Events
Past Event
Python Fundamentals Bootcamp (In-Person)
Northwestern IT Research Computing and Data Services
9:30 AM
//
TBD, Wieboldt Hall North Entrance
Details
This four-day bootcamp provides an engaging, comprehensive, hands-on introduction to the Python programming language. Python is an extremely popular, general-purpose, versatile coding language with a shallow learning curve, meaning you can do a lot with the tools you’ll learn in this four-day workshop. This in-person workshop will not be recorded.
Prerequisites: You will need to bring a laptop to participate. If you're already proficient in another coding language and you're looking for a beginner's introduction to Python because you want to be able to read and run Python code written by others or utilize Python packages for machine learning, web scraping, or text analysis, you should attend at least the first two-and-a-half or three days of the bootcamp. If you're looking to become a proficient Python coder, you should attend all four days of the bootcamp. The instructor will not be able to help you catch up if you miss materials.
Registration Required. Register only once for all four days of this bootcamp.
Time
Tuesday, September 17, 2024 at 9:30 AM - 3:30 PM
Location
TBD, Wieboldt Hall North Entrance Map
Contact
Calendar
Northwestern IT Research Computing and Data Services
CS Seminar: Understanding Quantum Systems via the Algorithmic Lens (Ainesh Bakshi)
Department of Computer Science (CS)
12:00 PM
//
3514, Mudd Hall ( formerly Seeley G. Mudd Library)
Details
Monday / CS Seminar
February 17th / 12:00 PM
Hybrid / Mudd 3514
Speaker
Ainesh Bakshi
Talk Title
Understanding Quantum Systems via the Algorithmic Lens
Abstract
Quantum mechanics is one of our most profound and successful theoretical frameworks for understanding the physical world. It continues to drive remarkable technological and theoretical breakthroughs, spanning computing, coding theory, cryptography, material science, and chemistry. In this talk, I will describe how the algorithmic lens has been pivotal in rigorously analyzing such quantum systems and revealed deeper structural properties that were previously inaccessible through traditional approaches.
Biography
Ainesh Bakshi is a Postdoctoral Fellow jointly appointed in the Mathematics and Computer Science departments at MIT. Prior to that, he obtained his PhD in Computer Science at CMU. He is broadly interested in theoretical computer science and quantum information. His main research thread revolves around using the algorithmic toolkit, consisting of iterative methods and convex hierarchies, to understand large quantum systems. These results have gained significant attention recently, including two Quanta articles, two QIP Invited Plenaries, a QIP Best Student Paper, and being featured in Quanta Magazine’s “Biggest Breakthroughs in Computer Science 2024.” He is also interested in extending this algorithmic toolkit and applying it to problems arising in high-dimensional statistics, privacy, metric embeddings, and numerical linear algebra.
Research/Interest Areas
Theoretical Computer Science, Quantum Information
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Zoom: TBA
Panopto: TBA
Community Connections Topic: Algorithmic Justice League / Dr. Joy Buolamwini
Time
Monday, February 17, 2025 at 12:00 PM - 1:00 PM
Location
3514, Mudd Hall ( formerly Seeley G. Mudd Library) Map
Contact
Calendar
Department of Computer Science (CS)
Generative AI for Language Instruction: Hands-on with Copilot
Media and Design Studio
3:30 PM
//
2530, Kresge Hall
Details

The Media and Design Studio and Language Resource Center are pleased to offer a hands-on workshop on the use of Microsoft Copilot. This workshop expands on examples presented in the fall quarter seminar series by allowing participants to directly interact with various recommended generative artificial intelligence ("Gen AI") tools.
Participants will learn how to use AI to develop lesson plans and materials and to create and shape various forms of multimedia for teaching use.
Time
Monday, February 17, 2025 at 3:30 PM - 4:30 PM
Location
2530, Kresge Hall Map
Contact
Calendar
Media and Design Studio
Smarter Decisions for a Better World: Insights from the Executive Director of INFORMS
Department of Industrial Engineering and Management Sciences (IEMS)
11:00 AM
//
L440, Technological Institute
Details
Abstract:
Professional associations serve as catalysts for innovation, interdisciplinary collaboration, and professional growth. INFORMS, with its diverse scope spanning operations research, management science, analytics, AI, applied mathematics, and beyond, plays a vital role in advancing these fields and shaping real-world decision-making.
