Research: Machine Learning, Pervasive Healthcare, Medical Time Series, Brain-Computer Interfaces, Neurological Disorder Diagnosis

Xiang is an Assistant Professor in the Department of Computer Science at UNC Charlotte Since 2022. He was a postdoctoral fellow at Harvard University working on deep learning for medical data analysis. Xiang received his Ph.D. degree (in 2020) in Computer Science from the University of New South Wales (UNSW). His research outcomes have been published in prestigious conferences (such as ICLR, NeurIPS, and KDD) and journals (like Nature Computational Science), attracted 1700+ citations.

Research: Machine Learning, Data Science, Scalable Algorithms, AI theory

Christian is an Assistant Professor in Computer Science at the University of North Carolina at Charlotte. Prior to joining UNC Charlotte, He was a Postdoctoral Fellow at the Department of Applied Mathematics and Statistics at Johns Hopkins University (mentored by Mauro Maggioni) after completing a Ph.D. in Mathematics at Technical University of Munich in 2019, advised by Felix Krahmer. He obtained M.Sc. and B.Sc. degrees in Mathematics from TU Munich in 2015 and 2013.

Research: Natural Language Processing, Machine Learning, Music Information Retrieval, Computational Creativity

Razvan is an Associate Professor in the Department of Computer Science at UNC Charlotte. Prior to joining Charlotte in 2020, he was a Professor in EECS at Ohio University. He received his PhD in Computer Science from the University of Texas at Austin in 2007. His research interests lie in the general area of machine learning, with a focus on applications in natural language processing, music information retrieval, biomedical informatics, computer architecture, computational creativity, and more recently education. His work has been funded by grants from the National Science Foundation, the National Institutes of Health, and the US Air Force.

Research: Efficient Machine Learning, Transfer Learning/Continual Learning, Computer Vision, Hardware Acceleration

Li is an Assistant Professor in the Department of Computer Science at University of North Carolina at Charlotte. Prior to that, Li received his Ph.D. degree from Arizona State University, Master’s degree from the University of Central Florida, and Bachelor's degree at Northeastern University, China. His research interests include 1) efficient and on-device Machine Learning; 2) computer vision; 3)transfer/continual Learning; 4) efficient AI computing hardware accelerator design.

Research: Reinforcement Learning, Distributed Learning, Knowledge Representation and Transfer, Human-AI Interactions, Brain-Computer Interfaces

Jake is an Assistant Professor in the Department of Computer Science at the Charlotte. He is working on efficient agent's learning and adaptation encompassing transfer learning, interpretational learning, human-AI interactions, robust and safe exploration, and distributed learning. He received Ph.D. in Computer Science at the Colorado State University under the supervision of Chuck Anderson. His dissertation investigated and developed Sparse Bayesian Models to enable example-based reinforcement learning. His research has been supported by NSF and NIH.

Research: Computer Vision, Video Representation Learning, Robotic Vision

Srijan is an Assistant Professor in the Department of Computer Science at the University of North Carolina at Charlotte. At UNC Charlotte, he is working on Video Representation Learning and Robotic Vision. Prior to UNC Charlotte, Srijan was a Postdoctoral Associate at Stony Brook University under the supervision of Michael Ryoo. In 2020, he successfully completed their Ph.D. in Computer Science at INRIA, Sophia Antipolis, France, under the guidance of Francois Bremond and Monique Thonnat. His Ph.D. thesis focused on "Spatio-temporal attention mechanisms for Action Recognition," Srijan pursued their Post-Graduate studies in Computer Science at the National Institute of Technology (NIT), Rourkela.

Research: Computer Vision, Video Understanding, Multi-Modal Learning

Arkaprava is a PhD student in the Department of Computer Science advised by Dr. Srijan Das. His research focuses on Action Recognition for videos for Actions of Daily Living. He is currently working on Self-Supervised Learning and Multi-Modal Learning for Video Understanding.

Research: Reinforcement Learning, Brain-Computer Interfaces

Benjamin is a PhD student in the Department of Computer Science advised by Dr. Jake Lee. His research focuses on understanding different modalities of human feedback to incorporate them to reinforcement learning. He is interested in human brain signals, especially error-related potentials known as to be elicited when humans commit or observe erroneous events to enhance human-guided training of AI. As a senior PhD student, he leads projects guiding junior graduate students.

Research: Multi-object Tracking, Audio/Speech Classificaiton

David is a PhD student in the Department of Computer Science advised by Drs. Min Shin and Jake Lee. His research focuses on social interaction detection for stroke patients' rehabilitation by using audio-based sound classification models with smart watches. His previous research focused on tracking multiple objects.

Research: Computer Vision, Video Understanding

Dominick is a PhD student in the Department of Computer Science advised by Dr. Srijan Das. His research focuses on understanding human actions in videos, specifically activities of daily living that are observed in real-world environments. He is interested in utilizing both egocentric and third person viewpoints, as well as multiple modalities, to solve the challenges of activities of daily living.

Research: Natural Language Processing, Computer Science Education, Dialogue Systems

Erfan is a PhD student in the Department of Computer Science at UNC Charlotte. His research interests lie in natural language processing, dialogue systems, and computer science education. His dissertation research focuses Socratic Debugging defined as a Socratic conversation between an instructor agent and a student where the instructor guides the student to fix a buggy program without giving the solution directly.

