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Department Events & Announcements

Events

• Mar

  26

  CS Colloquium - Ashwin Pananjady - "Statistics meets computation: Trade-offs between interpretability and flexibility"

  Department of Computer Science

  12:00 PM Room 3514, Mudd Hall ( formerly Seeley G. Mudd Library)

  EVENT DETAILS

  https://northwestern.zoom.us/j/339193711
  Meeting ID: 339 193 711

  Title:
  Statistics meets computation: Trade-offs between interpretability and flexibility

  Abstract
  

  Modeling and tractable computation form two fundamental but competing pillars of data science; indeed, fitting models to data is often computationally challenging in modern applications. At the same time, a "good" model is one that imposes the right kind of structure on the underlying data-generating process, and this involves trading off the competing objectives of interpretability and flexibility. With a focus on balancing these tensions, I present tractable methodological solutions for fitting flexible models in some canonical machine learning tasks.

  The bulk of the talk will focus on a class of “permutation-based" models, which present a flexible alternative to parametric modeling in a host of inference problems involving data generated by people. I introduce a set of algorithmic tools that handles structured missing data and breaks a conjectured computational barrier, demonstrating that carefully chosen non-parametric structure can significantly improve robustness to mis-specification while maintaining interpretability. To conclude the talk, I draw on this perspective to study modeling and computation in high-dimensional regression and reinforcement learning. A focus on exploiting structure in these contexts leads to novel algorithmic as well as statistical insight.

  Biography
  

  Ashwin Pananjady is a PhD student in the Department of Electrical Engineering and Computer Sciences at the University of California Berkeley, advised by Martin Wainwright and Thomas Courtade. His interests lie broadly in statistics, machine learning, information theory, and optimization, and include ranking and permutation estimation, high-dimensional statistics, and reinforcement learning. He is a recipient of the inaugural Lawrence Brown PhD student award from the Institute of Mathematical Statistics, an Outstanding Graduate Student Instructor award from UC Berkeley, and the Governor's Gold Medal from IIT Madras.

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  TIME Thursday, March 26, 2020 at 12:00 PM - 1:00 PM

  LOCATION Room 3514, Mudd Hall ( formerly Seeley G. Mudd Library)    map it

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  CONTACT Pam Villalovoz    pmv@northwestern.edu EMAIL

  CALENDAR Department of Computer Science

• Apr

  24

  CS Seminar: AI Powered Movement Analysis, Big Rehabilitation Data and a Path to Precision Rehabilitation (R. James Cotton)

  Department of Computer Science (CS)

  12:00 PM 3514, Mudd Hall ( formerly Seeley G. Mudd Library)

  EVENT DETAILS

  

  Wednesday / CS Seminar
  April 24th / 12:00 PM
  In Person / Mudd 3514

  Speaker
  R. James Cotton, Northwestern University & Shirley Ryan AbilityLab

  Talk Title
  AI Powered Movement Analysis, Big Rehabilitation Data and a Path to Precision Rehabilitation

  Abstract
  This talk will discuss multiple methodological lines of work making movement and gait analysis more clinically accessible and biomechanically grounded. This includes reconstruction from synchronized multiview videos, smartphone videos, and wearable sensors. We will also discuss how implicit functions provide a powerful representation to map from time to joint angles, and GPU accelerated methods that enable end-to-end biomechanical fits from these different modalities. It will discuss some of the opportunities that large movement data enables, including the use of self-supervised learning to discover gait representations that can function as both diagnostic and response biomarkers. Finally, we will outline a vision for a Causal Framework for Precision Rehabilitation that can model this data to link from impairment to function and identify the optimal dynamic treatment policies to improve rehabilitation outcomes.

  Biography
  I am an electrical engineer, neuroscientist, and physiatrist working as a physician-scientist at Shirley Ryan AbilityLab and Assistant Professor in the Northwestern University Department of Physical Medicine and Rehabilitation. I completed my residency in PM&R at Shirley Ryan AbilityLab (formers Rehabilitation Institute of Chicago) where I remained as faculty. Prior to that I obtained a B.S. in Electrical Engineering from Rice University followed by an MD and PhD in systems neuroscience from Baylor College of Medicine. My lab works at the intersection of artificial intelligence, wearable sensors, computer vision, causal and biomechanical modeling, and novel technologies to more precisely monitor and improve rehabilitation outcomes.