In this talk, Elena Gerstmann, Executive Director of INFORMS, will explore the organization’s impact—highlighting key initiatives, upcoming plans, and the ways INFORMS is driving progress across industries. She will also engage the Northwestern community in an interactive discussion, gathering insights on how we can collectively advance smarter decisions for a better world.
Bio:
Elena Gerstmann, PhD, FASAE, CAE (she/her), is the Executive Director of INFORMS, the leading organization for advancing the science and technology of decision-making to save lives, save money, and solve complex problems.
Before joining INFORMS, Elena was a Principal at Avenue M Group and previously served on the executive teams at the American Society of Mechanical Engineers (ASME) and the Institute of Electrical and Electronics Engineers (IEEE).
Elena holds a PhD in social psychology from Rutgers University. She currently serves on the Board of Directors for the Council of Engineering and Scientific Society Executives (CESSE) and is a past board member and Fellow of the American Society of Association Executives (ASAE).
Beyond her professional work, Elena and her wife are the proud parents of two young adults, one happy dog, and one ornery cat. They are also co-founders of SocialOffset, a nonprofit that helps travelers align their spending with their values.
Time
Tuesday, February 18, 2025 at 11:00 AM - 12:00 PM
Location
L440, Technological Institute Map
Contact
Calendar
Department of Industrial Engineering and Management Sciences (IEMS)
Thought Leader Dialogue: AI and the Future of Work
Center for Human-Computer Interaction + Design (HCI+D)
1:00 PM
Details

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
Calendar
Center for Human-Computer Interaction + Design (HCI+D)
School of Communication CommConnections
School of Communication
3:30 PM
//
201, Wirtz Center for the Performing Arts
Details
Teaching, Playing, & Performing with AI
With an introduction from Dean E. Patrick Johnson and Associate Dean for Research Molly Losh and a moderated discussion led by Eliza Bent.
Presenters
Melissa Blanco Borelli. Associate Professor in Theatre and Performance Studies
Thomas DeFrantz, Professor in Theatre and Performance Studies
Duri Long, Assistant Professor in Communication Studies
CommConnections: The SoC symposium series established to cross disciplines and create partnerships within the school
Reception to follow
Time
Tuesday, February 18, 2025 at 3:30 PM - 5:00 PM
Location
201, Wirtz Center for the Performing Arts Map
Contact
Calendar
School of Communication
CS Seminar: Developing Responsible AI Monitoring Technologies for Chronic Care (Dan Adler)
Department of Computer Science (CS)
12:00 PM
//
3514, Mudd Hall ( formerly Seeley G. Mudd Library)
Details
Wednesday / CS Seminar
February 19th / 12:00 PM
Hybrid / Mudd 3514
Speaker
Dan Adler
Talk Title
Developing Responsible AI Monitoring Technologies for Chronic Care
Abstract
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 Assessments
Time
Wednesday, February 19, 2025 at 12:00 PM - 1:00 PM
Location
3514, Mudd Hall ( formerly Seeley G. Mudd Library) Map
Contact
Calendar
Department of Computer Science (CS)
Learning Lab: Creating Rubrics x AI for Student Success
Searle Center Events
12:00 PM
Details

Part of the 2025 University Practicum on Supporting Student Success, participants may attend any and all practicum events.
