Inside Our ProgramProgram Events
Events
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Aug12
EVENT DETAILS
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Please join us in the Electrical and Computer Engineering Department at the Technological Institute for an hour-long seminar with Professor Mor Harchol-Balter, PhD, from Carnegie Mellon University.
Abstract: Scheduling is the primary tool we have for improving system performance without purchasing additional resources. By simply changing the order in which we run jobs, we can dramatically improve response time (both mean response time and the tail of response time). Scheduling is particularly effective in the case of heavy-tailed job size distributions, which are omnipresent and can result in very high response times. In this talk we focus on the heavy-tailed job size setting.
We will start by reviewing optimal scheduling for the single-server queue (the M/G/1), both for the mean and asymptotic tail of response time. This is well understood.
We then turn to multi-server systems (the M/G/n), where almost nothing is understood on optimal scheduling. We present our new results on the first scheduling algorithms for the M/G/n which are asymptotically strongly tail optimal.
We finish by discussing newer job models, like the multi-server job model, which is representative of today’s datacenter jobs. Here we present some recent algorithms for optimal scheduling under heavy traffic.
Throughout, our emphasis will be on intuition and lessons learned.
Bio: Mor Harchol-Balter is the Bruce J. Nelson Professor of Computer Science at Carnegie Mellon. She received her Ph.D. from U.C. Berkeley in 1996, under the direction of Manuel Blum. She is the SIG Chair for ACM SIGMETRICS (a 4-year elected position), having served as General Chair in 2013 and PC Chair in 2007. She is also a Fellow of both ACM and IEEE and has received several teaching awards, including the Herbert A. Simon Award and Spira Teaching Award. Mor's work focuses on designing new resource allocation policies, including load balancing policies, power management policies, and scheduling policies. Mor is heavily involved in the SIGMETRICS / PERFORMANCE / INFORMS research community where her papers have received many awards (ValueTools 24, INFORMS George Nicholson Prize 22, SIGMETRICS 21, SIGMETRICS 19, PERFORMANCE 18, INFORMS APS 18, EUROSYS 16, MASCOTS 16, MICRO 10, SIGMETRICS 03, ITC 03, SIGMETRICS 96). She is the author of two popular textbooks, both published by Cambridge University Press: Performance Analysis and Design of Computer Systems (2013), which bridges queueing theory and computer science, and Introduction to Probability for Computing (2024).
TIME Wednesday, August 12, 2026 at 2:00 PM - 3:00 PM
LOCATION L440, Technological Institute map it
CONTACT Lee Onysko lee.onysko@northwestern.edu EMAIL
CALENDAR Department of Electrical and Computer Engineering (ECE)
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Aug7
EVENT DETAILS
lessAccurately recording what, when, and how much people eat is essential to nutrition research and health interventions. Yet food diaries are burdensome, and no single wearable sensor answers all three questions well. Wrist and thermal sensors can operate continuously and privately but reveal little about food identity or portion size. Cameras provide richer context, but continuous capture and inference increase energy and privacy costs.
This dissertation investigates how a wearable dietary-monitoring system can rely on low-cost sensors most of the time and invoke richer visual models only when useful. I develop a battery-efficient multimodal machine-learning framework that treats dietary assessment as connected tasks rather than one monolithic prediction. The pipeline identifies hand-to-mouth activity from wrist, upward-facing thermal, and camera-supported evidence. A compact thermal trigger determines when to request forward-facing images for eating and drinking recognition, food classification, and caloric-intake estimation. Neural architecture search explores models that balance predictive quality, computation, size, and latency.
The dissertation combines lessons from prior wearable-sensing studies with module-specific methods and evaluations. Low-power candidate discovery can reduce reliance on continuous image processing; triggering separates always-on sensing from higher-cost visual analysis; and task-specific architecture search examines models suited to wearable constraints. Together, these contributions establish a practical design for conditional dietary monitoring. The broader goal is passive dietary assessment that is more accurate and less burdensome while respecting battery and privacy constraints and supporting future on-device and free-living evaluation.TIME Friday, August 7, 2026 at 2:00 PM - 4:00 PM
LOCATION Mudd 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Jensen Smith jensen.smith@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Aug20
EVENT DETAILS
lessThe component-by-component migration of a program from untyped to typed can trigger unintended performance degradations. When such a degradation occurs, typing well-chosen components can lessen the cost of type enforcement, while typing poorly chosen components can exacerbate it. In this talk, I examine whether off-the-shelf profiling tools deliver information that helps programmers navigate these migration choices effectively in Typed Racket.
TIME Thursday, August 20, 2026 at 1:00 PM - 4:00 PM
LOCATION Mudd 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Jensen Smith jensen.smith@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Sep24
EVENT DETAILS
lesstba
TIME Thursday, September 24, 2026 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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Sep28
EVENT DETAILS
lessMonday / CS Seminar
September 28 / 12:00 PM
Hybrid / Mudd 3514Speaker
TBATalk Title
TBAAbstract
TBABiography
TBA---
Zoom Link
Panopto LinkTIME Monday, September 28, 2026 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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Oct5
EVENT DETAILS
lessMonday / CS Seminar
October 5 / 12:00 PM
Hybrid / Mudd 3514Speaker
Brian Suchy, Software Engineer Google DeepMindTalk Title
Formal Relational Equivalence for SQL, GenAI, and BeyondAbstract
Verifying that complex query rewrites from database optimizers or AI-driven generators preserve exact bag semantics under three-valued logic is an NP-hard challenge. To address this, we present an MLIR-native compiler framework that formally reasons about relational algebra. By decoupling query semantics from specific execution engines and lowering queries into a unified Relational Algebra Intermediate Representation, our language-agnostic methodology definitively proves semantic equivalence across all possible database states.The core of the presentation will deep-dive into our multi-tiered proving architecture, which synthesizes several advanced academic methodologies. First, we utilize E-Graphs and Equality Saturation to rapidly explore the equivalence space and detect structural congruence between query abstract syntax trees using fast, algebraic rewrite rules. Second, we employ Semiring Arithmetic, treating relational algebra as expressions over K-relations to leverage algebraic simplification and canonical forms under semiring laws. Finally, we implement a First-Order Logic and SMT translation path, lowering Relational Algebra into Relational Calculus and then into First-Order Logic to evaluate constraints and domain-specific axioms using parallel solvers like Z3 and CVC5, which either formally proves equivalence or synthesizes concrete counter-examples.
Finally, we will discuss the practical implications of combining these formal mathematical methods with modern compiler design. Attendees will leave with a comprehensive understanding of how bridging database theory, equality saturation, and SMT solving can create robust solutions for verifying query optimizers, enforcing semantic correctness, and validating automated SQL generation at scale.
Biography
Brian Suchy is a Software Engineer within Google DeepMind.
In his time at Google he has worked on F1 Query (Google's internal SQL query engine), hardware development, and (of course) AI.
Prior to joining Google, Brian received his PhD student at Northwestern University, advised by Peter Dinda, with a focus on hardware/software codesign and memory management.Research Interests: Artificial Intelligence, Query Processing and Formal Logic
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Zoom Link
Panopto LinkTIME Monday, October 5, 2026 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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Oct29
EVENT DETAILS
lesstba
TIME Thursday, October 29, 2026 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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Nov19
EVENT DETAILS
lesstba
TIME Thursday, November 19, 2026 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)
