DK is an Assistant Professor in the CS Department at North Carolina State University and leads the NCSU Reliable & Efficient Computing Lab. His research interest is resource-efficient deep learning for AI at scale, investigating how to achieve Pareto optimality between decision reliability, computational resources, and model performance of deep learning systems. DK’s research has been published multiple times in top conferences and journals in AI, NLP, and other fields. He serves as the Column Editor for ACM SIGAI Newsletter, chairs The First Workshop on DL-Hardware Co-Design for AI Acceleration with AAAI 2023, and co-chairs The Resource-Efficient Learning for Knowledge Discovery Workshop with KDD 2023. He has served as session chair for New Deep Learning Architectures, and for Scalable & Trustable AI at KDD 2022, and has served as a (senior) PC member and regular reviewer for over 30 major conferences and 16 journals. In addition, he has launched the Machine Learning Algorithms & Natural Language Processing community. DK also has extensive research experience in the industry. He has been collaborating with Microsoft Research, Google ResearchMoffett AI, and NEC labs America, and holds 10 US patents/applications. DK's long-term research goal is to democratize AI to serve a broader range of populations and real-world domains.

Research Areas

  • Artificial Intelligence and Intelligent Agents


  • The Pennsylvania State University, PA, USA, 2022
  • University of Chinese Academy of Sciences, Beijing, China, 2017
  • Renmin University of China, Beijing, China, 2014


Google ScholarTwitterLinkedIn