News & EventsDepartment Events & Announcements
Events
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Nov4
EVENT DETAILS
lessMonday / CS Seminar
November 4th / 12:00 PM
Hybrid / Mudd 3514Speaker
Dr. Kristin Lauter, FAIR Labs North AmericaTalk Title
Cryptography in the "Post-AI" Era: Machine Learning attacks on Post-Quantum CryptographyAbstract
AI is taking off and we could say we are living in “the AI Era”. Progress in AI today is based on mathematics and statistics under the covers of machine learning models. This talk will explain at a high level how these techniques work, and some important applications. In particular, I will explain recent work on AI4Crypto, where we train AI models to attack Post Quantum Cryptography (PQC) schemes based on lattices. Understanding the concrete security of these standardized PQC schemes is important for the future of e-commerce and internet security. So in addition to living in a Post-Quantum era, we can say we are living in a “Post-AI” era.Biography
"Dr. Kristin Lauter is Senior Director of FAIR Labs North America (2022—present), based in Seattle. Her current research areas are AI4Crypto and Private AI. She joined FAIR (Facebook AI Research) in 2021, after 22 years at Microsoft Research (MSR). At MSR she was Partner Research Manager on the senior leadership team of MSR Redmond. Before joining Microsoft in 1999, she was Hildebrandt Assistant Professor of Mathematics at the University of Michigan (1996-1999). She is an Affiliate Professor of Mathematics at the University of Washington (2008—present). She received all her advanced degrees from the University of Chicago, BA (1990), MS (1991), PhD (1996) in Mathematics. She is best known for her work on Elliptic Curve Cryptography, Supersingular Isogeny Graphs in Cryptography, Homomorphic Encryption (SEALcrypto.org), Private AI, and AI4Crypto. She served as President of the Association for Women in Mathematics from 2015-2017 and on the Council of the American Mathematical Society from 2014-2017.
Lauter has been recognized for her mathematical research and leadership with numerous awards: the Selfridge Prize in Computational Number Theory (2008), as an elected Fellow of the American Mathematical Society (2015), Fellow of the Association for Women in Mathematics (2017), Fellow of the Society for Industrial and Applied Mathematics (SIAM) in 2020, and Fellow of the American Association for the Advancement of Science (2020). In 2021, Lauter was elected as an honorary member of the Royal Spanish Mathematical Society (RSME). She was awarded the Pólya Lectureship for the Mathematical Association of America (2018–2020) and the SIAM Block Community Prize Lecturer in 2022. She gave a TED talk on Private AI at Congreso Futuro in 2020 and on AI4Crypto in 2023."
Research/Interest Areas:
AI Privacy and Security, AI for Math, Cryptography, Number Theory---
Zoom: TBA
Panopto:TBA
DEI Minute: TBATIME Monday, November 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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Nov7
EVENT DETAILS
lessLearn 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
lessThis 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
lessTBA
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
lessEnCORE 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
lessMonday / 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
lessTBA
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
lessTBA
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
lessTBA
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
lessTBA
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
lessTBA
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
lessFall 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
lessThe 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