Time
Thursday, February 20, 2025 at 12:00 PM - 1:00 PM
Contact
Calendar
Searle Center Events
CS Seminar: Deep Learning Theory in the Age of Generative AI (Sadhika Malladi)
Department of Computer Science (CS)
12:00 PM
//
3514, Mudd Hall ( formerly Seeley G. Mudd Library)
Details
Friday / CS Seminar
February 21st / 12:00 PM
Hybrid / Mudd 3514
Speaker
Sadhika Malladi, Princeton University
Talk Title
Deep Learning Theory in the Age of Generative AI
Abstract
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 Students
Time
Friday, February 21, 2025 at 12:00 PM - 1:00 PM
Location
3514, Mudd Hall ( formerly Seeley G. Mudd Library) Map
Contact
Calendar
Department of Computer Science (CS)
CS Seminar: Vector-Centric Machine Learning Systems: A Cross-Stack Approach (Wenqi Jiang)
Department of Computer Science (CS)
12:00 PM
//
3514, Mudd Hall ( formerly Seeley G. Mudd Library)
Details
Monday / CS Seminar
February 24th / 12:00 PM
Hybrid / Mudd 3514
Speaker
Wenqi Jiang
Talk Title
Vector-Centric Machine Learning Systems: A Cross-Stack Approach
Abstract
"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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Zoom: TBA
Panopto: TBA
Community Connections Topic: TBA
Time
Monday, February 24, 2025 at 12:00 PM - 1:00 PM
Location
3514, Mudd Hall ( formerly Seeley G. Mudd Library) Map
Contact
Calendar
Department of Computer Science (CS)
Appl Math: James Stone on "Astrophysical Fluid Dynamics at Exascale"
McCormick-Engineering Sciences and Applied Mathematics (ESAM)
11:15 AM
//
M416, Technological Institute
Details
Title: Astrophysical Fluid Dynamics at Exascale
Speaker: James Stone, Institute for Advanced Study
Abstract: Most of the visible matter in the Universe is a plasma -- that is
a dilute gas of electrons, ions, and neutral particles -- interacting
with both magnetic and radiation fields. Studying the structure
and dynamics of astrophysical systems, from stars and planets, to
galaxies and the large-scale structure of the Universe itself,
usually requires numerical methods to solve the coupled equations
of compressible radiation magnetohydrodynamics (MHD). Robust
numerical algorithms for modeling astrophysical fluids, including
new methods for calculating radiation transport in relativistic
flows, will be discussed. Efficient implementation of these methods
on modern high-performance computing systems is crucial, and an
approach based on the Kokkos programming model that enables performance
portability will be described. Performance on a variety of
architectures of a new adaptive mesh refinement (AMR) astrophysical
MHD code will be given, including scaling on up to 65536 GPUs on
the OLCF Frontier exascale computer. Finally, a case study will
be presented that demonstrates some of the many new insights that
have come from applying computational methods to one particular problem:
how plasma accretes onto the black holes in the centers of galaxies.
Zoom: https://northwestern.zoom.us/j/95581369835
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Time
Tuesday, February 25, 2025 at 11:15 AM - 12:15 PM
Location
M416, Technological Institute Map
Contact
Calendar
McCormick-Engineering Sciences and Applied Mathematics (ESAM)
CS Seminar: Enabling Language Models to Process Information at Scale (Tianyu Gao)
Department of Computer Science (CS)
12:00 PM
//
3514, Mudd Hall ( formerly Seeley G. Mudd Library)
Details
Wednesday / CS Seminar
February 26th / 12:00 PM
Hybrid / Mudd 3514
Speaker
Tianyu Gao
Talk Title
Enabling Language Models to Process Information at Scale
Abstract
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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Zoom: TBA
Panopto: TBA
DEI Minute: tinyurl.com/cspac-dei-minute
Time
Wednesday, February 26, 2025 at 12:00 PM - 1:00 PM
Location
3514, Mudd Hall ( formerly Seeley G. Mudd Library) Map
Contact
Calendar
Department of Computer Science (CS)
WED@NICO SEMINAR: Morgan Frank, University of Pittsburgh "AI, Complexity, and the Future of Work"
Northwestern Institute on Complex Systems (NICO)
12:00 PM
//
Lower Level, Chambers Hall
Details

Speaker:
Morgan Frank, Assistant Professor, Department of Informatics and Networked Systems, University of Pittsburgh
Title:
AI, Complexity, and the Future of Work
Abstract:
Artificial Intelligence has evolved and now challenges our understanding of skills, careers, and the future of work. Using a variety of data on employment, occupations’ skill requirements, millions of resumes, and unemployment data from US states’ unemployment insurance offices, this talk will explore how workers’ skills shape their careers and how automation estimates fit into a framework for career adaptability and the economic resilience of labor markets. Work from this talk comes from a variety of publications in PNAS, Nature Communications, and Science Advances.