  Research Area/Interests
  AI, computer vision, gait analysis, wearable sensors, rehabilitation

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  TIME Wednesday, April 24, 2024 at 12:00 PM - 1:00 PM

  LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library)    map it

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  CONTACT Wynante R Charles    wynante.charles@northwestern.edu EMAIL

  CALENDAR Department of Computer Science (CS)

• Apr

  25

  TGI Bagel Thursday

  Department of Computer Science (CS)

  9:00 AM 3514, Mudd Hall ( formerly Seeley G. Mudd Library)

  EVENT DETAILS

  

  Spring is finally here. Enjoy the good vibes to come with some free bagels and coffee courtesy the Computer Science Department. Mix and mingle with fellow CS students and faculty every last Thursday of the month.

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  TIME Thursday, April 25, 2024 at 9:00 AM - 11:00 AM

  LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library)    map it

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  CONTACT Wynante R Charles    wynante.charles@northwestern.edu EMAIL

  CALENDAR Department of Computer Science (CS)

• Apr

  29

  CS Seminar: Data-Efficient Graph Learning (Kaize Ding)

  Department of Computer Science (CS)

  12:00 PM 3514, Mudd Hall ( formerly Seeley G. Mudd Library)

  EVENT DETAILS

  

  Monday / CS Seminar
  April 29th / 12:00 PM
  Hybrid / Mudd 3514

  Speaker
  Kaize Ding, Northwestern University

  Talk Title
  Data-Efficient Graph Learning
  
  Abstract
  The world around us -- and our understanding of it -- is rich in relational structure: from atoms and their interactions to objects and entities in our environments. Graphs, with nodes representing entities and edges representing relationships between entities, serve as a common language to model complex, relational, and heterogeneous systems. Despite the success of recent deep graph learning, the efficacy of existing efforts heavily depends on the ideal data quality of the observed graphs and the sufficiency of the supervision signals provided by the human-annotated labels, leading to the fact that those carefully designed models easily fail in resource-constrained scenarios.

  In this talk, I will present my recent research contributions centered around data-efficient learning for relational and heterogeneous graph-structured data. First, I will introduce what data-efficient graph learning is and my contributions to different research problems under its umbrella, including graph few-shot learning, graph weakly-supervised learning, and graph self-supervised learning. Based on my work, I will elucidate how to push forward the performance boundary of graph learning models especially graph neural networks with low-cost human supervision signals. I will also touch upon the real-world applications of data-efficient graph learning to different domains and finally conclude my talk with a brief overview of my future research agenda.

  Biography
  Kaize Ding is an Assistant Professor in the Department of Statistics and Data Science at Northwestern University. Before joining Northwestern, he obtained his Ph.D. degree in Computer Science at Arizona State University in 2023 under the supervision of Prof. Huan Liu. His research interests are generally in data mining, machine learning, and natural language processing, with a particular focus on graph machine learning, data-efficient learning, and reliable AI. His work has been published in top-tier conferences and journals (e.g., AAAI, EMNLP, IJCAI, KDD, NeurIPS, TheWebConf, and TNNLS), and has been recognized with several prestigious awards and honors, including the AAAI New Faculty Highlights, SDM Best Posters Award, Best Paper Award at the Trustworthy Learning on Graphs workshop, etc.

