AI/ML Resource Fair

Labs in SEAS
UVA SEAS

Time: 2024-10-03, 12:00 - 13:00 ET
Location: Link Lab Arena and Zoom

Overview As part of AI/ML seminar activities, we will host the first-ever AI/ML resource fair at UVA!

The goal of the resource fair is to encourage collaboration between labs and graduate students, and for motivating undergrads to look for research opportunities. This resource fair includes posters from various labs across departments in SEAS.

Posters

• Biomedical Engineering

  PI	Presenter / Poster Title
  Jeff Saucerman	- Jeff Saucerman, Anders Nelson: Network modeling and high-content imaging identifies cardiac fibrobalst phenotypic responses to drugs

• Chemical Engineering

  PI	Presenter / Poster Title
  Camille Bilodeau	- Daniel Garzon: PepMNet: A Hybrid Deep Learning Model for Predicting Peptide Properties Using Hierarchical Graph Representations

• Computer Science

  PI	Presenter / Poster Title
  Chen-Yu Wei	- Haolin Liu: Towards Theoretical Foundations for Reinforcement Learning in Dynamic Environments
  	- Braham Snyder
  Felix Lin	- Afsara Benazir: Maximizing the Capabilities of Tiny Speech Foundation Models in a Privacy Preserving Manne
  	- Rongxiang Wang: Boosting streaming speech processing with foundation models
  	- Wonkyo Choe
  Kun Qian	- Kun Qian: Introduction to Wireless-Intelligence-For-Everything (WIFX) Lab
  Matheus V. X. Ferreira	- Matheus V. X. Ferreira
  Rohan Chandra	- Rohan Chandra: Perception, Reasoning, and Planning for Safe, Agile, and Natural Mobile Service Robots
  Shangtong Zhang	- Jiuqi Wang, Ethan Blaser
  Wajih Ul Hassan	- Mati Ur Rehman: A Privacy-Aware Approach to System Intrusion Detection
  Yangfeng Ji	- Caroline Gihlstorf: Investigating Correlations Between Computational Mechanisms of LLMs and Their Performance on Linguistic Test Suites
  	- Karolina Naranjo-Velasco: CoCoSet 🥥: A Colombian Court Decisions DataSet Using Visual Cues
  Yen-Ling Kuo	- Yen-Ling Kuo: Learning and Interactive Robotics Lab Overview
  	- Xuhui Kang, Sean SungWook Lee: Teaching Robots to Manipulate Objects and Work with Humans

• Electrical and Computer Engineering

  PI	Presenter / Poster Title
  Cong Shen	- Wei Shen: Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization
  Cong Shen & Jundong Li	- Zihan Chen: Verification of Machine Unlearning is Fragile
  Jundong Li	- Yinhan He: Explaining Graph Neural Networks with Large Language Models:A Counterfactual Perspective for Molecular Property Prediction
  Miaomiao Zhang	- Nian Wu: TLRN: Temporal Latent Residual Networks For Large Deformation Image Registration
  	- Jiarui Xing
  	- Nivetha Jayakumar: DIGIT: Diffeomorphic Image Generation with Instructions from Text
  Mool C. Gupta	- Atchutananda Surampudi, Mahantesh Khetri: Laser Processing and Application of AI/ML Models
  Nikos Sidiropoulos	- Paris Karakasis: Multivariate Density Estimation Using Low-Rank Fej´er-Riesz Factorization
  Scott Acton	- Matthew Korban: A Semantic and Motion-Aware Spatiotemporal Transformer Network for Action Detection
  	- Soumee Guha
  	- Jessica Tierney
  Tom Fletcher	- Aman Shrivastava, Yinzhu Jin: Controllable Image Synthesis
  	- Tyler Spears, Ferial Delavari: Understanding Functional and Structural Brain Networks from Brain MRIs with Deep Learning
  	- Aman Shrivistava, Shen Zhu, Tyler Spears: Generating Arbitrary-Resolution Brain MRIs with Implicit Latent Representation

• Mechanical and Aerospace Engineering

  PI	Presenter / Poster Title
  Ye Sarah Sun	- Chukwuemeka Ochieze: Distributed Sensing Enabled Soft Robot Modeling and Control: From Theory, Sensing, to Robot Design
  	- Sameh Beaber, Zhen Liu: Physics-Guided Deep Learning Enabled Surrogate Modeling for Pneumatic Soft Robots
  	- Soroush Zare: Transformer-CNN-Based EEG Motor Imagery Classification for Assistive Technology

• Systems and Information Engineering

  PI	Presenter / Poster Title
  Afsaneh Doryab	- Afsaneh Doryab
  Matthew L. Bolton	- Yeonbin Son, Matthew L. Bolton: Human-in-the-loop Framework for eXplainable Recommender Systems