News & EventsDepartment Events & Announcements
Events
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Nov6
EVENT DETAILS
Wednesday / CS Seminar
November 6th / 12:00 PM
Hybrid / Mudd 3514Speaker
Nate Foster, Cornell UniversityTalk Title
The Network is the Computer: A Programming Language PerspectiveAbstract
Historically, the fields of programming languages and networking have operated in relative isolation: applications run on end hosts and communicate with each other using standard network protocols. However, the landscape has changed significantly in the past decade, driven by the needs of large-scale systems and the emergence of programmable network hardware. Today, it is possible to design and implement custom network protocols and even to relocate application-level functionality into the network fabric. This talk will discuss the pivotal role that programming languages are playing in modern networks, highlighting how experiences designing domain-specific abstractions and reasoning tools for networks can provide fresh insights for the field of programming languages, too.Biography
Nate Foster is a Professor of Computer Science at Cornell University and a Visiting Researcher at Jane Street. The goal of his research is to develop languages and tools that make it easy for programmers to build secure and reliable systems. His current work focuses on the design and implementation of languages and tools for network programming. In the past he has also worked on bidirectional languages (also known as “lenses”), database query languages, data provenance, type systems, mechanized proof, and formal semantics. He received a PhD in Computer and Information Science from the University of Pennsylvania. His awards include a Sloan Research Fellowship, an NSF CAREER Award, the SIGPLAN Robin Milner Award, SIGCOMM Rising Star Award, and Most Influential Paper Awards at ICFP and POPL.Research/Interest Areas: Programming Languages and Networking
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Zoom: https://northwestern.zoom.us/j/99112784408
Panopto: https://northwestern.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=210829aa-904b-48b3-ac44-b21a01363ac1
DEI Minute: TBATIME Wednesday, November 6, 2024 at 12:00 PM - 1:00 PM
LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Nov7
EVENT DETAILS
Learn how traditional 3D graphics engineering has converged with Generative AI and Robotics using OpenUSD and NVIDIA Omniverse.
I’ll discuss my career path from NU, to grad school, to Oscar nominated and Emmy winning Visual Effects, to my current role at NVIDIA.
This speaker will present via Zoom, but an in-person session will be held for the presentation.
TIME Thursday, November 7, 2024 at 5:00 PM - 6:00 PM
LOCATION 3501, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Bella Barrios marbella.barrios@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Nov8
EVENT DETAILSmore info
This dissertation proposes methods for verifying that machine learning models are trustworthy, while keeping sensitive information (such as training data and model parameters) confidential from the verifier via cryptographic techniques. Several previous methods from academic literature are capable of producing models that are trustworthy (i.e. satisfying mathematical metrics of unbiasedness, reliability, privacy, etc.), but in practice violations of user trust from service providers are common. I argue that this disjuncture occurs in part because service providers are materially disincentivized from trustworthy behavior. This problem is compounded by the fact that most machine learning services are provided in a “black-box” model in order to protect intellectual property, which makes it difficult to assess model trustworthiness and thus hold service providers accountable for breaches in trust.
Here we take up the task of ensuring the use of trustworthy models in practice. We do so by designing zero-knowledge proof and secure multiparty computation protocols which verify trustworthiness via controlled releases of information about machine learning models to external parties, leaving the black box intact. Both methods do so by computing a specified set of operations on hidden data with provable correctness and confidentiality even in the presence of adversarial parties. We devote much attention to tailoring our protocols for concrete efficiency, as the computational
overhead of the cryptography we employ would otherwise impose a substantial practical barrier to the use of our methods. The main components of the work are as follows:
1. We design a zero-knowledge proof protocol that verifies the fairness of a decision tree model relative to a set of training data. We design our own “crypto-friendly” decision tree training algorithm, whose assumptions enable highly efficient zero-knowledge proofs of fairness.
2. We expand the scope of zero-knowledge proofs of fairness dramatically by designing a protocol which is modular to model type and training algorithm, and has improved security guarantees. We utilize an efficient probabilistic auditing protocol which enables practical scalability even for neural networks with tens of millions of parameters.
