Hello! 

I'm Mitul !

I'm a Software Engineer and AI researcher passionate about building intelligent systems that solve real-world problems. My interests lie at the intersection of Applied ML, Backend Systems, and Healthcare AI, where I enjoy combining research with practical engineering to create impactful technology.

I recently graduated with a B.Tech (Honours) in CS from KIIT University and, currently working as a Member of Technical Staff at ADP Workforce Suite (WFS) in Hyderabad, India. Earlier, I worked as a Software Engineer Intern at ADP Global Payments & Compliance (GPAC) in Hyderabad, India. Alongside software engineering, I actively pursue research in applied and foundational machine learning, with a focus on developing models that are robust, interpretable, and deployable in real-world environments.

My research journey has been shaped through collaborations with Bio-AI Lab, UiT Norway, where I worked under Dr. Arif Ahmed Sekh (Senior Researcher, Bio-AI Lab) on developing FairMed - XGB (AI in Emergency Medicine, Elsevier), a fairness-aware ML framework to reduce gender bias in critical care prediction systems while preserving clinical performance. 

Previously, I also interned at the Defence Research & Development Organisation under Dr. Sourav Kaity (Scientist - F, Integrated Test Range) to develop a low-latency radar-tracking simulation system, processing live trajectories of airborne objects, specifically missiles. Concurrently, I collaborated with Dr. Somnath Mahato (Project Scientist - III) of the Indian Meteorological Department on Adversarial detection of anomalous Wi-Fi activity through Residual-GANs (ICORT 2025 - Best Paper Award !), Adversarial-Ensemble KAN for enhancing Wi-Fi Indoor localization (Franklin Open, Elsevier) & Enhancing RS satellite performance for indian defence (ICSCSS 2025)

In parallel, over the years since 2022, I worked at the research lab of Dr. Prasant Kumar Pattnaik & Dr. Suneeta Mohanty of KIIT University on multiple research problems involving Hyb-KAN ViT (CVPR 2026 Workshop on ECV), Optimizing ML models through quantization algorithms (Franklin Open, Elsevier),  Adversarial-Ensemble KAN for enhancing Wi-Fi Indoor localization (Franklin Open, Elsevier). 

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I'm fascinated by the future of Agentic AI, foundation models, and AI for healthcare & finance, and I hope to contribute to advancing these technologies through both research and industry.

Outside of work, I enjoy mentoring students interested in AI research, speaking at technical events, travelling, photography, and occasionally challenging friends to a game of chess.

If you're interested in research collaborations, software engineering, or simply discussing AI, I'd be happy to connect..!