Past events

Computer Science M.S. application deadline for fall. Applications must be submitted by 11:59 p.m. CST.

We offer fall admission only and do not admit for the spring semester.

Computer Science M.C.S. application deadline for fall. Applications must be submitted by 11:59 p.m. CST.

We offer fall admission only and do not admit for the spring semester.

The computer science colloquium takes place on Mondays and Fridays from 11:15 a.m. - 12:15 p.m. This week's speaker, Tomer Galanti (MIT), will be giving a talk titled "Fundamental Problems in AI: Transferability, Compressibility and Generalization".

Abstract

In this talk, we delve into several fundamental questions in deep learning. We start by addressing the question, "What are good representations of data?" Recent studies have shown that the representations learned by a single classifier over multiple classes can be easily adapted to new classes with very few samples. We offer a compelling explanation for this behavior by drawing a relationship between transferability and an emergent property known as neural collapse. Later, we explore why certain architectures, such as convolutional networks, outperform fully-connected networks, providing theoretical support for how their inherent sparsity aids learning with fewer samples. Lastly, I present recent findings on how training hyperparameters implicitly control the ranks of weight matrices, consequently affecting the model's compressibility and the dimensionality of the learned features.

Additionally, I will describe how this research integrates into a broader research program where I aim to develop realistic models of contemporary learning settings to guide practices in deep learning and artificial intelligence. Utilizing both theory and experiments, I study fundamental questions in the field of deep learning, including why certain architectural choices improve performance or convergence rates, when transfer learning and self-supervised learning work, and what kinds of data representations are learned in practical settings.

Biography

Learn about the MSSE program at the upcoming in-person information session on February 28 from 1-2 p.m. CST.

Info sessions are recommended for those who have at least 1-2 years of software engineering experience.

During each session, MSSE staff will review:

• Requirements (general)
• Applying
• Prerequisite requirements
• What makes a strong applicant
• Funding
• Resources
• Common questions
• Questions from attendees
   

RSVP to attend!

Artificial Intelligence is now at the forefront of technological interest in solving socially challenging problems, like identifying people who may discuss dangerous mental illness behaviors online (e.g. suicidal ideation, self-injury, and opioid addiction). We urgently need better AI to handle the volume and risk of this content in social networks. However, it is important to create AI and interventions in this space that are ethical and helpful, or we risk harming the very people we intend to help. Assistant Professor Stevie Chancellor will discuss the promises and perils for AI that predicts and intervenes in mental health in social media, and what we can do to make it more technically rigorous, ethical, and compassionate toward people in distress. She will discuss recent work in her research group on TikTok and mental health, and visions for the future of AI to assist in socially hard problems.

Please join us at the Computer Science and Data Science Graduate Student Department Head Town Hall. Light refreshments and snacks will be available.

This is your chance to voice your opinion and offer critical feedback on teaching, student services, and any other items you think can be improved.  Your feedback and insights are important to help us improve your graduate experience.

Please use the link below to RSVP, or provide feedback regarding your experiences in your computer science courses and within the department. Please note that you can remain anonymous to provide feedback:

RSVP Link

Please join us at the Computer Science and Data Science Undergraduate Student Department Head Town Hall. Light refreshments and snacks will be available.

This is your chance to voice your opinion and offer critical feedback on teaching, student services, and any other items you think can be improved.  Your feedback and insights are important to help us improve your graduate experience.

Please use the link below to RSVP, or provide feedback regarding your experiences in your computer science courses and within the department. Please note that you can remain anonymous to provide feedback:

RSVP Link

The computer science colloquium takes place on Fridays from 11:15 a.m. - 12:15 p.m. This week's speaker, Xuhai "Orson" Xu (MIT), will be giving a talk titled "How Do We Get There?: Toward Intelligent Behavior Intervention."

Abstract

As the intelligence of everyday smart devices continues to evolve, they can already monitor basic health behaviors such as physical activities and heart rates. The vision of an intelligent behavior change intervention pipeline for health -- combining behavior modeling & interaction design -- seems to be within reach. How do we get there?

In this talk, I will introduce a comprehensive intervention pipeline that bridges behavior science theory-driven designs and generalizable behavior models. I will also introduce my efforts on passive sensing datasets, human-centered algorithms, and a benchmark platform that drives the community toward more robust and deployable intervention systems for health and well-being.

Biography