Dhurba Baral
Graduate Student, MS in Computer Science
University of Cincinnati
Cincinnati, OH, USA
I am a Computer Science graduate student at the University of Cincinnati pursuing an MS in Computer Science. I am currently doing research under the supervision of Jarek Meller, PhD, focusing on Computational Biology, where I apply deep learning to problems in genomics and drug discovery, including genotype–phenotype analysis using Single Nucleotide Polymorphisms (SNPs) and predicting drug–target interactions. I have more than two years of professional experience in machine learning, data engineering, and LLM-based applications, including my works in graph-based reasoning and developing scalable ML workflows.
Education
MS in Computer Science
University of Cincinnati
Bechelor's in Computer Engineering
Tribhuvan University
Research Interests
- Computational Genomics, genotype–phenotype analysis
- Computational Molecular Biology
- Applications of AI in drug discovery
Experience
Student Research Associate (Part Time)
Meller Lab, College of Medicine, University of Cincinnati
Supervisor: Jarek Meller, PhD
- Investigating genotype–phenotype relationships using Single Nucleotide Polymorphisms (SNPs).
- Developing deep learning approaches for Drug–Target Interaction (DTI) prediction to accelerate drug discovery.
Machine Learning Engineer
TAI, Inc.
Responsibilities:
- Fine-tuned BERT for document processing and implemented Neo4j to model data as a graph for representing and querying complex relationships between data entities.
- Fine-tuned Large Language Models (e.g., Llama and GPT) using Low-Rank Adaptation (LoRA) and quantization, and implemented Retrieval Augmented Generation (RAG) for building customer-facing chat bots.
- Implemented ML solutions using AWS SageMaker for end-to-end model training and deployment.
- Implemented CI/CD pipelines using Jenkins, writing Groovy scripts to automate build, test, and deployment workflows. Leveraged container-based technologies such as Docker to enable simplified, scalable, and reproducible production deployments.
AI Fellow
AI Fellowship 2023, Fusemachines, Nepal
Coursework: Regression, Classification, Clustering, and Arttificial Neural Networks, Recurrent Neural Networks, Transformers, and more.
Python and AI/ML Mentor
iCES (Innovative Computer Engineering Students’ Society), Pashchimanchal Campus, Tribhuvan University
Participated as Python and AI/ML Mentor in a month-long workshop on Machine Learning and Deep Learning forbachelor students.
Modules taught: Linear Regression, Logistic Regression, Naïve Bayes Classifier, Natural Language Processing (RNN, GRU, LSTM)
Hackathon Winner
Deltathon, Delta 3.0, Purwanchal Campus, Tribhuvan University
Built an AI-based system for detecting bees, monitoring their behavior and health status, and suggesting possible solutions to the detected problems directly to farmers.
Won the Best Hardware Project Award in the hackathon.
Tech Used: YOLOv5 for object detection module integrated with Raspberry Pi and Pi Camera, Convolutional Neural Networks (CNNs) for image classification
Machine Learning Instructor
iCES (Innovative Computer Engineering Students’ Society), Pashchimanchal Campus, Tribhuvan University
Participated as an ML instructor in a three-day workshop on Machine Learning and NLP.
Modules taught: Regression (Linear, Polynomial, Random Forest Regressor), Natural Language Processing (RNN, GRU, LSTM)
Participant: Jenesys 2016 Japan (Theme: Energy)
Japan International Cooperation Center (JICE)
Participated in JENESYS 2016 program and studied cutting-edge technologies used in Japan for harnessing energy from various sources.