Overview

Sarwan Ali is a passionate researcher and comppleted his Ph.D. in Computer Science at Georgia State University, Atlanta, Georgia. His research interests lie in the areas of Deep Learning, Machine Learning, Bioinformatics, Data Mining, Artificial Intelligence, Algorithms, and Combinatorial Optimization.

Research Experience

• Graduate Research Assistant
  Georgia State University, Atlanta, GA, USA
  Jan 2021 – Present
  Advisor: Dr. Murray Patterson

• Research Specialist, Biomedical Informatics
  Emory University, Atlanta, GA, USA
  June 2024 – October 2024
  Advisor: Dr. Selen Bozkurt

• Visiting Research Scientist, Bioinformatics
  Boston College, Boston, MA, USA
  Aug 2022 – Dec 2022
  Advisor: Dr. Jose Bento

Teaching

• Lecturer
  Georgia State University, Atlanta, GA, USA
  Course: CSC 4850/6850 Introduction to Machine Learning

Recent Publications

• November 2024: Paper MIK: Modified Isolation Kernel for Biological Sequence Visualization, Classification, and Clustering accepted at Machine Learning for Health Symposium (ML4H).
• October 2024: Paper DANCE: Deep Learning-Assisted Analysis of Protein Sequences Using Chaos Enhanced Kaleidoscopic Images accepted at IEEE Big Data Conference (Acceptance Rate: 19.7%).
• September 2024: 3 papers accepted at International Conference on Information Management and Big Data (SimBig):
  1. Preserving Hidden Hierarchical Structure: Poincaré Distance for Enhanced Genomic Sequence Analysis
  2. EPIC: Enhancing Privacy through Iterative Collaboration
  3. Computing Gram Matrix for SMILES Strings using RDKFingerprint and Sinkhorn-Knopp Algorithm
• September 2024: Paper Elliptic Geometry-Based Kernel Matrix for Improved Biological Sequence Classification accepted at Elsevier Knowledge-Based Systems (KBS) (Impact Factor: 7.2).
• August 2024: 2 papers accepted at International Conference on Neural Information Processing (ICONIP):
  1. DeepPWM-BindingNet: Unleashing Binding Prediction with Combined Sequence and PWM Features
  2. Advancing Protein-DNA Binding Site Prediction: Integrating Sequence Models and Machine Learning Classifiers
• June 2024: Paper Molecular Sequence Classification Using Efficient Kernel-Based Embedding accepted at Elsevier Information Sciences (Impact Factor: 8.1).
• June 2024: Paper CAMP: A Context-Aware Cricket Players Performance Metric accepted at Journal of the Operational Research Society.
• May 2024: Paper Gaussian Beltrami-Klein Model for Protein Sequence Classification: A Hyperbolic Approach accepted at International Symposium on Bioinformatics Research and Applications (ISBRA).
• April 2024: Paper From PDB Files to Protein Features: A Comparative Analysis of PDB Bind and STCRDAB Datasets accepted at Springer Medical & Biological Engineering & Computing (MBEC).
• March 2024: Awarded the Graduate Research Award for the Year 2023 at Georgia State University.
• March 2024: Paper SsAG: Summarization and Sparsification of Attributed Graphs accepted at ACM Transactions on Knowledge Discovery from Data (TKDD).
• January 2024: 2 papers accepted at Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD):
  1. A Universal Non-Parametric Approach for Improved Molecular Sequence Analysis
  2. Weighted Chaos Game Representation for Molecular Sequence Classification
• January 2024: Paper PseAAC2Vec Protein Encoding for TCR Protein Sequence Classification accepted at Elsevier Computers in Biology and Medicine (CIBM) (Impact Factor: 7.7).