About Me

I am Prakash Chourasia, Ph.D Graduate student advised by Dr. Murray Patterson at the Department of Computer Science at Georgia State University.

My research interest are in the fields of Machine Learning, Artificial Intelligence, Data Mining, Federated Learning, Representation learning, Kernel methods, Algorithms, Bioinformatics, Drug Discovery, and Health data. My current research focuses on developing ML/AI techniques in the field of bioinformatics.

I am an aspiring Research Professional, well equipped with practical and innovative solutions. I am a staunch believer that diligence and determination with a focused goal are necessary for the long run.

Previously, I earned my Masters Degree in Computer Science from Georgia State University in 2014-16. I have 5+ years of experience in Software/IT Industry. I worked at Amerisave Mortgage Corporation. and Incomm as a Software Engineer. I received my Bachelors of Engineering in Information Technology from Rajiv Gandhi Technical University, Bhopal, India.

Research

My main areas of interest are in the fields of Machine Learning, Artificial Intelligence, Data Mining, Federated Learning, Representation learning, Kernel methods, Algorithms, Bioinformatics, Drug Discovery, and Health data. My current research focuses on developing ML/AI techniques in the field of bioinformatics. Broadly, I'm interested in Artificial Intelligence, Machine Learning, Drug Discovery and Federated Learning.

Publications -

Conference Papers

1. Sarwan Ali, Haris Mansoor, Prakash Chourasia, Yasir Ali, and Murray Patterson.``Gaussian Beltrami-Klein Model for Protein Sequence Classification: A Hyperbolic Approach" ISBRA 2024 (preprint)
2. Sarwan Ali, Madiha Shabbir, Haris Mansoor, Prakash Chourasia and Murray Patterson. "Elliptic Geometry-Based Kernel Matrix for Improved Biological Sequence Classification" IEEE WCCI / IJCNN 2024 (preprint) "A rank conference"
3. Sarwan Ali, Tamkanat Ali, Prakash Chourasia, and Murray Patterson."A Universal Non-Parametric Approach For Improved Molecular Sequence Analysis" PAKDD 2024 (preprint) "A rank conference"
4. Zahra Tayebi, Sarwan Ali, Prakash Chourasia, Taslim Murad, and Murray Patterson. "T Cell Receptor Protein Sequences and Sparse Coding: A Novel Approach to Cancer Classification." ICONIP (2023), "A rank conference" [PDF]
5. Prakash Chourasia, Taslim Murad, Zahra Tayebi, Sarwan Ali, and Murray Patterson. ``Laws of Federated Learning for Bioinformatics" The International Conference on Information Management and Big Data (SIMBiG) 2023 "Best Paper Award" .
6. Sarwan Ali, Prakash Chourasia, and Murray Patterson.``Expanding Chemical Representation with k-mers and Fragment-based Fingerprints for Molecular Fingerprinting" The International Conference on Information Management and Big Data (SIMBiG) 2023
7. Prakash Chourasia, Taslim Murad, Sarwan Ali, and Murray Patterson. "Enhancing t-SNE Performance for Biological Sequencing Data through Kernel Selection." International Symposium on Bioinformatics Research and Applications, (ISBRA) 2023.
8. Sarwan Ali, Prakash Chourasia and Murray Patterson. "PDB2Vec: Using 3D Structural Information For Improved Protein Analysis" International Symposium on Bioinformatics Research and Applications, (ISBRA) 2023.
9. Sarwan Ali, Haris Mansoor, Prakash Chourasia and Murray Patterson. "Hist2Vec: Kernel-Based Embeddings for Biological Sequence Classification." International Symposium on Bioinformatics Research and Applications, (ISBRA) 2023.
10. Prakash Chourasia, Zahra Tayebi, Sarwan Ali, and Murray Patterson. ''Empowering Pandemic Response with Federated Learning for Protein Sequence Data Analysis." In 2023 International Joint Conference on Neural Networks (IJCNN), pp. 01-08. IEEE, 2023, "A rank conference" [PDF] [Slides]
11. Sarwan Ali, Prakash Chourasia, and Murray Patterson. ''When Biology has Chemistry: Solubility And Drug Subcategory Prediction using SMILES Strings." International Conference on Learning Representation (ICLR), 2023, ``A* rank conference" [PDF]
12. Ali, Sarwan, Babatunde Bello, Prakash Chourasia, Ria Thazhe Punathil, Pin-Yu Chen, Imdad Ullah Khan, and Murray Patterson. ``Virus2Vec: Viral Sequence Classification Using Machine Learning." Conference on Health, Inference, and Learning (CHIL 2023), ``Selected for Oral presentation (12\% acceptance rate)" [PDF] [Slides]
13. Taslim Murad*, Prakash Chourasia*, Sarwan Ali*, and Murray Patterson. ``Hashing2vec: Fast embedding generation for sars-cov-2 spike sequence classification." In Asian Conference on Machine Learning (ACML 2023), pp. 754-769, 2023. (32\% acceptance rate) *Equal Contribution [PDF]
14. Prakash Chourasia, Sarwan Ali, Murray Patterson.``Effect of Informative Initialization on the Quality of t-SNE For Biological Sequences" IEEE BigData 2022. (18.6\% acceptance rate) [PDF] [Slides]
15. Sarwan Ali, Taslim Murad, Prakash Chourasia and Murray Patterson. ``Spike2Signal: Classifying Coronavirus Spike Sequences with Deep Learning". In the IEEE Eight International Conference on Big Data Computing Service and Applications (Big Data Service) 2022.
16. Prakash Chourasia, Sarwan Ali, Simone Ciccolella, Gianluca Della Vedova, and Murray Patterson. `` Clustering SARS-CoV-2 variants from raw high-throughput sequencing read data". In the 11th International Conference on Computational Advances in Bio and medical Sciences, ICCABS (2021).

