About Me

I am a PhD candidate in Computer Science in the School of Computing and Augmented Intelligence at Arizona State University. My PhD research is supervised by Professor Dr. Mo Sarwat and Professor Dr. Jia Zou. My research interests lie in the areas of machine learning, big data analytics, geospatial data management, and database systems. My current research focuses on building noble systems for efficient processing and utilization of large scale geospatial and spatio-temporal data with applications to machine learning and deep learning techniques.

I worked as a Research & Development Intern at Wherobots Inc during Spring 2023 and Fall 2023. Before joining Arizona State University, I obtained my Bachelor of Science in Computer Science and Engineering from Chittagong University of Engineering and Technology in 2014. I also worked as a Software Engineer with several IT companies during the period of 2015 to 2018.

Research Interests

Machine Learning, Big Geo-spatial Data analytics, and Database Systems

Recent News

  • [02/05/2024] A vision paper titled “Serving Deep Learning Models from Relational Databases” was accepted in EDBT 2024.
  • [12/23/2023] A research paper titled “Deep Learning with Spatiotemporal Data: A Deep Dive into GeotorchAI” was accepted in ICDE 2024.
  • [08/15/2023] Completed Internship at Wherobots Inc. as a Research & Development Intern.
  • [06/19/2023] Attended ACM SIGMOD 2022, volunteered to organize the conference and presented my work: “A Demonstration of GeoTorchAI: A Spatiotemporal Deep Learning Framework”.
  • [04/24/2023] Received ACM SIGMOD 2023 student travel grant to attend the conference and present a paper. Also, have been selected a volunteer to help organize the conference.
  • [02/26/2023] A demo paper titled “A Demonstration of GeoTorchAI: A Spatiotemporal Deep Learning Framework” was accepted in SIGMOD 2023.
  • [01/09/2023] Started Internship at Wherobots Inc. as a Research & Development Intern.
  • [11/02/2022] Attended ACM SIGSPATIAL 2022, volunteered to organize the conference and presented my work: “GeoTorch: A Spatiotemporal Deep Learning Framework”.
  • [10/12/2022] Received ACM SIGSPATIAL 2022 travel award to attend the conference and present a paper.
  • [09/30/2022] Received ASU GPSA travel grant to attend the conference ACM SIGSPATIAL 2022 and present a paper.
  • [08/22/2022] A short paper titled “GeoTorch: A Spatiotemporal Deep Learning Framework” was accepted in ACM SIGSPATIAL 2022.
  • [06/12/2022] Attended ACM SIGMOD/PODS 2022 conference.
  • [05/10/2022] Attended ICDE 2022 and presented my work: “A Machine Learning-Aware Data Re-partitioning Framework for Spatial Datasets”.
  • [03/23/2022] A research paper titled “A Machine Learning-Aware Data Re-partitioning Framework for Spatial Datasets” was accepted in ICDE 2022.
  • [12/09/2020] A research paper titled “Evaluation of ML Algorithms in Predicting the Next SQL Query from the Future” was accepted in ACM TODS 2021.
  • [04/15/2020] A demo paper titled “Tabula in action: a sampling middleware for interactive geospatial visualization dashboards” was accepted in VLDB 2020.
  • [01/02/2019] A short paper titled “Recurrent Neural Networks for Dynamic User Intent Prediction in Human-Database Interaction” was accepted in EDBT 2019.