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Program Events

Events

• Dec

  8

  CS Seminar - Kathryn Cunningham "Diversifying Pathways to Computer Science Education"

  Department of Computer Science

  12:00 PM

  EVENT DETAILS

  This will be a virtual seminar
  
  Abstract
  Computer science departments are faced with skyrocketing enrollments as more students recognize the opportunities that computing provides. Surprisingly, this growth is fueled by an increase in non-majors more than an increase in computer science majors. As computing becomes a more universal subject, like English or Mathematics, we must investigate whether current instructional approaches work equally well for everyone, or present barriers for some more than others. How can we address the learning needs of students who are increasingly diverse in terms of goals, interests, and prior experience? In this talk, I will present three examples of computing education innovations from my research that draw on program comprehension, educational psychology, and the study of higher education. Through my work, I have developed new approaches to support the success of a variety of undergraduates as they study computing, including female non-majors, traditional computer science majors, and low-income community college transfer students.
  

  Biography
  Dr. Kathryn Cunningham is a Postdoctoral Scholar and CIFellow at Northwestern University. Her passion is addressing inequities in computing education by diversifying and improving the way we support students at the undergraduate level. She received her PhD from the University of Michigan in Information, her MSc from Georgia Tech in Computer Science (Human-centered Computing), and her BS from the University of Arizona in Computer Science and Molecular and Cellular Biology.
  

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  TIME Wednesday, December 8, 2021 at 12:00 PM - 1:00 PM

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  CONTACT Pamela Villalovoz    pmv@northwestern.edu EMAIL

  CALENDAR Department of Computer Science

• Apr

  19

  CS Seminar: Hardware-Aware Efficient Primitives for Machine Learning (Dan Fu)

  Department of Computer Science (CS)

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

  EVENT DETAILS

  

  Friday / CS Seminar
  April 19th / 12:00 PM
  In Person / Mudd 3514

  Speaker
  Dan Fu, Stanford University

  Talk Title
  Hardware-Aware Efficient Primitives for Machine Learning

  Abstract
  Efficiency is increasingly tied to quality to machine learning, with more efficient training algorithms leading to more powerful models. However, today's most popular machine learning models are built on asymptotically inefficient primitives. For example, attention in Transformers scales quadratically in the input size, while MLPs scale quadratically in model dimension. In this talk, I discuss my work on improving the efficiency of the core primitives in machine learning, with an emphasis on hardware-aware algorithms and long-context applications. First, I focus on replacing attention with gated state space models (SSMs) and convolutions, which scale sub-quadratically in context length. I describe the H3 (Hungry Hungry Hippos) architecture, a gated SSM architecture that matches Transformers in quality up to 3B parameters and achieves 2.4x faster inference. Second, I focus on developing hardware-aware algorithms for SSMs and convolutions. I describe FlashFFTConv, a fast algorithm for computing SSMs and convolutions on GPU by optimizing the Fast Fourier Transform (FFT). FlashFFTConv yields up to 7x speedup and 5x memory savings, even over vendor solutions from Nvidia. Third, I will briefly touch on how these same techniques can also be used to develop sub-quadratic scaling in the model dimension. I will describe Monarch Mixer, which uses a generalization of the FFT to achieve sub-quadratic scaling in both sequence length and model dimension. Throughout the talk, I will give examples of how these ideas are beginning to take hold, with gated SSMs and their variants now leading to state-of-the-art performance in long-context language models, embedding models, and DNA foundation models.

  Biography
  Dan Fu is a PhD student in the Computer Science Department at Stanford University, where he is co-advised by Christopher Ré and Kayvon Fatahalian. His research interests are at the intersection of systems and machine learning. Recently, he has focused on developing algorithms and architectures to make machine learning more efficient, especially for enabling longer-context applications. His research has appeared as oral and spotlight presentations at NeurIPS, ICML, and ICLR, and he has received the best student paper runner up at UAI. Dan has also been supported by an NDSEG fellowship.

  Research Area/Interests
  machine learning, systems

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  TIME Friday, April 19, 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

  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: Kaize Ding

  Department of Computer Science (CS)

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

  EVENT DETAILS

  TBA

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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 Seminar: Tong Zhang

  Department of Computer Science (CS)

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

  EVENT DETAILS

  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

  3

  CS Seminar: Shafi Goldwasser

  Department of Computer Science (CS)

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

  EVENT DETAILS

  TBA

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  TIME Friday, May 3, 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

  ADD TO CALENDAR

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

  CALENDAR Department of Computer Science (CS)