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Department Events & Announcements

Events

• Feb

  6

  CS Seminar: Aligning Machine Learning, Law, and Policy for Responsible Real-World Deployments (Peter Henderson)

  Department of Computer Science (CS)

  10:00 AM 3514, Mudd Hall ( formerly Seeley G. Mudd Library)

  EVENT DETAILS

  Monday / CS Seminar
  February 6th / 10:00 AM
  Mudd 3514

  Title: Aligning Machine Learning, Law, and Policy for Responsible Real-World Deployments
  Speaker: Peter Henderson

  Abstract:

  Machine learning (ML) is being deployed to a vast array of real-world applications with profound impacts on society. ML can have positive impacts, such as aiding in the discovery of new cures for diseases and improving government transparency and efficiency. But it can also be harmful: reinforcing authoritarian regimes, scaling the spread of disinformation, and exacerbating societal biases. As we rapidly move toward systemic use of ML in the real world, there are many unanswered questions about how to successfully use ML for social good while preventing its potential harms. Many of these questions inevitably require pursuing a deeper alignment between ML, law, and policy. Are certain algorithms truly compliant with current laws and regulations? Is there a better design that can make them more in tune to the regulatory and policy requirements of the real world? Are laws, policies, and regulations sufficiently informed by the technical details of ML algorithms, or will they be ineffective and out-of-sync? In this talk, I will discuss ways to bring together ML, law, and policy to address these questions. I will draw on real-world examples throughout the talk, including a unique real-world collaboration with the Internal Revenue Service. I will show how investigating questions of alignment between ML, law, and policy can advance core research in ML, as well as how we might develop new algorithms to expand policy and regulatory options. It is my hope that the tools discussed in this talk will help us lead to more effective and responsible ways of deploying ML in the real world, so that we steer toward positive impacts and away from potential harms.

  Biography:
  Peter Henderson is a joint JD-PhD (Computer Science) candidate at Stanford University advised by Dan Jurafsky. He is also an OpenPhilanthropy AI Fellow, a Graduate Student Fellow at the Stanford RegLab working closely with Daniel E. Ho, and technical advisor at the Institute of Security and Technology. Previously, he received his M.Sc. at McGill University, advised by Joelle Pineau and David Meger. In the past he has worked at the California Supreme Court, Amazon AWS & Alexa, and Meta Fundamental AI Research.

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  TIME Monday, February 6, 2023 at 10:00 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)

• Mar

  24

  Winter Degrees Conferred

  University Academic Calendar

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  Winter Degrees Conferred

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  TIME Friday, March 24, 2023

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  CONTACT Office of the Registrar    nu-registrar@northwestern.edu EMAIL

  CALENDAR University Academic Calendar

• Mar

  27

  Spring Break Ends

  University Academic Calendar

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  Spring Break Ends

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  TIME Monday, March 27, 2023

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  CONTACT Office of the Registrar    nu-registrar@northwestern.edu EMAIL

  CALENDAR University Academic Calendar

• Mar

  27

  CS Seminar: Designing Formally Correct Intermittent Systems (Milijana Surbatovich)

  Department of Computer Science (CS)

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

  EVENT DETAILS

  Monday / CS Seminar
  March 27th / 12:00 PM
  Mudd 3514

  Title: Designing Formally Correct Intermittent Systems
  Speaker: Milijana Surbatovich

  Abstract:
  "Extreme edge computing" is an emerging computing paradigm targeting application domains like medical wearables, disaster-monitoring tiny satellites, or smart infrastructure. This paradigm brings sophisticated sensing and data processing into an embedded device's deployment environment, enabling computing in environments that are too harsh, inaccessible, or dense to support frequent communication with a central server. Batteryless, energy harvesting devices (EHDs) are key to enabling extreme edge computing; instead of using batteries, which may be too costly or even impossible to replace, they can operate solely off energy collected from their environment. However, harvested energy is typically too weak to power a device continuously, causing frequent, arbitrary power failures that break traditional software and make correct programming difficult. Given the high assurance requirements of the envisioned application domains, EHDs must execute software without bugs that could render the device inoperable or leak sensitive information. While researchers have developed intermittent systems to support programming EHDs, they rely on informal, undefined correctness notions that preclude proving such necessary correctness and security properties. My research lays the foundation for designing formally correct intermittent systems that provide correctness guarantees. In this talk, I show how existing correctness notions are insufficient, leading to unaddressed bugs. I then present the first formal model of intermittent execution, along with correctness definitions for important memory consistency and timing properties.

  I use these definitions to design and implement both the language abstractions that programmers can use to specify their desired properties and the enforcement mechanisms that uphold them. Finally, I discuss my future research directions in intermittent system security and leveraging formal methods for full-stack correctness reasoning.

