News & EventsDepartment Events & Announcements
Events
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Feb18
EVENT DETAILSmore info
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From generating text and images to understanding problems and making decisions, artificial intelligence has prompted a wave of experimentation at work. Join us for an insightful conversation with Dr. Eric Horvitz, Chief Scientific Officer of Microsoft and Dr. David Autor, Rubinfeld Professor of Economics at MIT, contributing authors to the National Academies Report on Artificial Intelligence and the Future of Work. This timely discussion will delve into the evolving landscape of work, addressing critical issues such as creating new forms of valuable work and augmenting workers to changing workplace dynamics and labor. The public will gain valuable strategies for navigating workforce changes. Researchers will gain critical insights into AI development and work. And policymakers will understand the need for flexible responses. Don’t miss this chance to engage with thought leaders shaping the future of work and gain actionable insight to stay ahead in our rapidly changing world.
TIME Tuesday, February 18, 2025 at 1:00 PM - 2:00 PM
CONTACT Madison Deyo madison.deyo@northwestern.edu EMAIL
CALENDAR Center for Human-Computer Interaction + Design (HCI+D)
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Feb19
EVENT DETAILS
lessWednesday / CS Seminar
February 19th / 12:00 PM
Hybrid / Mudd 3514Speaker
Dan AdlerTalk Title
Developing Responsible AI Monitoring Technologies for Chronic CareAbstract
Data from everyday devices are increasingly being repurposed to monitor symptoms of heterogeneous chronic conditions: conditions where symptoms present diversely across individuals, and the devices used for symptom monitoring vary across a population. While these variations may not greatly affect personal tracking applications, they pose challenges towards use in clinical settings. Specifically, how can we develop technologies that accurately identify patient-specific symptoms, and ensure reliable symptom monitoring? How can these tools support patients and their healthcare providers? In this talk, I will discuss my work designing, developing, and evaluating AI-driven symptom monitoring technologies to address these challenges. I will close by presenting my vision for a more responsible approach to develop these technologies – one that is deeply integrated with the needs of patients, healthcare providers, and other key stakeholders within our health system.Biography
Dan Adler is a PhD Candidate in the College of Computing and Information Science at Cornell University. His research designs, develops, and evaluates novel data-driven technologies and AI models that support healthcare delivery. Dan’s work has been published at top-tier venues in ubiquitous computing (IMWUT), human-computer interaction (CHI, CSCW), and digital health (npj Mental Health Research, BJPsych, JMIR). His research has been highlighted in the national media, cited in government reports, translated into interventions that support patients, and led to patentable systems. He is the recipient of an NSF Graduate Research Fellowship, and was a finalist for the Gaetano Borriello Outstanding Student Award at ACM UbiComp. Dan holds a Bachelor’s in Biomedical Engineering and Applied Mathematics and Statistics from The Johns Hopkins University.Research/Interest Areas
Human-Computer Interaction; Ubiquitous Computing; Responsible AI/ML; Digital Health
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Zoom: https://northwestern.zoom.us/j/94583712653?pwd=bJCsurzyfvg4v4LhWU5SjXEaH7RQSB.1
Panopto: https://northwestern.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=8fb71c59-ec7c-441b-824e-b2820147b70a
Community Connections Topic: Equitable AssessmentsTIME Wednesday, February 19, 2025 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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Feb21
EVENT DETAILS
lessFriday / CS Seminar
February 21st / 12:00 PM
Hybrid / Mudd 3514Speaker
Sadhika Malladi, Princeton UniversityTalk Title
Deep Learning Theory in the Age of Generative AIAbstract
Modern deep learning has achieved remarkable results, but the design of training methodologies largely relies on guess-and-check approaches. Thorough empirical studies of recent massive language models (LMs) is prohibitively expensive, underscoring the need for theoretical insights, but classical ML theory struggles to describe modern training paradigms. I present a novel approach to developing prescriptive theoretical results that can directly translate to improved training methodologies for LMs. My research has yielded actionable improvements in model training across the LM development pipeline — for example, my theory motivates the design of MeZO, a fine-tuning algorithm that reduces memory usage by up to 12x and halves the number of GPU-hours required. Throughout the talk, to underscore the prescriptiveness of my theoretical insights, I will demonstrate the success of these theory-motivated algorithms on novel empirical settings published after the theory.Biography
Sadhika Malladi is a final-year PhD student in Computer Science at Princeton University advised by Sanjeev Arora. Her research advances deep learning theory to capture modern-day training settings, yielding practical training improvements and meaningful insights into model behavior. She has co-organized multiple workshops, including Mathematical and Empirical Understanding of Foundation Models at ICLR 2024 and Mathematics for Modern Machine Learning (M3L) at NeurIPS 2024. She was named a 2025 Siebel Scholar.Research/Interest Areas
machine learning, theoretical machine learning, natural language processing, optimization
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Zoom: https://northwestern.zoom.us/j/93472031147?pwd=EMcOSUapzdfxmWaIUX6EheUDmztCU3.1
Panopto: https://northwestern.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=f8cd1b02-aca0-4bc9-b475-b2820164a63f