Speaker Bio:
Morgan Frank is an Assistant Professor at the School of Computing and Information at the University of Pittsburgh. Morgan is interested in the complexity of AI, the future of work, and the socio-economic consequences of technological change. While many studies focus on phenotypic labor trends, Morgan’s recent research examines how genotypic skill-level processes around AI impact individuals and society. Combining labor research with investigations into the nature of AI research and the social or societal implications of AI adoption, Morgan hopes to inform our understanding of AI’s impact. Morgan has a PhD from MIT’s Media Lab, was a postdoc at MIT IDSS and the IDE, and has a master’s degree in applied mathematics from the University of Vermont where he was a member of the Computational Story Lab.
Location:
In person: Chambers Hall, 600 Foster Street, Lower Level
Remote option: https://northwestern.zoom.us/j/91407653122
Passcode: NICO25
About the Speaker Series:
Wednesdays@NICO is a vibrant weekly seminar series focusing broadly on the topics of complex systems, data science and network science. It brings together attendees ranging from graduate students to senior faculty who span all of the schools across Northwestern, from applied math to sociology to biology and every discipline in-between. Please visit: https://bit.ly/WedatNICO for information on future speakers.
Time
Wednesday, February 26, 2025 at 12:00 PM - 1:00 PM
Location
Lower Level, Chambers Hall Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
Rochelle Rives of CUNY will present her new book "The new Physiognomy. Face, Form, and Modern Expression
Department of Spanish and Portuguese
12:30 PM
//
1515, Kresge Hall
Details
Advances in facial recognition, artificial intelligence, and other technologies provoke urgent ethical questions about facial expressivity and how we interpret it. In 'The New Physiognomy,' Rochelle Rives roots contemporary facial dilemmas in a more expansive timeline of modernist engagements with the face to argue that facial ambiguity is essential to how we value other people. Beginning with nineteenth-century caricatures of Oscar Wilde's face, Rives reasons that modernist modes of reading the face perceived it as a manifestation of both biologically determined traits and scripted forms of personality. Considering faces such as sculptures of great poets, portraits of facially wounded World War I soldiers, W. H. Auden's aging face, and Cindy Sherman's recent photographic self-portraits, Rives reframes how to read modernist works by Theodore Dreiser, Edith Wharton, Jean Rhys, Joseph Conrad, Mina Loy, Henry Tonks, and Henri Gaudier-Brzeska. (Johns Hopkins UP)
Lunch will be provided
*Co-sponsors: Comp Lit studies, English, Global Avant-Garde and Modernist Studies (GAMS)
Time
Thursday, February 27, 2025 at 12:30 PM - 2:00 PM
Location
1515, Kresge Hall Map
Contact
Calendar
Department of Spanish and Portuguese
Generative AI for Language Instruction: Hands-on with Copilot
Media and Design Studio
3:00 PM
//
2530, Kresge Hall
Details

The Media and Design Studio and Language Resource Center are pleased to offer a hands-on workshop on the use of Microsoft Copilot. This workshop expands on examples presented in the fall quarter seminar series by allowing participants to directly interact with various recommended generative artificial intelligence ("Gen AI") tools.
Participants will learn how to use AI to develop lesson plans and materials and to create and shape various forms of multimedia for teaching use.
