Career Summary

I am an aspiring AI and Computer Science researcher dedicated to developing trustworthy, explainable, and human-centered AI systems for healthcare and clinical decision support.

My research builds reliable, interpretable, and multimodal machine learning systems that advance real-world medical intelligence and improve healthcare accessibility — clinically grounded AI integrating explainability, retrieval-augmented reasoning, multimodal learning, and robust evaluation for safer, more transparent, and human-centered healthcare. To reach this goal, I am developing myself along three interconnected directions:

1. Retrieval-Augmented Clinical AI, to design systems that integrate external medical knowledge with multimodal reasoning for reliable diagnostic and monitoring tasks.
2. Explainable and Interpretable ML, to build prediction models whose decisions are transparent, locally interpretable, and robust under distribution shift in healthcare settings.
3. Multimodal and Vision–Language Reasoning, to advance models that jointly reason over text, image, motion, and tabular signals for clinical and human-centered applications, especially in low-resource and resource-constrained settings.

I am currently a Research Associate at ElITE Research Lab LLC (New York, USA / Remote), where I design and evaluate retrieval-augmented multimodal systems for&ndash clinical decision support. I previously served as a Research Assistant at Multimedia University (Malaysia), working on applied AI research, dataset construction, and reproducible evaluation pipelines, and as a Researcher at American International University-Bangladesh, building interpretable ML models for clinical prediction tasks. I collaborate with Ts. Dr. Md. Jakir Hossen and Dr. Liew Tze Hui (Multimedia University) on retrieval-augmented clinical AI and multimodal vision–language reasoning; Prof. Dr. M. Firoz Mridha (AIUB) on explainable ML and LLM-assisted multimodal programming; Prof. Md. Kishor Morol (Cornell University) on multimodal clinical AI and low-resource NLP; and Dr. Salah Uddin Ahmed (USN / NTNU, Norway) on LLM-assisted programming and human-centered AI. I also serve as Product Manager, AI Systems at APEX DMIT Ltd., translating ML research into deployable AI systems.

My research has been published in venues such as ICMLA, HCII, ICCIT, IJPHS, MECON, ICICML, ICHIH, AIBDF, ICON-SONICS, and ICHORA. I serve as a peer reviewer for PLOS ONE, IEEE SMC, ICONIP, and IEEE EDUCON, and as a judge for the Three Minute Thesis Competition. I am a quick learner and highly adaptable, able to lead end-to-end research workflows and translate research into deployable systems. I enjoy exploring new topics, sharing knowledge, honing skills, and pushing my limits.

Feel free to email me (rajandasgupta.me at gmail dot com) if you're interested in collaboration or discussing research!

News and Updates

Publication Stats

Selected Publications

• BRAINS: A Retrieval-Augmented System for Alzheimer’s Detection and Monitoring
  Rajan Das Gupta, Md Kishor Morol, Nafiz Fahad, Md Tanzib Hosain, S. B. Z. Choya, Md Jakir Hossen
  ICMLA 2025 — 24th International Conference on Machine Learning and Applications [PDF]

• HyCARD-Net: A Synergistic Hybrid Intelligence Framework for Cardiovascular Disease Diagnosis
  Rajan Das Gupta, Xiaobin Wu, Xun Liu, Jiaqi He
  ICICML 2025 — 4th Intl. Conf. on Image Processing, Computer Vision and Machine Learning [PDF]

• Locally Interpretable Surrogate-Guided Neural Framework for Multi-Class Liver Cirrhosis Staging
  Rajan Das Gupta, Xiaobin Wu, Xun Liu, Jiaqi He
  ICHIH 2025 — 4th Intl. Conf. on Health Big Data and Intelligent Healthcare

• Multimodal Programming in Computer Science with Interactive Assistance Powered by Large Language Model
  Rajan Das Gupta, Md. Tanzib Hosain, M. Firoz Mridha, Salah Uddin Ahmed
  HCII 2025 — Human-Computer Interaction International, pp. 59–69 [PDF]

• ViMoNet: A Multimodal Vision–Language Framework for Human Behavior Understanding from Motion and Video
  Rajan Das Gupta, Md Yeasin Rahat, Nafiz Fahad, A. Ahmed, Liew Tze Hui
  AIBDF 2025 — 5th Intl. Symposium on AI and Big Data [PDF]