3. We provide a secure multiparty computation protocol that enables many parties to collaboratively train a machine learning model with verified confidentiality and robustness to unhelpful or poisonous training data. We formalize and exploit properties arising from the intersection of Byzantine robust aggregation algorithms and secure computation to make our methods concretely efficient.TIME Friday, November 8, 2024 at 11:00 AM - 1:00 PM
LOCATION 3001, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Olive Franzese olive.franzese@u.northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Nov11
EVENT DETAILS
TBA
TIME Monday, November 11, 2024 at 12:00 PM - 1:00 PM
LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Nov18
EVENT DETAILSmore info
EnCORE and IDEAL TRIPODS Institutes Collaboration website here
Monday, November 18 and Tuesday, November 19, 2024
The NSF TRIPODS Institutes—The Institute for Emerging CORE Methods for Data Science (EnCORE) at UCSD and The Institute for Data, Econometrics, Algorithms, and Learning (IDEAL) at Northwestern University—are co-hosting a workshop titled "Foundations of Fairness and Accountability." The event will take place from November 18-19, 2024 in a hybrid format at the Department of Computer Science at Northwestern University, Evanston, Illinois. We plan to follow up with a second workshop at early Spring at the EnCORE institute at the University of California San Diego.
The workshop will feature a blend of talks and interactive discussions, focusing on key topics related to fairness and accountability. The main areas of exploration include:
1. Fairness in Resource Allocation
2. Fairness in Clustering & Ranking
3. Fairness in Prediction
4. Socio-Technical Aspects of Fairness & Accountability
5. Accountability in Experiment Design, with an emphasis on Replicability
6. Applications of these concepts across fields like Law, AI, and Biology.TIME Monday, November 18, 2024 at 9:00 AM - 4:30 PM
LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Indira Munoz indira.munoz@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Nov18
EVENT DETAILS
Monday / CS Seminar
November 18th / 12:00 PM
Hybrid / Mudd 3514Speaker
Kyros Kutulakos, University of TorontoTalk Title
The Ultimate Video CameraAbstract
Over the past decade, advances in image sensor technologies have transformed the 2D and 3D imaging capabilities of our smartphones, cars, robots, drones, and scientific instruments. As these technologies continue to evolve, what new capabilities might they unlock? I will discuss one possible point of convergence---the ultimate video camera---which is enabled by emerging single-photon image sensors and photon-processing algorithms. We will explore the extreme imaging capabilities of this camera within the broader historical context of high-speed and low-light imaging systems, highlighting its potential to capture the physical world in entirely new ways.Biography
Kyros is a Professor of Computer Science at the University of Toronto and an expert in computational imaging and computer vision. His research over the past decade has focused on combining programmable sensors, light sources, optics and algorithms to create cameras with unique capabilities---from seeing through scatter and looking around corners to capturing surfaces with complex material properties robustly in 3D. He is currently leading efforts to harness the full potential of technologies such as single-photon cameras and programmable-pixel image sensors, for applications in extreme computer vision and scientific imaging. Kyros is the recipient of an Alfred P. Sloan Fellowship, an NSF CAREER Award, and eight paper prizes at the computer vision field's top conferences, including the best paper award at ICCV 2023 and CVPR 2019.Research/Interest Areas: Computer vision, computational imaging
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Zoom: TBA
Panopto: TBA
DEI Minute: TBATIME Monday, November 18, 2024 at 12:00 PM - 1:00 PM
LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Nov20
EVENT DETAILS
TBA
TIME Wednesday, November 20, 2024 at 12:00 PM - 1:00 PM
LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Nov21
EVENT DETAILS
TBA
TIME Thursday, November 21, 2024 at 9:00 AM - 11:00 AM
LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Nov25
EVENT DETAILS
TBA
TIME Monday, November 25, 2024 at 12:00 PM - 1:00 PM
LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Nov27
EVENT DETAILS
TBA
TIME Wednesday, November 27, 2024 at 12:00 PM - 1:00 PM
LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Dec4
EVENT DETAILS
TBA
TIME Wednesday, December 4, 2024 at 12:00 PM - 1:00 PM
LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Dec7
EVENT DETAILS
Fall classes end
TIME Saturday, December 7, 2024
CONTACT Office of the Registrar nu-registrar@northwestern.edu EMAIL
CALENDAR University Academic Calendar
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Dec14
EVENT DETAILS
The ceremony will take place on Saturday, December 14 in Pick-Staiger Concert Hall, 50 Arts Circle Drive.
*No tickets required
TIME Saturday, December 14, 2024 at 4:00 PM - 6:00 PM
LOCATION Pick-Staiger Concert Hall map it
CONTACT Andi Joppie andi.joppie@northwestern.edu EMAIL
CALENDAR McCormick School of Engineering and Applied Science