Overview

Taslim Murad completed her Ph.D. in the Department of Computer Science at Georgia State University. Her research focuses on Deep Learning, Machine Learning, Bioinformatics, Neuroimaging, and Multimedia Analysis. She specializes in developing representation learning methods for biological sequence data and applying deep learning models to solve complex problems in bioinformatics and medical imaging.

Research Interests

• Representation Learning: Developing efficient embedding methods for biological sequences, including proteins, viruses, and DNA.
• Deep Learning for Bioinformatics: Applying deep learning models to classify and analyze biological sequences, such as SARS-CoV-2 spike sequences and TCR protein sequences.
• Neuroimaging: Using machine learning to analyze neuroimaging data for brain age estimation and neurodegenerative disease detection.
• Multimedia Analysis: Designing deep learning-based methods for video streaming and analytics under resource constraints.

Research Experience

• Graduate Research Assistant
  Georgia State University, Atlanta, GA, USA
  Sep 2019 – May 2024
  Advisor: Dr. Murray Patterson
  • Developed representation learning methods for biological sequence classification.
  • Applied deep learning models to analyze SARS-CoV-2 spike sequences and TCR protein sequences.
  • Contributed to neuroimaging research for brain age estimation and Alzheimer’s disease detection.
• Postdoctoral Research Fellow
  Washington University in St. Louis, St. Louis, MO, USA
  May 2024 – Present
  • Continuing research in neuroimaging and bioinformatics, focusing on advanced machine learning techniques for medical data analysis.

Teaching Experience

• Lab Instructor
  Georgia State University, Atlanta, GA, USA
  Jan 2020 – May 2021
  Courses: Theory Foundation of Computer Science (CSC 2510), Principles of Computer Science (CSC 1301)

• Teaching Assistant
  Georgia State University, Atlanta, GA, USA
  Aug 2019 – Dec 2019
  Course: Computer Networks (CSC 4220)

Selected Publications

• DAO: Dynamic Adaptive Offloading for Video Analytics
  Taslim Murad, A. Nguyen, Z. Yan
  Proceedings of the 30th ACM International Conference on Multimedia, 3017-3025, 2022. DOI

• Spike2Signal: Classifying Coronavirus Spike Sequences with Deep Learning
  Sarwan Ali, Taslim Murad, Prakash Chourasia, Murray Patterson
  2022 IEEE Eighth International Conference on Big Data Computing Service and Applications, 2022. DOI

• Exploring the Potential of GANs in Biological Sequence Analysis
  Taslim Murad, Sarwan Ali, Murray Patterson
  Biology, 12(6), 854, 2023. DOI

• Spike2CGR: An Efficient Method for Spike Sequence Classification Using Chaos Game Representation
  Taslim Murad, Sarwan Ali, Imdad Ullah Khan, Murray Patterson
  Machine Learning, 112(10), 3633-3658, 2023. DOI