Journals

1. Prakash Chourasia, Sarwan Ali, Simone Ciccolella, Gianluca Della Vedova, and Murray Patterson. ``Reads2vec: Efficient embedding of raw high-throughput sequencing reads data." Journal of Computational Biology 30, no. 4 (2023): 469-491 Impact Factor: 1.7 [PDF]
2. Sarwan Ali, Prakash Chourasia, Zahra Tayebi, Babatunde Bello, and Murray Patterson. "ViralVectors: Compact and Scalable Alignment-free Virome Feature Generation" Medical \& Biological Engineering \& Computing 2023 Impact Factor: 3.2 [PDF]
3. Sarwan Ali, Babatunde Bello, Prakash Chourasia, Ria Thazhe Punathil, Yijing Zhou, and Murray Patterson. ``PWM2Vec: An Efficient Embedding Approach for Viral Host Specification from Coronavirus Spike Sequences." MDPI Biology (2022). Impact Factor: 5.07
4. Sarwan Ali, Prakash Chourasia, and Murray Patterson."When Protein Structure Embedding Meets Large Language Models" MDPI Genes Impact Factor: 3.5
5. Sarwan Ali, Prakash Chourasia, and Murray Patterson."From PDB Files to Protein Features: A Comparative Analysis of PDB Bind and STCRDAB datasets" MDPI Algorithms for Natural Computing Models Impact Factor: 2.3

Education

Honours and Awards

Molecular Basis of Disease (MBD) Ph.D. Fellowship (4 years funding for Ph.D.)		2023
Student Travel Award [ICDM 2023, [IJCNN 2023], [ICLR 2023]]		2023
Graduate Research Assistantship: Fully funded scholarship for Ph.D. studies		2021
Home Depot HACKATHON Winning team - 3rd Prize		2016
President Award for Boy Scouts - Eagle Scout (By Dr. APJ Abdul Kalam, Former President of India)		2007

Teaching Experience

Services

• Organizing committee                (XAI Section of WCCI 2024)
• Conference/Journal Reviewer           (IJCNN 2024, ACML 2023, ISBRA 2023)

Teaching Experience

Teaching Fellow

CSC 1302: Principles of Computer Science II Worked as instructor for a class of 150 students

Spring 2022

Graduate Teaching Assistant

CSC 1301: Python Programming		[Hossein Saghaeiannejad Esfahani]		Spring 2024
CSC 4370 Web Programming		[Louis Henry]		Spring, Summer, Fall 2023
CSC 3320: System-Level Programming		[Michael Weeks]		Fall 2022
CSC 3210: Computer Org and Programming		[Xucan Chen]		Fall 2021

Work Experience

News

• March, 2024: Our paper (Elliptic Geometry-Based Kernel Matrix for Improved Biological Sequence Classification) got accepted for publication at IEEE World Congress on Computational Intelligence (IEEE WCCI 2024)
• January, 2024: Our papers "A Universal Non-Parametric Approach For Improved Molecular Sequence Analysis" got accepted for publication at Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)