Time
Thursday, February 27, 2025 at 3:00 PM - 4:00 PM
Location
2530, Kresge Hall Map
Contact
Calendar
Media and Design Studio
CS Seminar
Department of Computer Science (CS)
12:00 PM
//
3514, Mudd Hall ( formerly Seeley G. Mudd Library)
Details
Monday / CS Seminar
January 13th / 12:00 PM
Hybrid / Mudd 3514
Speaker
TBA
Talk Title
TBA
Abstract
TBA
Biography
TBA
Research/Interest Areas
TBA
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Zoom: TBA
Panopto: TBA
DEI Minute: tinyurl.com/cspac-dei-minute
Time
Friday, February 28, 2025 at 12:00 PM - 1:00 PM
Location
3514, Mudd Hall ( formerly Seeley G. Mudd Library) Map
Contact
Calendar
Department of Computer Science (CS)
CS Seminar
Department of Computer Science (CS)
12:00 PM
//
3514, Mudd Hall ( formerly Seeley G. Mudd Library)
Details
Monday / CS Seminar
January 13th / 12:00 PM
Hybrid / Mudd 3514
Speaker
TBA
Talk Title
TBA
Abstract
TBA
Biography
TBA
Research/Interest Areas
TBA
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Zoom: TBA
Panopto: TBA
DEI Minute: tinyurl.com/cspac-dei-minute
Time
Monday, March 3, 2025 at 12:00 PM - 1:00 PM
Location
3514, Mudd Hall ( formerly Seeley G. Mudd Library) Map
Contact
Calendar
Department of Computer Science (CS)
CS Seminar
Department of Computer Science (CS)
12:00 PM
//
3514, Mudd Hall ( formerly Seeley G. Mudd Library)
Details
Monday / CS Seminar
January 13th / 12:00 PM
Hybrid / Mudd 3514
Speaker
TBA
Talk Title
TBA
Abstract
TBA
Biography
TBA
Research/Interest Areas
TBA
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Zoom: TBA
Panopto: TBA
DEI Minute: tinyurl.com/cspac-dei-minute
Time
Wednesday, March 5, 2025 at 12:00 PM - 1:00 PM
Location
3514, Mudd Hall ( formerly Seeley G. Mudd Library) Map
Contact
Calendar
Department of Computer Science (CS)
WED@NICO SEMINAR: Neda Bagheri, University of Washington "Computational modeling of emergent spatiotemporal cell population dynamics"
Northwestern Institute on Complex Systems (NICO)
12:00 PM
//
Lower Level, Chambers Hall
Details

Speaker:
Neda Bagheri, Associate Professor, Department of Biology, University of Washington
Title:
Computational modeling of emergent spatiotemporal cell population dynamics
Abstract:
Computational models are essential tools that can be used to simultaneously explain and guide biological intuition. My lab employs agent-based modeling, machine learning, and dynamical systems to explain biological observations and interrogate multi-lateral regulatory networks that drive individual cellular decisions as well as cell population dynamics. We are interested in the inherent multiscale nature of biology, with a specific focus on system-level dynamics that emerge from interactions of simpler individual-level modules.
In this presentation, I introduce a multiscale agent-based model of a generic solid tumor microenvironment that integrates subcellular signaling and metabolism, cell-level decision processes, and dynamic vascular architecture and function. We use this modeling framework to understand decision processes among heterogeneous cell agents in changing microenvironments. The model is open-source and flexible/adaptable (it can characterize countless cell population dynamics!), but it is computationally costly to simulate and analyze at large scales. I highlight these challenges along with strategies to mitigate them, and showcase successes that derive from our model development process. I also describe how the model can be used to inform the design of experiments, interventions, and hypotheses that modulate population level responses.
Speaker Bio:
Neda Bagheri earned her doctorate in Electrical Engineering from the University of California in Santa Barbara. Her focus on control theory and dynamics piqued her interest in biology. After completing a postdoc in Biological Engineering at MIT, she joined the Chemical & Biological Engineering faculty at Northwestern University (2012). In 2019, she was recruited to both the University of Washington Seattle (where she holds a joint position in Biology and Chemical Engineering) and the Allen Institute for Cell Science.
In recognition for her research accomplishments and vision, Bagheri was awarded a National Science Foundation CAREER Award (2017) and a Senior Moulton Medal (2020). She was honored as a Distinguished Speaker for the Accelerated Discover Forum at IBM Research-Almaden (2018) as well as for the Mindlin Foundation (2019), and as the Plenary Speaker for the triennial International Federation of Automatic Control DYCOPS conference (2022). She serves on multiple science advisory and editorial boards, guiding the frontier of multidisciplinary research.
Location:
In person: Chambers Hall, 600 Foster Street, Lower Level
Remote option: https://northwestern.zoom.us/j/97273424116
Passcode: NICO25
About the Speaker Series:
Wednesdays@NICO is a vibrant weekly seminar series focusing broadly on the topics of complex systems, data science and network science. It brings together attendees ranging from graduate students to senior faculty who span all of the schools across Northwestern, from applied math to sociology to biology and every discipline in-between. Please visit: https://bit.ly/WedatNICO for information on future speakers.
