Machine Learning and Data Intensive Computing 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

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 (Started in Fall 2022)

Abhinab 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 (Started in Fall 2024)

Anusha 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 (Started in Fall 2025)

Prashant 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.

Headshot of Sudip Tiwari

Sudip Tiwari (Started in Fall 2026)

https://sudiptiwari.github.io

Sudip earned his bachelor's degree in Computer Engineering from Pulchowk Campus, Tribhuvan University, Nepal. His current research interests lie in large language models, knowledge distillation, and low-resource and data-efficient machine learning. Outside of research, he enjoys hiking, traveling, playing and watching football (soccer) and cricket.

PhD Alumni

Dissertation: A Robust Learning Framework for Resource-Constrained Domain Adaptation

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

 

Dissertation: Toward a Unified Framework for Open World Visual Learning

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