I'm an AI Researcher and Engineer, currently a Technical Lead in Cloud Native & Agentic AI at HCLTech, with an M.Tech in Artificial Intelligence from IIT Patna. My background spans machine learning, reinforcement learning, and data science, with a focus on solving real-world problems in finance, agentic AI, and natural language processing from deep learning models for finance to MLOps pipelines for personalized advertising, backed by published research on LLM-based financial compliance and reinforcement learning for trading.
Aditya Bhagat
Education
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Indian Institute of Technology Patna (IIT Patna, IITP)
Master of Technology in Artificial Intelligence
Jul 2024 – Jul 2026, Patna, India -
G H Raisoni College of Engineering, Nagpur (GHRCE)
Bachelor of Technology in Electronics Engineering, Minor in Computer Science and Engineering
Dec 2021 – Jun 2024, Nagpur, India -
Government Polytechnic Nagpur (GP Nagpur)
Diploma in Electrical Engineering
Jul 2018 – Jul 2021, Nagpur, India
Experience
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HCLTech
Technical Lead · Sep 2026 – Present (), Noida, India- CTO & Ecosystem, Cloud Native labs.
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Indian Institute of Technology Patna (IIT Patna)
Teaching Assistant · Jan 2025 – Jun 2026 (), Patna, India- TA for CS 2203: Artificial Intelligence and Lab (Spring 2026).
- TA for CS 431: Big Data Analytics and Lab (Autumn 2025).
- TA for CS 1201: Data Structures and Lab (Spring 2025).
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Visvesvaraya National Institute of Technology Nagpur (VNIT Nagpur)
Research Intern · Jan – Jul 2024 (), Nagpur, India- Published paper in Springer CCIS 2024 on reinforcement learning for stock trading.
- Contributed a forthcoming book chapter on quantum-inspired autonomous driving.
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Visvesvaraya National Institute of Technology Nagpur (VNIT Nagpur)
Summer Research Intern · Jun – Jul 2023 (), Nagpur, India- Developed deep learning models for rainfall–runoff prediction.
- Co-authored IGI Global 2024 book chapter on UAV-based forest fire detection.
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G H Raisoni College of Engineering, Nagpur (GHRCE)
Data Science Intern · Aug – Nov 2022 (), Nagpur, India- Published at IEEE ICCCNT 2023 on sea level prediction using ML models.
Projects
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Aether Marketing System
[GitHub]
AI-powered marketing automation platform- Built an end-to-end MLOps system for personalized ad generation using K-Means and Gemini 2.5 Pro.
- Developed scalable backend with FastAPI, Celery, Redis, and PostgreSQL; integrated CI/CD, Docker, and Kubernetes.
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CuisineInsight Q&A
[GitHub]
Retrieval-augmented restaurant review analysis system- Implemented RAG on 10k+ Yelp reviews using LangChain, Flask, PyTorch, and Ollama.
- Built sentiment analysis (TF-IDF + Logistic Regression, 91% accuracy) with Chroma vector search integration.
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Multi-User PDF Q&A
[GitHub]
Interactive PDF question-answering web application- Developed a Streamlit-based Q&A app using FAISS vector search and Gemini 1.5 Flash API.
- Used Redis for scalable embedding storage and deployed using Docker and Kubernetes.
Publications
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FinRegGuard: Can LLMs Detect Regulatory Evasion? A 100K Adversarial Benchmark for U.S. Financial Law
AI4Law Workshop, International Conference on Machine Learning (ICML), 2026 | Accepted (Proceedings Forthcoming)
Developed a 100K-example adversarial benchmark to evaluate whether large language models can detect regulatory evasion strategies in U.S. financial law, providing a rigorous framework for assessing legal reasoning and compliance capabilities. -
Multi-feature Reinforcement Learning for Financial Market Decision Making
Communications in Computer and Information Science (CCIS), 2025 | Book Chapter
Developed a multi-feature reinforcement learning framework combining candlestick patterns and fundamental metrics with GRU and DQN models to generate profitable trading signals in Indian and U.S. equity markets. DOI -
ML/DL-Based Forest Fire Prediction Using UAV
Advances in Computational Intelligence and Robotics, 2024 | Book Chapter
Designed deep learning models for UAV-based forest fire detection, integrating image and environmental data to improve prediction accuracy and response time. DOI -
Prediction of Global Sea Water Level using Linear Regression and Gradient Descent
14th International Conference on Computing Communication and Networking Technologies (ICCCNT), 2023 | Conference Paper
Developed linear regression models with gradient descent to predict global sea level changes, achieving 30% higher accuracy compared to baseline ML models. DOI
Certifications
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Oracle Cloud GenAI Professional 2025 [View] -
Oracle Cloud Data Science Professional 2025 [View]
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Google Analytics Certification [View] -
NVIDIA End-to-End Data Science [View] -
QuantInsti Options Trading (Python) [View] -
Blockchain and its Applications (NPTEL) [View] -
Compiler Design (NPTEL) [View]
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Air Pollution and Control (NPTEL) [View]
Letters of Recommendation
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Dr. Ashish Tiwari
Assistant Professor, Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology (VNIT), Nagpur, India
[PDF] -
Dr. Pramod V. Walke
Dean Academics, G. H. Raisoni College of Engineering (GHRCE), Nagpur, Maharashtra, India
[PDF] -
Dr. Laxman Thakre
Head of Electronics Engineering Department, G. H. Raisoni College of Engineering (GHRCE), Nagpur, Maharashtra, India
[PDF] -
Dr. Dinesh Padole
Dean of Admissions, G. H. Raisoni College of Engineering (GHRCE), Nagpur, Maharashtra, India
[PDF] -
Dr. Snehlata Dongre
Head of Computer Science and Engineering Department, G. H. Raisoni College of Engineering (GHRCE), Nagpur, Maharashtra, India
[PDF]