  Research Area/Interests
  Data Mining; Machine Learning; Natural Language Processing

  Zoom: https://northwestern.zoom.us/j/99555833103?pwd=TEtaakVGL2xUYytDa2Nvbk14Z3VhUT09

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  TIME Monday, April 29, 2024 at 12:00 PM - 1:00 PM

  LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library)    map it

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  CONTACT Wynante R Charles    wynante.charles@northwestern.edu EMAIL

  CALENDAR Department of Computer Science (CS)

• May

  1

  CS Distinguished Lecture: Tong Zhang

  Department of Computer Science (CS)

  12:00 PM 3514, Mudd Hall ( formerly Seeley G. Mudd Library)

  EVENT DETAILS

  Wednesday / CS Distinguished Lecture
  May 1st / 12:00 PM
  Hybrid / Mudd 3514

  Speaker
  Tong Zhang, University of Illinois Urbana-Champaign

  Talk Title
  TBA

  Abstract
  TBA

  Biography
  TBA

  Research Area/Interests
  TBA

  Zoom: TBA

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  TIME Wednesday, May 1, 2024 at 12:00 PM - 1:00 PM

  LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library)    map it

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  CONTACT Wynante R Charles    wynante.charles@northwestern.edu EMAIL

  CALENDAR Department of Computer Science (CS)

• May

  8

  CS Distinguished Lecture: Monica Lam

  Department of Computer Science (CS)

  12:00 PM 3514, Mudd Hall ( formerly Seeley G. Mudd Library)

  EVENT DETAILS

  Wednesday / CS Distinguished Lecture
  May 8th / 12:00 PM
  Hybrid / Mudd 3514

  Speaker
  Monica Lam, Stanford University

  Talk Title
  TBA

  Abstract
  TBA

  Biography
  TBA

  Research Area/Interests
  TBA

  Zoom
  TBA

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  TIME Wednesday, May 8, 2024 at 12:00 PM - 1:00 PM

  LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library)    map it

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  CONTACT Wynante R Charles    wynante.charles@northwestern.edu EMAIL

  CALENDAR Department of Computer Science (CS)

• May

  8

  Extending Care: A Conversation about Conservation and Futurity

  Block Museum of Art

  6:00 PM Block Museum of Art, Mary and Leigh

  EVENT DETAILSmore info

  The Center for Scientific Studies in the Arts is a collaboration between the Art Institute of Chicago and materials science-related departments at Northwestern University to pursue objects-based and objects-inspired scientific research. Materials research benefits ongoing work in conservation, archaeology, art history, and curatorial scholarship.

  Learn how the Center uses materials research to care for art objects in sustainable, innovative ways with Maria Kokkori, Senior Scientist in the Center for Scientific Studies in the Arts. She will be in conversation with Corey Byrnes, Northwestern Associate Professor of Chinese Culture and co-founder/co-director of the Environmental Humanities Workshop in Kaplan Humanities Center.

  This event is presented by the McCormick School of Engineering and Applied Science in conjunction with exhibition Actions for the Earth: Art, Care & Ecology.

  Register Now

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  TIME Wednesday, May 8, 2024 at 6:00 PM - 7:30 PM

  LOCATION Block Museum of Art, Mary and Leigh    map it

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  CONTACT Block Museum of Art    block-museum@northwestern.edu EMAIL

  CALENDAR Block Museum of Art

• May

  10

  CS Distinguished Lecture: Trust, Backdoor Vulnerabilities and Possible Mitigations (Shafi Goldwasser)

  Department of Computer Science (CS)

  12:00 PM 3514, Mudd Hall ( formerly Seeley G. Mudd Library)

  EVENT DETAILS

  Friday / CS Distinguished Lecture
  May 10th / 12:00 PM
  Hybrid / Mudd 3514

  Speaker
  Shafi Goldwasser; Simons Institute for the Theory of Computing, University of California Berkeley

  Talk Title
  Trust, Backdoor Vulnerabilities and Possible Mitigations

  Abstract
  Cryptographic tools and models enable to trust the use of technology platforms controlled by worst case computationally bounded adversaries. In this talk I will use cryptographic modeling and tools to view trust dilemmas in various phases of the machine learning pipelines. We will touch on privacy in the training stage, verification of properties of
  machine learning models, and the possibility of achieving robustness in presence of backdoors.

