Rate My Professor Aparna Varde

Aparna Varde is a Full Professor at the SDU Centre for Software Technology within the Maersk Mc-Kinney Moller Institute at the University of Southern Denmark's Faculty of Engineering. Appointed in September 2025 as the first full professor of software engineering at the new Vejle campus, she previously held a tenured position as Associate Professor in the School of Computing at Montclair State University, where she also served as Associate Director of the Clean Energy and Sustainability Analytics Center and Doctoral Faculty in the Environmental Science and Management Ph.D. Program. Earlier roles include tenure-track Assistant Professor at Virginia State University and Visiting Researcher at the Max Planck Institute for Informatics in Germany. She earned her B.E. in Computer Engineering from the University of Bombay in India, M.S. in Computer Science from Worcester Polytechnic Institute, and Ph.D. in Computer Science from the same institution, with a dissertation titled Graphical Data Mining for Computational Estimation in Materials Science Applications advised by Prof. Elke Rundensteiner. Her academic career has focused on advancing artificial intelligence through ethical and efficient applications.

Professor Varde's research interests encompass machine learning, data mining, explainable AI, sustainable AI, intelligent systems, and integrating commonsense knowledge into AI systems to promote transparency, trust, and resource efficiency. In March 2026, she secured a DKK 6 million grant from the Novo Nordisk Foundation—her first at SDU—to develop sustainable AI systems that require fewer resources, combining machine learning with expert knowledge and supporting the Intelligent Systems Laboratory in Vejle, including hiring a PhD candidate and postdoctoral researcher. Key publications include NJ-EQUIP: A Spatiotemporal Analytics and Visualization Portal to Advance Energy Equity (IEEE CCWC, 2026, Best Paper Award in Energy Management Track); A vision for sustainable, equitable healthcare applications with XAI and transfer learning to augment neural models (ACM EDBT, 2026); Incorporating Commonsense Knowledge to Enhance Robot Perception (IEEE TASE, 2025); Facilitating COVID Recognition from X-rays with Computer Vision Models and Transfer Learning (Multimedia Tools and Applications, 2024); Computational Estimation by Scientific Data Mining with Classical Methods to Automate Learning Strategies of Scientists (ACM TKDD, 2022); and Extracting Cultural Commonsense Knowledge at Scale (ACM WWW, 2023, Spotlight Mention). She has received numerous accolades, including Best Paper Awards at IEEE IISA 2024, IEEE IEMTRONICS 2024, and earlier IEEE conferences, the Outstanding Professor and Researcher classification by USCIS in 2008, and Department of Energy funding during her PhD. At SDU, she plans to teach courses on explainable AI, sustainable AI, and responsible use of generative models starting in 2026.