Arjun Pandya, apandya1 _at_ umbc.edu, Spring 2018 – present
Oluwatobiloba (Tobi) Odunsi, oodunsi1 _at_ umbc.edu, Spring 2021 – present
Xingyan Li, xingyanli _at_ umbc.edu, Fall 2021 – present
Seraj Mostafa, s172 _at_ umbc.edu, Fall 2021 – present
Azim Khan, azimkhan22 _at_ umbc.edu, Spring 2022 – present
Francis Nji, fnji1 _at_ umbc.edu, Spring 2022 – present
Joyce Padela, jpadela1 _at_ umbc.edu, Spring 2022 – present
Homayra Alam, halam3 _at_ umbc.edu, Fall 2022 – present
Omar Faruque, omarf1 _at_ umbc.edu, Fall 2022 – present
Akila Sampath, asampath _at_ umbc.edu, Spring 2023 – present
Mostafa Cham, mcham2 _at_ umbc.edu, Fall 2023 – present
Tartela Tabassum, tartelt1 _at_ umbc.edu, Spring 2024 – present
Graduated PhD Students
Sahara Ali, Summer 2024, Ph.D. Doctoral Thesis: Spatiotemporal Forecasting and Causality Methods for Arctic Amplification. Position after graduation: Assistant Professor, Department of Information Science, University of North Texas.
Xin Huang, Summer 2023, Ph.D. Doctoral Thesis: Deep Learning based Cloud Retrieval Techniques using Multiple Satellite Remote Sensing Data. Position after graduation: Assistant Professor, Department of Computer and Information Sciences, Towson University.
Qitao Xie, Spring 2023, Ph.D. in Electrical Engineering, Doctoral Thesis: Deep Learning Based Chatbot on FinTech Applications. Part-time Student.
Xin (Starly) Wang, Spring 2018 – Spring 2022. Ph.D. ’22, Doctoral Thesis: Secure, Reproducible And Adaptive Machine Learning In Distributed Systems. Position after graduation: Post-doc, Tsinghua University.
Pei Guo, Spring 2017 – Spring 2021. Ph.D. Doctoral Thesis: Scalable Multivariate Causality Discovery From Large-scale Global Spatiotemporal Climate Data. Position after graduation: Data Scientist, Wyze Labs.
Wenbin Zhang, Fall 2016-Fall 2020. Ph.D. Doctoral Thesis: Learning Fairness and Graph Deep Generation in Dynamic Environments. 1st Position after graduation: Post-doc, Machine Learning Department at Carnegie Mellon University. 2nd Position after graduation: Assistant Professor, Department of Computer Science at Michigan Technological University
Graduated MS Students
Garima Kumari, M.S. ’23. Master Thesis: Distributed Deep Learning Techniques for Remote Sensing Applications
Rohan Salvi, M.S. ’23. Master Thesis: Spatio-temporal Multivariate Weather Data Clustering Using DBScan and K-medoids Methods
Charan Duggirala, M.S. ’23. Master Thesis: Distributed GPU Computing For Deep Learning In Proton Beam Therapy For Cancer Treatment
Supriya Sangondimath, M.S. ’21. Master Thesis: Service-oriented Scalable MODIS Aggregation Using STRATUS Framework
Savio Kay, M.S. ’19, Master Thesis: A Big Data Study on Scientific Dataset Subsampling for Faster Data Aggregation Using Xarray And Dask. Position after graduation: Associate Programmer, Emmes.
Deepak Prakash, M.S. ’19. Master Thesis: Benchmarking of Parallel Climate Data Aggregation in a Distributed Environment. Position after graduation: Data Analyst and Business Intelligence Analyst at PNC Financial Services.
Rishi Sankineni, M.S. ’17, Master Thesis: Parallel Feature Selection of Multiple Class Datasets using Apache Spark. Position after graduation: Data Scientist, Kaiser Permanente.
Sarthak Bhatt, M.S. ’17, Position after graduation: Full Stack Developer, Sparksoft Corporation.
Muthukumar Thevar, M.S. ’17. Master Thesis: The Effect of K-nearest Neighbors Classifier for Intrusion Detection of Streaming Net-flows in Apache Spark Environment.
Sai C. Pallaprolu, M.S. ’17, Master Thesis: Zero-day Attack Identification in Streaming data: Nearest Neighbor Heuristics and Dynamic Semantic Network Generation in the Spark Eco-system.
Collaborators
Dr. Aravind Mohan: Dr. Mohan is currently an Assistant Professor in the Department of Computer Science at McMurry University. Previously, Dr. Mohan was a faculty member at Allegheny College. He completed his Ph.D. in Computer Engineering at Wayne State University in 2017 in the Big Data Research Lab led by Dr. Shiyong Lu. Before that, he worked in the industry as a software engineer. His research focuses on big data management and cloud computing. His broader areas of interest are services computing, online education services, and information retrieval. He has published several research articles in peer-reviewed international conferences, including the IEEE conference on services computing, big data congress, big data, big data computing services and applications, and the ACM SIGIR conference. He is a member of IEEE and ACM.