Charalampos Chelmis

Charalampos Chelmis is an Associate Professor in the Department of Computer Science at the University at Albany, State University of New York (SUNY). He directs the Intelligent Big Data Analytics, Applications, and Systems (IDIAS) Lab, focusing on cutting-edge research in data-intensive computing for social good. Previously, he was a Senior Research Associate at the University of Southern California.

Education:

• PhD in Computer Science, University of Southern California (2013)
• MS in Computer Science, University of Southern California (2010)
• BEng in Computer Engineering and Informatics, University of Patras, Greece (2007)

Research Interests: Dr. Chelmis specializes in Network Science, Big Data analytics, and scalable algorithms for complex, high-dimensional datasets. His work integrates graph theory, machine learning, and data mining to address real-world challenges like energy efficiency and social network analysis. Key applications include cyberbullying detection, demand response in smart grids, and computational social science.

Publication Trends: His recent articles (2015-2016) demonstrate a strong focus on scalable algorithms for social networks and energy systems, including FPGA optimizations, dynamic graph computation, and machine learning for time-series prediction. Dominant themes include social influence modeling, big data clustering, and hardware-accelerated graph processing.

Awards & Honors:

• DARPA Forecasting Chikungunya Challenge Methodology Prize (2015)
• SUNY-B Faculty Research Award (2018)
• UAlbany's Next Research Frontier Award (2019)
• Fulbright Mutual Educational Exchange Grant (2008)

Grants & Advising: He leads an NSF-funded project (CRII: III: Adding Exploratory Statistical Analysis and Prediction Support to SPARQL) to simplify semantic data analysis. As director of IDIAS Lab, he mentors PhD and Master's students in projects like noisy-label learning and cyberbullying detection.

Labs & Teams: The IDIAS Lab develops solutions for socially important problems, collaborating with industry partners (e.g., Google, Oracle) and focusing on scalable ML systems and semantic data integration.