Laboratory Directory

Lab Directors

Headshot of Qi Yu

Xumin Liu

Qi Yu, PhD

Graduate Program Director and Professor
Rochester Institute of Technology

I received my Ph.D. from the Department of Computer Science at Virginia Tech, Blacksburg, VA, M.E from National University of Singapore, Singapore, and B.S from Zhejiang University, Hangzhou, China. For more details check my CV.

 

 

Xumin Liu, PhD

Professor of Computer Science
Rochester Institute of Technology

I received my Ph.D. from the Department of Computer Science at Virginia Tech, Blacksburg, VA, M.E. from Jinan University, Guangzhou, China, and B.E. from Dalian University of Technology, China. For more details check my CV. 

PhD students

Headshot of Yuansheng Zhu

Yuansheng Zhu (Started in Fall 2019)

Yuansheng received his bachelor degree in automation at Northwestern Polytechnical University in 2017, and master degree in Electrical Engineering at the University of Pittsburgh in 2019 respectively. His research generally lies in Machine learning and Computer Vision with applications to different fields, such as medical diagnosis and anomaly detection.

Headshot of Xiaofan Que

Xiaofan Que (Started in Fall 2019)

Xiaofan received her B.Eng and M.Eng in Computer Science from University of Electronic Science and Technology of China, Chengdu, China. Her research interest focuses on robust meta-curriculum learning from noisy few-shot tasks. 

Dingrong Portrait

Dingrong Wang (Started in Fall 2020)

Dingrong received his Bachelor degree in Software Engineering from Dalian University of Technology, Dalian, China. His research interest now lies in the areas of reinforcement learning and its applications in computer vision.

Mozaffari Portrait

Mahsa Mozaffari (Started in Fall 2022)
https://mahsamozaffari.com

Mahsa received her B.S. degree in software engineering from Sharif University of Technology, Tehran, Iran, and her M.Sc. degree in Electrical Engineering from University of South Florida, Tampa, FL. Her research interests include Multilinear Methods, Multimodal Machine Learning, Bayesian Inference, and Deep Learning with applications in computer vision, and tensor analysis.

Pyakurel Portrait

Spandan Pyakurel (Started in Fall 2022)

Spandan received her bachelor degree in Computer Engineering from Pulchowk Campus, Tribhuvan University, Nepal. Her research interest lies in the areas of machine learning and AI with a special focus on uncertainty analysis and novelty detection.

Abhinab Acharya

Abhinab Acharya earned his Bachelor’s degree in Electrical Engineering from Tribhuvan University and worked as an R&D Software Engineer at North Star Developer’s Village, where he developed machine learning solutions and deployed large-scale platforms. His current research focuses on continual learning, data-efficient machine learning, and robustness of foundation models, with applications to vision and multimodal systems.

Anusha Acharya

Anusha Acharya received her Bachelor’s degree in Mechanical Engineering from Pulchowk Campus, Tribhuvan University, Nepal. Her research focuses on developing weakly supervised methods for anomaly detection, with applications in safety-critical events.

Prashant Shrestha

Prashant Shrestha received his Bachelor's Degree in Electronics, Communication and Information Engineering from Tribhuvan University, Nepal. His current research interest lies in LLM Safety and federated learning.

PhD Alumni

Dissertation: Towards a Foundational Framework for Real-World Active Learning: Theory, Algorithms, and Applications

Dissertation: Uncertainty-Aware Meta-Learning for Learning from Limited Data

Dissertation: Learning to Learn from Sparse User Interactions

 

Dissertation: Robust Weakly Supervised Learning for Real-World Anomaly Detection

 

Dissertation: Knowledge Integration for Human-In-The-Loop Machine Learning

 

Dissertation: Active Learning from Knowledge-Rich Data

 

Dissertation: Modeling Users Feedback Using Bayesian Methods for Data-Driven Requirements Engineering

 

Dissertation: Domain knowledge representation learning for image understanding

 

MS Students

A Low-Cost Warehouse Management Solution for Small Businesses

Comparison of approaches used in Recommender Systems
Davis Jaymes, Classifying Forms of Dementia Through the Use of Machine Learning

Time Series Based Classification on Electroencephalagraphy (EEG) Data: A comparative study

Exploring News Content for Popularity Prediction

Comparison of Supervised & Hybrid Topic Modeling for Extraction, Ranking & Evaluation of Quality Features of Web Services & User Review Sentiment Analysis

Mining Unstuctured Data to Extract Meaningful Keywords for Large-Scale Data Analysis

Use of Social Media in Promoting Democracy Through Political Campaign and Election Monitoring in Nigeria