Community Connections Topic: Supporting First Generation StudentsTIME Friday, February 21, 2025 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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Feb24
EVENT DETAILS
lessMonday / CS Seminar
February 24th / 12:00 PM
Hybrid / Mudd 3514Speaker
Wenqi JiangTalk Title
Vector-Centric Machine Learning Systems: A Cross-Stack ApproachAbstract
"Despite the recent popularity of large language models (LLMs), the transformer neural network invented eight years ago has remained largely unchanged. It prompts the question of whether machine leanring (ML) systems research is solely about improving hardware and software for tensor operations. In this talk, I will argue that the future of machine learning systems extends far beyond model acceleration. Using the increasingly popular retrieval-augmented generation (RAG) paradigm as an example, I will show that the growing complexity of ML systems demands a deeply collaborative effort spanning data management, systems, computer architecture, and ML.I will present RAGO and Chameleon, two pioneering works in this field. RAGO is the first systematic performance study of retrieval-augmented generation. It uncovers the intricate interactions between vector data systems and models, revealing drastically different performance characteristics across various RAG workloads. To navigate this complex landscape, RAGO introduces a system optimization framework to explore optimal system configurations for arbitrary RAG algorithms. Building on these insights, I will introduce Chameleon, the first heterogeneous accelerator system for RAG. Chameleon combines LLM and retrieval accelerators within a disaggregated architecture. The heterogeneity ensures efficient serving of both LLM inference and retrievals, while the disaggregation enables independent scaling of different system components to accommodate diverse RAG workload requirements. I will conclude the talk by emphasizing the necessity of cross-stack co-design for future ML systems and the abundant of opporutnities ahead of us."
Biography
Wenqi Jiang is a final-year PhD student at ETH Zurich, advised by Gustavo Alonso and Torsten Hoefler. He aims to enable more efficient, next-generation machine learning systems. Rather than focusing on a single layer in the computing stack, Wenqi's research spans the intersections of data management, computer systems, and computer architecture. His work has driven advancements in several areas, including retrieval-augmented generation (RAG), vector search, and recommender systems. These contributions have earned him recognition as one of the ML and Systems Rising Stars, as well as the AMD HACC Outstanding Researcher Award.Research/Interest Areas
Data management, computer systems, and computer architecture.
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Community Connections Topic: TBATIME Monday, February 24, 2025 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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Feb26
EVENT DETAILS
lessWednesday / CS Seminar
February 26th / 12:00 PM
Hybrid / Mudd 3514Speaker
Tianyu GaoTalk Title
Enabling Language Models to Process Information at ScaleAbstract
Language models (LMs) are highly effective at understanding and generating text, holding immense potential as intuitive, personalized interfaces for accessing information. Expanding their ability to gather and synthesize large volumes of information will further unlock transformative applications, ranging from generative search engines to AI literature assistants. In this talk, I will present my research on advancing LMs for information processing at scale. (1) I will present my evaluation framework for LM-based information-seeking systems, emphasizing the importance of providing citations for verifying the model-generated answers. Our evaluation highlights shortcomings in LMs’ abilities to reliably process long-form texts (e.g., dozens of webpages), which I address by developing state-of-the-art long-context LMs that outperform leading industry efforts while using a small fraction of the computational budget. (2) I will then introduce my foundational work on using contrastive learning to produce performant text embeddings, which form the cornerstone of effective and scalable search. (3) In addition to building systems that can process large-scale information, I will discuss my contributions to creating efficient pre-training and adaptation methods for LMs, which enable scalable deployment of LM-powered applications across diverse settings. Finally, I will share my vision for the next generation of autonomous information processing systems and outline the foundational challenges that must be addressed to realize this vision.Biography
Tianyu Gao is a fifth-year PhD student in the Department of Computer Science at Princeton University, advised by Danqi Chen. His research focuses on developing principled methods for training and adapting language models, many of which have been widely adopted across academia and industry. Driven by transformative applications, such as using language models as information-seeking tools, his work also advances robust evaluation and fosters a deeper understanding to guide the future development of language models. He led the first workshop on long-context foundation models at ICML 2024. He won an outstanding paper award at ACL 2022 and received an IBM PhD Fellowship in 2023. Before Princeton, he received his BEng from Tsinghua University in 2020.Research/Interest Areas
Natural language processing, language models
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Panopto: TBA
DEI Minute: tinyurl.com/cspac-dei-minuteTIME Wednesday, February 26, 2025 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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Feb27
EVENT DETAILS
lessJoin us for free bagels and coffee courtesy of the Computer Science Department. Come mix and mingle with fellow CS students and faculty.
