, we explore data management techniques to help users ask complex queries over video data and receive query results with precise semantics as well as techniques to help users with early video exploration and organization. We present two sub-systems of our broader VOCAL project: EQUI-VOCAL and VOCALExplore, both available open source through our project website.

Biography

Magdalena Balazinska is Professor, Bill & Melinda Gates Chair, and Director of the Paul G. Allen School of Computer Science & Engineering at the University of Washington. Magdalena's research interests are in the field of database management systems. Her current research focuses on data management for data science, big data systems, cloud computing, and image and video analytics. Prior to her leadership of the Allen School, Magdalena was the Director of the eScience Institute, the Associate Vice Provost for Data Science, and the Director of the Advanced Data Science PhD Option. She also served as Co-Editor-in-Chief for Volume 13 of the Proceedings of the Very Large Data Bases Endowment (PVLDB) journal and as PC co-chair for the corresponding VLDB'20 conference. Magdalena is an ACM Fellow. She holds a Ph.D. from the Massachusetts Institute of Technology (2006). Shortly after her arrival at the University of Washington, she was named a Microsoft Research New Faculty Fellow (2007). Magdalena received the inaugural VLDB Women in Database Research Award (2016) for her work on scalable distributed data systems. She also received an ACM SIGMOD Test-of-Time Award (2017) for her work on fault-tolerant distributed stream processing and a 10-year most influential paper award (2010) from her earlier work on reengineering software clones.

Zoom Link: https://northwestern.zoom.us/j/93870604354?pwd=N1BUK2Q1emNXL25XTlVCdFZEVHRsUT09

Panopto: https://northwestern.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=6ef43831-a848-4a2e-94f4-b0ab014c833d

Research Interests/Area
Data management

"Tools for Hypothesizing Effects in Analysis and Science"

Abstract

A host of visualization and interactive tools aim to support learning from data to inform decision-making. However, attempts to design for exploratory data analysis and other analytical tasks are frequently based on overly simplified views of statistical workflow. Consequently, users may engage in pattern-finding at the expense of recognizing uncertainty or considering potential sources of heterogeneity and variation in the effects they seek to discover. I will describe how goals like facilitating model checking and supporting rational decision-making have led me and collaborators to develop novel software designs and evaluative frameworks for analysis and visualization tools. For example, rethinking the goals of exploratory data analysis software led us to develop Exploratory Visual Modeling (EVM), a Tableau-style GUI visual analysis tool with built-in statistical modeling support that enables analysts to check their provisional interpretations of data in an exploratory session. Motivated by the heavy reliance on average treatment effects in data-driven science, Causal Quartets depict possible patterns of variation compatible with an average treatment effect at the level of individual units, helping modelers consider the implications of effect heterogeneity for downstream policy decisions. Relatedly, the difficulty of identifying what has been learned about the value of a better visualization from the typical evaluative study informed our development a rational agent framework for benchmarking attainable performance with a data-driven interface. Using our framework, researchers can design better experiments for studying interface performance, and better explain losses in performance they observe.

Biography

Jessica Hullman is Ginni Rometty Associate Professor of Computer Science at Northwestern University. Her research addresses challenges and limitations that arise when people draw inductive inferences from data. Her work has contributed multiple visualization and interaction techniques for improving reasoning under uncertainty from data-driven interfaces, as well as theoretical frameworks for understanding the role of visualization in statistical workflow. Jessica's work has been awarded best paper awards at top visualization and HCI venues, a Microsoft Faculty award and NSF CAREER, Medium, and Small awards as PI, among others.

Zoom Link: https://northwestern.zoom.us/j/97908273578?pwd=aUxFZ1Npc3oyNFdrSmQrdHU0QldlZz09 

Panopto: https://northwestern.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=c4bec2ac-083e-4ed8-bb93-b0af011b0a8d

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.

IDEAL: New Perspectives on Data Science with Imperfect Data

Other Events & Opportunities

Native American and Indigenous Heritage Month

Greg Reardon, University of California Santa Barbara, RE Touch Lab, "Wave-Mediated Haptics: Leveraging Wave Transport for Dynamic Tactile Feedback"

CS News

NU News