Research Focus

Andre Kashliev conducts research in AI Systems and big data modeling/management, with emphasis on cloud-based machine learning pipelines, generative AI systems, and workflow-driven AI architectures. His work focuses on scalable data modeling, distributed workflows, and provenance-aware systems that support reproducible and responsible AI. Broader 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.