Time
Wednesday, March 5, 2025 at 12:00 PM - 1:00 PM
Location
Lower Level, Chambers Hall Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
Research-In-Progress: Martin Falk
NSF-Simons National Institute for Theory and Mathematics in Biology
3:00 PM
//
Suite 4010
Details
Members of the NITMB community are invited to join us for Research-In-Progress meetings, an informal venue for members of the NITMB to discuss ongoing and/or planned research.
Martin Falk is a postdoctoral scholar in the Murugan and Irvine groups at the University of Chicago. The goal of Martin Falk’s research is to create next-generation materials which can compute, morph, and continually adapt to their environments. Falk’s work draws on techniques from computer vision and active learning and developing AI agents capable of autonomous search and rigorous scientific discovery in novel material platforms.
Learn more about Martin Falk's research and engage in discussion with the NITMB community. Research-In-Progress talks take place on Wednesdays at 3pm at the NITMB office (875 N Michigan Ave., Suite 4010). Snacks and coffee will follow.
Time
Wednesday, March 5, 2025 at 3:00 PM - 4:00 PM
Location
Suite 4010
Contact
Calendar
NSF-Simons National Institute for Theory and Mathematics in Biology
CS Seminar
Department of Computer Science (CS)
12:00 PM
//
3514, Mudd Hall ( formerly Seeley G. Mudd Library)
Details
Monday / CS Seminar
January 13th / 12:00 PM
Hybrid / Mudd 3514
Speaker
TBA
Talk Title
TBA
Abstract
TBA
Biography
TBA
Research/Interest Areas
TBA
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Zoom: TBA
Panopto: TBA
DEI Minute: tinyurl.com/cspac-dei-minute
Time
Friday, March 7, 2025 at 12:00 PM - 1:00 PM
Location
3514, Mudd Hall ( formerly Seeley G. Mudd Library) Map
Contact
Calendar
Department of Computer Science (CS)
SQE Lecturer Series: "Variegating Epigenetic Mechanisms as Complex Disease Switches" with Andrew Pospisilik , PhD
Simpson Querrey Institute for Epigenetics Lecture Series
10:00 AM
//
Simpson Querrey Auditorium, Simpson Querrey Biomedical Research Center
Details
The Simpson Querrey Institute for Epigenetics presents:
Andrew Pospisilik, PhD
Full Professor and Chair, Department of Epigenetics
Van Andel Research Institute, Grand Rapids, MI
"Variegating Epigenetic Mechanisms as Complex Disease Switches"
Abstract:
Our goal is to elucidate mechanisms underpinning complex disease susceptibility and presentation. Focusing on non-genetic, non-environmental origins of disease susceptibility, we previously identified the epigenetic silencer, Trim28, and the imprinted gene Nnat, as critical regulators of developmental robustness. Loss-of-function of either gene, intriguingly, triggers a unique developmental phenomenon known as ‘polyphenism’, in which animals can take on one of two distinct developmental phenotypic forms (and disease risk states) despite being genetically identical and environmentally controlled. Profiling human cohorts we find signatures of the same processes being active in approximately 50% of metabolically diseased patients. Our models represent the first formal demonstrations of mammalian polyphenisms and carry profound implications for our understanding of the origins of disease risk. I will share data that (i) characterize the distinctions between these triggerable disease in cancer, obesity and food-addiction; (ii) dissect the mechanism underpinning the underlying developmental bifurcation; (iii) provide evidence for alternate developmental trajectories in humans; and (iv) show one machine learning approach we are using to begin to tackle this problem in the genetically and environmentally heterogeneous human population. Collectively, our data highlight an underappreciated mechanistic layer heterogeneity (or sub-types) across the disease landscape.