  Biography:
  Milijana Surbatovich is a PhD Candidate in the Electrical and Computer Engineering Department at Carnegie Mellon University, co-advised by Professors Brandon Lucia and Limin Jia. Her research interests are in applied formal methods, programming languages, and systems for intermittent computing and non-traditional computing platforms broadly. She is excited by research problems that require reasoning about correctness and security across the architecture, system, and language stack. She was awarded CMU's CyLab Presidential Fellowship in 2021 and was selected as a 2022 Rising Star in EECS. Previously, she received an MS in ECE from CMU in 2020 and a BS in Computer Science from the University of Rochester in 2017.

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  TIME Monday, March 27, 2023 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)

• Mar

  28

  Spring Classes begin 8 a.m. (Northwestern Monday: Classes scheduled to meet on Mondays meet on this day)

  University Academic Calendar

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  Spring Classes begin 8 a.m. (Northwestern Monday: Classes scheduled to meet on Mondays meet on this day)

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  TIME Tuesday, March 28, 2023

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  CONTACT Office of the Registrar    nu-registrar@northwestern.edu EMAIL

  CALENDAR University Academic Calendar

• Apr

  3

  CS Seminar: AI for Scientists: Accelerating Discovery through Knowledge, Data & Learning (Jennifer J. Sun)

  Department of Computer Science (CS)

  10:00 AM 3514, Mudd Hall ( formerly Seeley G. Mudd Library)

  EVENT DETAILS

  Monday / CS Seminar
  April 3rd / 10:00 AM
  Mudd 3514

  Title: AI for Scientists: Accelerating Discovery through Knowledge, Data & Learning
  Speaker: Jennifer J. Sun

  Abstract:
  With rapidly growing amounts of experimental data, machine learning is increasingly crucial for automating scientific data analysis. However, many real-world workflows demand expert-in-the-loop attention and require models that not only interface with data, but also with experts and domain knowledge. My research develops full stack solutions that enable scientists to scalably extract insights from diverse and messy experimental data with minimal supervision. My approaches learn from both data and expert knowledge, while exploiting the right level of domain knowledge for generalization. In this talk, I will present progress towards developing automated scientist-in-the-loop solutions, including methods that automatically discover meaningful structure from data such as self-supervised keypoints from videos of diverse behaving organisms. I will also present methods that use these interpretable structures to inject domain knowledge into the learning process, such as guiding representation learning using symbolic programs of behavioral features computed from keypoints. I work closely with domain experts, such as behavioral neuroscientists, to integrate these methods in real-world workflows. My aim is to enable AI that collaborates with scientists to accelerate the scientific process.

  Biography:
  Jennifer is a PhD candidate in Computing and Mathematical Sciences at Caltech, advised by Professors Pietro Perona and Yisong Yue. Her research focuses on developing scientist-in-the-loop computational systems that automatically convert experimental data into insight with minimal expert effort. She aims to accelerate scientific discovery and optimize expert attention in real-world workflows, tackling challenges including annotation efficiency, model interpretability and generalization, and semantic structure discovery. Beyond her research work, she has organized multiple workshops to facilitate connections across fields at top AI conferences, such as CVPR, and she has received multiple awards, such as best student paper at CVPR 2021.

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  TIME Monday, April 3, 2023 at 10:00 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

  21

  How ChatGPT and Generative AI Will Change Legal Services

  McCormick School of Engineering and Applied Science

  9:00 AM Levy Mayer Hall

  EVENT DETAILSmore info

  

  Introducing a new joint Executive Education series created by Northwestern Pritzker School of Law and McCormick School of Engineering designed to help law firm leaders, lawyers, and other legal professionals understand and make the most of the computational technologies that are transforming the delivery of legal services.

  Register Now

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  TIME Friday, April 21, 2023 at 9:00 AM - 5:30 PM

  LOCATION Levy Mayer Hall    map it

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  CONTACT Daniel W. Linna Jr.    daniel.linna@law.northwestern.edu EMAIL

  CALENDAR McCormick School of Engineering and Applied Science

• Apr

  28

  Bagel Friday

  Department of Computer Science (CS)

  9:30 AM 3514, Mudd Hall ( formerly Seeley G. Mudd Library)

  EVENT DETAILS

  Come enjoy free bagels and coffee!

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  TIME Friday, April 28, 2023 at 9:30 AM - 10:30 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

  29

  No classes - Memorial Day

  University Academic Calendar

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  No classes - Memorial Day

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  TIME Monday, May 29, 2023

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  CONTACT Office of the Registrar    nu-registrar@northwestern.edu EMAIL

  CALENDAR University Academic Calendar

• Jun

  1

  CS End of Year Ice Cream Social

  Department of Computer Science (CS)

  1:00 PM

  EVENT DETAILS

  Come enjoy free ice cream and celebrate the end of the school year.

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  TIME Thursday, June 1, 2023 at 1:00 PM - 4:00 PM

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

  CALENDAR Department of Computer Science (CS)

• Jun

  3

  Spring classes end

  University Academic Calendar

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  EVENT DETAILS

  Spring classes end

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  TIME Saturday, June 3, 2023

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  CONTACT Office of the Registrar    nu-registrar@northwestern.edu EMAIL

  CALENDAR University Academic Calendar