Interests and Expertise

Andre Kashliev's work focuses on Big Data Modeling/Management, and Cloud AI Systems. His broader interests include cloud-based Machine Learning pipelines, generative AI systems, and workflow-driven AI architectures. His research addresses the issues of scalable data modeling, distributed workflows, and provenance-aware systems that support reproducible and responsible AI. His other interests include databases, cloud computing, data analytics, and scientific workflows.

Brief Bio

Andre Kashliev has completed his Ph.D. in Computer Science at Wayne State University in 2016 in the Big Data Research Lab led by Dr. Shiyong Lu. Prior to that he obtained his M.S. in Computer Science from the University of Texas-Pan American in 2011. He has published numerous research articles in peer-reviewed international journals and conferences, including IEEE Transactions on Services Computing (TSC), Data & Knowledge Engineering (DKE), International Journal of Computers and Their Applications (IJCA), International Journal of Big Data, IEEE International Congress BigData (IJBD), and IEEE International Conference on Services Computing (SCC), and others.