I
Time
Monday, March 10, 2025 at 10:00 AM - 11:00 AM
Location
Simpson Querrey Auditorium, Simpson Querrey Biomedical Research Center Map
Contact
Calendar
Simpson Querrey Institute for Epigenetics Lecture Series
CS Seminar
Department of Computer Science (CS)
12:00 PM
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3514, Mudd Hall ( formerly Seeley G. Mudd Library)
Details
Monday / CS Seminar
January 13th / 12:00 PM
Hybrid / Mudd 3514
Speaker
TBA
Talk Title
TBA
Abstract
TBA
Biography
TBA
Research/Interest Areas
TBA
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Zoom: TBA
Panopto: TBA
DEI Minute: tinyurl.com/cspac-dei-minute
Time
Monday, March 10, 2025 at 12:00 PM - 1:00 PM
Location
3514, Mudd Hall ( formerly Seeley G. Mudd Library) Map
Contact
Calendar
Department of Computer Science (CS)
ME512 Seminar Speaker- Somnath Ghosh
McCormick - Mechanical Engineering (ME)
3:00 PM
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L211, Technological Institute
Details
Machine Learning Enabled Parametric Multiscale Modeling of Metals & Composites: From Fatigue Crack Nucleation to Damage Sensing
Professor Somnath Ghosh
Civil & Systems Engineering, Mechanical Engineering, and Materials Science & Engineering
Johns Hopkins University
The rapid surge of machine learning (ML) tools in developing efficient surrogate models for solving challenging problems has drawn significant attention from the Mechanics of Materials community. However, ML techniques rely on extensive training datasets and often lack physical interpretability. Also, exclusively data-driven models can result in ill-posed problems or non-physical solutions. Alternatively, the notion of ML-enhanced parametric upscaling has been introduced for multi-scale analysis of fatigue failure in metallics materials, damage and failure of unidirectional and woven composites, and damage sensing in multifunctional composites. The Parametrically Upscaled Constitutive Model (PUCM) for metallic materials like Ti alloys and the Parametrically Upscaled Continuum Damage Mechanics Model (PUCDM) for composites are thermodynamically-consistent constitutive models that bridge multiple spatial scales through the explicit representation of representative aggregated microstructural parameters (RAMPs), representing statistical distributions of morphological and crystallographic descriptors of the microstructure. ML tools, viz. genetic programming-based symbolic regression (GPSR) and artificial neural networks (ANN) are implemented for generating PUCM/PUCDM coefficients as functions of lower-scale RAMPs, using data sets of homogenized micromechanical response variables. For damage sensing in piezocomposite structures, the Parametrically Upscaled Coupled Constitutive Damage Model (PUCCDM) is developed coupling mechanical, damage, and electrical fields. An advanced machine learning model (ConvLSTM) based on the combination of a convolutional neural network and a recurrent neural network is developed to predict microstructural damage mechanisms from macroscopic electric signal and RAMPs. The computational tool chain outputs the highly efficient PUCM/PUCDM/PUCCDM, which are invaluable tools for multiscale analysis with implications in location-specific design.
Time
Monday, March 10, 2025 at 3:00 PM - 4:00 PM
Location
L211, Technological Institute Map
Contact
Calendar
McCormick - Mechanical Engineering (ME)
CS Seminar
Department of Computer Science (CS)
12:00 PM
//
3514, Mudd Hall ( formerly Seeley G. Mudd Library)
Details
Monday / CS Seminar
January 13th / 12:00 PM
Hybrid / Mudd 3514
Speaker
TBA
Talk Title
TBA
Abstract
TBA
Biography
TBA
Research/Interest Areas
TBA
---
Zoom: TBA
Panopto: TBA
DEI Minute: tinyurl.com/cspac-dei-minute
Time
Wednesday, March 12, 2025 at 12:00 PM - 1:00 PM
Location
3514, Mudd Hall ( formerly Seeley G. Mudd Library) Map
Contact
Calendar
Department of Computer Science (CS)
CS Seminar
Department of Computer Science (CS)
12:00 PM
//
3514, Mudd Hall ( formerly Seeley G. Mudd Library)
Details
Monday / CS Seminar
January 13th / 12:00 PM
Hybrid / Mudd 3514
Speaker
TBA
Talk Title
TBA
Abstract
TBA
Biography
TBA
Research/Interest Areas
TBA
---
Zoom: TBA
Panopto: TBA
DEI Minute: tinyurl.com/cspac-dei-minute
Time
Friday, March 14, 2025 at 12:00 PM - 1:00 PM
Location
3514, Mudd Hall ( formerly Seeley G. Mudd Library) Map
Contact
Calendar
Department of Computer Science (CS)
Winter exams begin
University Academic Calendar
All Day
Details
Winter exams begin
Time
Monday, March 17, 2025
Contact
Calendar
University Academic Calendar