• A Deep Learning and Machine Learning Approach to Predict Neonatal Death in the Context of Sao Paulo
  M. Raihan, P. K. Saha, Rajan Das Gupta, A. Z. M. Kabir, A. A. Tamanna, et al.
  IJPHS 2025 — International Journal of Public Health Science [PDF]

• VLAgeBench: Benchmarking Large Vision-Language Models for Zero-Shot Human Age Estimation
  R. H. Sajib, M. K. Morol, Rajan Das Gupta, M. S. Mahmood, S. S. Das
  ICCIT 2026 — 28th Intl. Conf. on Computer and Information Technology [PDF]

View Publications and Ongoing Works →

Research Experiences

• Research Associate, ElITE Research Lab LLC | New York, USA / Remote | Oct 2024 – Present
• Research Assistant, Multimedia University | Malaysia / Remote | Sept 2024 – Aug 2025
• Researcher, American International University-Bangladesh | Dhaka, Bangladesh | Oct 2023 – Sept 2024
• Lecturer, PLAYPEN Education | Bangladesh | September 2023 – October 2024
• Product Manager, AI Systems, APEX DMIT Ltd. | Bangladesh | Oct 2024 – Present
• Project Coordinator and UX Lead, Olivine Limited | Bangladesh | Oct 2021 – July 2023

Technical Skills

• Programming Languages: Python (Advanced), C, C++, MATLAB, R, SQL
• DS & ML Tools (Python): NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, TensorFlow, PyTorch, PyCaret, LangChain, VLLM, Pydantic
• Data Science Techniques: EDA, Experimental Design, Hypothesis Testing, Sampling, Statistical Inference, Data-driven Decision Making
• Machine Learning Techniques: Statistical ML Methods, Deep Learning, NLP, Computer Vision, Graph Neural Networks (GNNs), GFlowNets, Flow Matching, Diffusion Models, RL and Reasoning in LLMs, Self-Verification, Uncertainty, Agentic Decision-Making, AI Reasoning, RAG, AI Agent Environments and Systems, and Reward-Based RL Fine-Tuning
• Biomedical AI & Clinical Applications: Molecular Properties, Interaction, Dynamics, Optimization and Simulation; De Novo Molecule Design/Dynamics with GNNs, RL/Reward/Energy-Guided Modeling, Flow Matching, Diffusion; AI-based Drug Discovery and Genomics; Single Cells and Multi-Omics and AI; Knowledge Graphs in Biomedicine; Bio/Medical/Clinical Agents and NLP Applications; Lab Automation (Opentrons and Ginkgo); Analysis and Modeling with Benchling
• AI Safety, Governance, and Responsible Development: Alignment, value-sensitive design, interpretability, risk assessment, governance frameworks, policy and regulatory compliance, auditability, model monitoring, and responsible deployment
• Data Analysis & Visualization: MS Excel, Power BI, Tableau, SAS
• Interdisciplinary Research: AI for Good, multilinguality and multicultural alignment, accessibility design in low-resource settings, fairness and unbiased representation in clinical and social contexts, human factors and ergonomics evaluation, integrating local knowledge and cultural values into AI systems, and sociotechnical risk mitigation for mental-health and clinical deployments
• Human-Computer Interaction (HCI): Clinical and patient-centric AI workflows, LLM customization and prompt interface design, scalable survey and user-study pipelines, data collection and annotation with domain experts, UI and UX frameworks for trust and comprehension, participatory design with healthcare stakeholders, and evaluation methods that capture cognitive load, usability, safety, and user experience in high-risk environments
• Automation & Productivity: MS Word, PowerPoint, Excel Automation; Google Sheets Scripting; Python-based Automation; Adobe Photoshop and Illustrator
• Other Tools & Skills: GitHub, VS Code, Azure, AnyScale, Replit, Colab, Kaggle, Parallel & Distributed Computing, Product & Project Management, Strategic Planning

Academic Services

• Conference Program Committee & Reviewer
  • AI/ML: IEEE ICTAI 2026 (International Conference on Tools with Artificial Intelligence)
• Conference & Journal Reviewer
  • AI/ML & Neural Computing: ICONIP, IEEE SMC
  • Engineering Education: IEEE EDUCON
  • HCI/HAI: HCII 2025 (Human-Computer Interaction International)
  • Journals: PLOS ONE, IJPHS (International Journal of Public Health Science)
  Total conference or journal papers reviewed: 20+
• Judge
  • Three Minute Thesis Competition, 2025

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