  Biography

  Shafi Goldwasser is Director of the Simons Institute for the Theory of Computing, and Professor of Electrical Engineering and Computer Science at the University of California Berkeley. Goldwasser is also the RSA Professor (post tenure) of Electrical Engineering and Computer Science at MIT and Professor Emeritus of Computer Science and Applied Mathematics at the Weizmann Institute of Science, Israel. Goldwasser holds a B.S. Applied Mathematics from Carnegie Mellon University (1979), and M.S. and Ph.D. in Computer Science from the University of California Berkeley (1984).

  Goldwasser's contributions include the introduction of probabilistic encryption, interactive zero knowledge protocols, elliptic curve primality testings, hardness of approximation proofs for combinatorial problems, combinatorial property testing, and pseudo deterministic algorithms.

  Goldwasser was the recipient of the ACM Turing Award in 2012, the Gödel Prize in 1993 and in 2001, the ACM Grace Murray Hopper Award in 1996, the RSA Award in Mathematics in 1998, the ACM Athena Award for Women in Computer Science in 2008, the Benjamin Franklin Medal in 2010, the IEEE Emanuel R. Piore Award in 2011, the Simons Foundation Investigator Award in 2012, and the BBVA Foundation Frontiers of Knowledge Award in 2018. Goldwasser is a member of the NAS, NAE, AAAS, the Russian Academy of Science, the Israeli Academy of Science, the London Royal Mathematical Society and a Foreign Member of the Royal Society. Goldwasser holds honorary degrees from Ben Gurion University, Bar Ilan University, Carnegie Mellon University, Haifa University, University of Oxford, and the University of Waterloo, and has received the UC Berkeley Distinguished Alumnus Award and the Barnard College Medal of Distinction.

  Research Area/Interests
  Cryptography, Complexity, Probabilistic Algorithms

  Zoom: TBA

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  TIME Friday, May 10, 2024 at 12:00 PM - 1:00 PM

  LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library)    map it

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  CONTACT Wynante R Charles    wynante.charles@northwestern.edu EMAIL

  CALENDAR Department of Computer Science (CS)

• May

  30

  TGI Bagel Thursday

  Department of Computer Science (CS)

  9:00 AM 3514, Mudd Hall ( formerly Seeley G. Mudd Library)

  EVENT DETAILS

  TBA

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  TIME Thursday, May 30, 2024 at 9:00 AM - 11:00 AM

  LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library)    map it

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  CONTACT Wynante R Charles    wynante.charles@northwestern.edu EMAIL

  CALENDAR Department of Computer Science (CS)

• May

  30

  End of Year Awards

  Department of Computer Science (CS)

  3:00 PM TBA, Mudd Hall ( formerly Seeley G. Mudd Library)

  EVENT DETAILS

  TBA

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  TIME Thursday, May 30, 2024 at 3:00 PM - 5:00 PM

  LOCATION TBA, Mudd Hall ( formerly Seeley G. Mudd Library)    map it

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  CONTACT Wynante R Charles    wynante.charles@northwestern.edu EMAIL

  CALENDAR Department of Computer Science (CS)

• Jun

  10

  Northwestern Engineering PhD Hooding and Master's Degree Recognition Ceremony

  McCormick School of Engineering and Applied Science

  9:00 AM Welsh-Ryan Arena

  EVENT DETAILSmore info

  McCormick School of Engineering PhD Hooding and Master’s Degree Recognition Ceremony

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  TIME Monday, June 10, 2024 at 9:00 AM - 11:00 AM

  LOCATION Welsh-Ryan Arena   

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  CONTACT Amy Pokrass    amy.pokrass@northwestern.edu EMAIL

  CALENDAR McCormick School of Engineering and Applied Science

• Jun

  10

  Northwestern Engineering Undergraduate Convocation

  McCormick School of Engineering and Applied Science

  2:00 PM Welsh-Ryan Arena

  EVENT DETAILSmore info

  McCormick School of Engineering Undergraduate Convocation

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  TIME Monday, June 10, 2024 at 2:00 PM - 4:00 PM

  LOCATION Welsh-Ryan Arena   

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  CONTACT Amy Pokrass    amy.pokrass@northwestern.edu EMAIL

  CALENDAR McCormick School of Engineering and Applied Science