Faculty


Daniel Jugan
Personal Website: http://webpages.charlotte.edu/djugan/


Rrezarta Krasniqi
EducationDegree Institution: University of North TexasDegree: Ph.D. in Computer Science and EngineeringYear Graduated: 2024 Degree Institution: University of Notre Dame Degree: M.S. in Computer Science and EngineeringYear Graduated: 2021 Research Areas: Software Engineering, Requirements Engineering, Software Quality, Software Maintenance and Evolution, Applied Machine Learning, AI for SE My research centers on detecting quality-related bugs, and I […]

Siddharth Krishnan
Siddharth is a new faculty in the department of computer science (College of Computing and Informatics) at UNCC. His research interests are in web-mining, data analytics, computational social science, and applied machine learning with a primary emphasis on analyzing, characterizing, and forecasting information (news, rumors, memes, advertisements, etc.) dynamics on online social networks & social […]

Christian Kuemmerle
Personal Website: http://ckuemmerle.com Degree Institution: Technical University of Munich Degree: Ph.D. in Mathematics Research Areas: Mathematical Foundations of Machine Learning, Non-Convex Optimization, Trustworthy Machine Learning, Scalable Algorithms, Information Theory, Recommender Systems Dr. Christian Kümmerle’s research interests are in the mathematical foundations of machine learning and the development and analysis of efficient algorithms for large scale […]

Abigail Leavitt LaBella
Dr. Abigail Leavitt LaBella received her Ph.D from the University Program in Genetics and Genomics at Duke University in 2017. After defending her thesis on deep-sea population genomics, Dr. LaBella worked as a postdoctoral scholar in the lab of Dr. Antonis Rokas at Vanderbilt University. During this time Dr. LaBella led research projects that leveraged […]

Jake Lee
Personal Website: http://webpages.charlotte.edu/mlee173 Lab and Website: Video and Image Analysis Lab Ph.D. Institution: Colorado State University Research Description: Dr. Jake Lee’s research interests are in foundational machine learning, with an emphasis on reinforcement learning. Recent projects in robotics, adaptive systems, human-AI interactions are investigated under NSF and NIH support. Diverse angles of learning including knowledge […]