TIME Thursday, February 27, 2025 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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Feb28
EVENT DETAILS
lessMonday / CS Seminar
January 13th / 12:00 PM
Hybrid / Mudd 3514Speaker
TBATalk Title
TBAAbstract
TBABiography
TBAResearch/Interest Areas
TBA
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DEI Minute: tinyurl.com/cspac-dei-minuteTIME Friday, February 28, 2025 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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Mar3
EVENT DETAILS
lessMonday / CS Seminar
January 13th / 12:00 PM
Hybrid / Mudd 3514Speaker
TBATalk Title
TBAAbstract
TBABiography
TBAResearch/Interest Areas
TBA
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Panopto: TBA
DEI Minute: tinyurl.com/cspac-dei-minuteTIME Monday, March 3, 2025 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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Mar5
EVENT DETAILS
lessMonday / CS Seminar
January 13th / 12:00 PM
Hybrid / Mudd 3514Speaker
TBATalk Title
TBAAbstract
TBABiography
TBAResearch/Interest Areas
TBA
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Panopto: TBA
DEI Minute: tinyurl.com/cspac-dei-minuteTIME Wednesday, March 5, 2025 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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Mar7
EVENT DETAILS
lessMonday / CS Seminar
January 13th / 12:00 PM
Hybrid / Mudd 3514Speaker
TBATalk Title
TBAAbstract
TBABiography
TBAResearch/Interest Areas
TBA
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Zoom: TBA
Panopto: TBA
DEI Minute: tinyurl.com/cspac-dei-minuteTIME Friday, March 7, 2025 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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Mar10
EVENT DETAILS
lessMonday / CS Seminar
January 13th / 12:00 PM
Hybrid / Mudd 3514Speaker
TBATalk Title
TBAAbstract
TBABiography
TBAResearch/Interest Areas
TBA
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Panopto: TBA
DEI Minute: tinyurl.com/cspac-dei-minuteTIME Monday, March 10, 2025 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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Mar12
EVENT DETAILS
lessMonday / CS Seminar
January 13th / 12:00 PM
Hybrid / Mudd 3514Speaker
TBATalk Title
TBAAbstract
TBABiography
TBAResearch/Interest Areas
TBA
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Panopto: TBA
DEI Minute: tinyurl.com/cspac-dei-minuteTIME Wednesday, March 12, 2025 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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Mar14
EVENT DETAILS
lessMonday / CS Seminar
January 13th / 12:00 PM
Hybrid / Mudd 3514Speaker
TBATalk Title
TBAAbstract
TBABiography
TBAResearch/Interest Areas
TBA
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Panopto: TBA
DEI Minute: tinyurl.com/cspac-dei-minuteTIME Friday, March 14, 2025 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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Mar17
EVENT DETAILS
lessWinter exams begin
TIME Monday, March 17, 2025
CONTACT Office of the Registrar nu-registrar@northwestern.edu EMAIL
CALENDAR University Academic Calendar
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Mar22
EVENT DETAILS
lessSpring Break Begins
TIME Saturday, March 22, 2025
CONTACT Office of the Registrar nu-registrar@northwestern.edu EMAIL
CALENDAR University Academic Calendar
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Mar31
EVENT DETAILS
lessSpring Break Ends
TIME Monday, March 31, 2025
CONTACT Office of the Registrar nu-registrar@northwestern.edu EMAIL
CALENDAR University Academic Calendar