Research: Machine Learning, Non-Convex Optimization, AI theory

I am currently pursuing PhD under Dr Christian Kuemmerle. Prior to this I completed an MSc in Data Science from CMI, India and an MSc in Mathematics from DU, India. My research focuses on creating scalable and dependable algorithms in Machine Learning and Data Science, particularly at the intersection of Mathematics and Computer Science. I address computational and statistical challenges posed by complex models, such as developing efficient optimization techniques for solving problems with sparsity or low-rank structures. My work leverages various mathematical concepts, including high-dimensional Probability, Non-Convex Optimization, Numerical Linear Algebra, and Advanced Machine Learning to effectively tackle these challenges

Research: Computer Science Education, Accessibility Services

Justin is a Ph.D. student in the Department of Computer Science at UNC Charlotte. He received his B.S. degree in Computer Science from the University of North Carolina at Chapel Hill. His research interests include computer science education and accessibility services.

Research: Machine Learning, Data Mining, Graph Neural Networks, Computational Neuroscience

Nan is a Ph.D. student in the Department of Computer Science at the University of North Carolina (UNC) at Charlotte. Before joining UNC Charlotte, he received his B.S. degree in Bioinformatics from Peking University in 2023. His research interests lie in machine learning and data mining with applications in computational neuroscience.

Research: Computer Vision, Video Understanding, Object Detection

Rajatsubhra (Raj) is a first year PhD student in the Department of Computer Science advised by Dr. Srijan Das. He is exploring the areas of object detection through semi-supervised learning and video activity understanding. In his leisure time he likes to play fifa and read Batman comics.

Research: Anomaly Detection, Fraud Detection

Raju is a PhD student in the Department of Computer Science advised by Dr. Jake Lee. His research focuses on anomaly and fraud detection problems, especially in banking and credit card cases. As a senior software engineer, he is passionate about leveraging technology to tackle complex challenges and eager to make a meaningful impact in the field.

Research: Reinforcement Learning, Continual Learning

Rakesh is a MS student in the Department of Computer Science advised by Dr. Jake Lee. His research focuses on evaluating continual learning algorithms in diverse environments, assisting Ben.

Research: Machine Learning, Medical Time Series, Domain Generalization

Taida "Trent" Li is a Ph.D student in the Department of Computer Science at the University of North Carolina at Charlotte (UNCC), currently affiliated with Charlotte Machine Learning Lab (CML). Li received his master's degree in computer science from Rice University in May 2023. His research interests lie in machine learning in medical time series.

Research: Natural Language Processing, Machine Learning, Recommender Systems

Tonmoy Hasan is a PhD student in the Department of Computer Science at UNC Charlotte. His primary areas of research include natural language processing, machine learning, and recommender systems, with a current emphasis on modeling serendipity-oriented recommender systems.

Research: Machine Learning, Medical Time Series, Self-supervised Learning

Yihe is a Ph.D. student in the Department of Computer Science at the University of North Carolina(UNC) - Charlotte. Yihe received his Bachelor's degree in Electrical and Computer Engineering from University of Missouri - Columbia and his Master's degree in Computer Science from New York University. His research interests lie in medical time series and self-supervised learning.

Research: Reinforcement Learning, Continual Learning

Andrew is a MS student in the Department of Computer Science advised by Dr. Jake Lee. His research focuses on evaluating continual learning algorithms in diverse environments, assisting Ben.

Research: Machine Learning, Medical Imaging, Neuro-imaging

Aniqa is a master's candidate in the Department of Computer Science at UNC Charlotte. She is currently working on Multimodal Machine Learning for neurological disease diagnosis under the supervision of Dr. Zhang. She has previously worked extensively with neuro-imaging acquisition, databases and processing.

Research: Computer Vision

Jonathan is a Masters student in the Department of Computer Science. His research focuses on object detection, specifically the use of semi-supervised learning to leverage large quantities of unlabeled data. He is interested in utilizing a number of different architectures and methods to solve the challenges semi-supervised object detection.

Research: Audio/Speech Classificaiton, Physical Activity and Social Behavior

Mehdi is a MS student in the Department of Computer Science advised by Drs. Min Shin and Jake Lee. As a Fullbright scholar from Algeria, he focuses on detecting and identifying the human speech sounds from TV. He generalizes the problem to distinguish natural voice from speaker generated voice.

Research: Machine Learning

Sampada is a M.S. student in the Department of Computer Science at UNC Charlotte. She received her B.S. degree in Computing and Software Systems from The University of Melbourne in 2017. Her research interests include machine learning.

Research: Computer Vision, Video Understanding

Vishal is a Masters student in the Department of Computer Science advised by Dr. Srijan Das. His research work focuses on creating baseline benchmarks for various action recognition algorithms primarily assisting Dominick Reilly.

Research: Machine Learning, Cryptography

Eshan is a high school senior serving as a research intern since July 2023. He plans on studying computer science in college and intends to focus on artificial intelligence. He is currently working on developing machine learning models for a variety of different purposes. He has also worked in cryptography in the past.

Research: Graph Learning, Complex System Optimization

Joshua is an UG student in the Department of Computer Science advised by Dr. Jake Lee. His research focuses on testing diverse graph construction algorithms, primarily assisting Ben.

Research: Machine Learning, Graph Representation Learning, Medical Time Series, Clinical Trial Outcome Prediction

Yu has joined the CharMLab as a research intern since Fall 2022. He is a master student at the University of Chinese Academy of Sciences (UCAS) working on machine learning for healthcare now. Yu received his B.S. degree (in 2021) in Fintech and Software Engineering from Northeastern University.