Curriculum Vitae
Education
- M.S. in Computer Science, New York University (Aug 2025 – Expected May 2027)
- Coursework: Artificial Intelligence, Data Science, Math-focused Deep Learning, Advanced Deep Learning Applications
- Graduate Research Assistant, COPHEE Lab, under Prof. Vedant Das Swain
- Teaching Assistant, Deep Learning (DS-GA 1008), Fall 2025 and Fall 2026, under Prof. Yann LeCun and Prof. Alfredo Canziani
- B.Tech in Computer Science (AI and ML), SRM Institute of Science and Technology (2021 – 2025)
- Research supervised by Prof. Alice Nithya
- Exchange Program, Financial Management, Tamkang University, Taiwan (Mar 2022 – Jun 2022)
Research Experience
- Incoming ML Research Member, Frisson Labs, California (Aug 2026 – Present)
- Research on world models applied to voice and gaming
- Incoming AI Safety Research Fellow, Iliad Intensive, California (Aug 2026 – Present)
- Agent foundations, modular systems, and world models
- AI Research Engineer, Stealth AI Lab, New York (Jun 2026 – Aug 2026)
- Enterprise world models and world-model interpretability
- Graduate Research Assistant, NYU COPHEE Lab, NYU Tandon (Jan 2026 – Present)
- Thesis with Prof. Vedant Das Swain on interpretable predictive modeling for high-dimensional behavior-log data
- Methods: factor-level attribution, counterfactual analysis, and human-auditable internal representations
- Application domain: burnout risk estimated from workplace signals (meetings, email, collaboration traces), with models designed to be audited and reasoned about by a person rather than to automate a decision
- Core contributor to World-Model-Lens, a capability-typed mechanistic interpretability toolkit for world models
- Research Contributor, University of Melbourne DISNET Lab (Oct 2024 – Jan 2025)
- V2G bidirectional-charging model matching vehicle source and destination pairs against live-traffic data on Open Maps, under Prof. Adel Toosi
- Research Contributor, University College London (Jul 2024 – Oct 2024)
- End-to-end RAG application for querying insurance terms and conditions
- Hybrid semantic search and hallucination-reduction pipelines over 1TB+ text corpora
- Research Intern, University College London, under Prof. Philip Treleaven (May 2024 – Aug 2024)
- Practical implementation of the Venture Scientists paper, mentored by Andy Pardoe
- Transformer-driven RAG framework for insurance-claim analysis
- Internal whitepaper on LLM interpretability, later adopted for internal policy-recommendation systems
- Project Program, AI and Machine Learning, University of Oxford, under Pramit Saha (Mar 2024 – May 2024)
- Parameter-efficient fine-tuning of large language models for text generation (LoRA, adapter layers, prompt tuning)
- Project Program, Competitive Intelligence for Startups, London Business School, under Atul Banerjee (Mar 2024 – May 2024)
- Entry-to-market strategy, product-market fit assessment, valuation analysis
Industry Experience
- Co-Founder, HydroMind (Dec 2022 – May 2025). Acquired by 6th Element Inc.
- Research, consulting, and product design; bootstrapped
- Scaled and sold ModVPN; grew the team to 18
- Strategic partnerships with AWS, Elastic, and Microsoft for Startups; ARR $120K
- Deep Learning Engineer, HydroMind, Chennai (Dec 2022 – Feb 2024)
- Full-time engineering across the consulting-to-product transition
- Product Development Intern, Informed.AI, United Kingdom (Jun 2024 – Dec 2024)
- Post-graduate internship and MSc-project matching platform with Fraser McKenzie of Wisdom Works Group, under Prof. Andy Pardoe
- Transformer-based candidate–job semantic matching (+46% alignment accuracy)
- FastAPI and PostgreSQL backend serving 200+ concurrent users at 99.9% uptime
- Caching and load-balancing reduced query latency by 42%
- Software Engineering Fellow, Headstarter AI (Jul 2024 – Sep 2024)
- Five AI applications and APIs using Next.js, OpenAI, Pinecone, Stripe
- Led a five-person team on microservice architectures with CI/CD
- Mentored by engineers from Amazon, Capital One, and Bloomberg
- Machine Learning Intern, National Institute of Technology Karnataka (Jan 2024 – Feb 2024)
- ML models across 1,000+ IoT sensors on WEMOS LoLin32, WEMOS D1 MINI ESP32, and ESP32 Dev modules (+27% edge prediction accuracy, −18% inference delay)
- End-to-end embedded ML pipelines with model compression and dynamic quantization
- Drift-monitoring dashboards (+23% anomaly detection)
- Lens Creator and Part-time Developer, Snap Inc. (Jan 2022 – Feb 2024)
- Published two AR/VR and AI-based Lens Correctors
- Real-time object-tracking pipeline at sub-10ms latency, serving 1M+ daily interactions
- TensorRT-optimized low-light segmentation (+48% accuracy)
- Transformer-based image filters shipped via Snap Lens Studio (+37% feature adoption)
Publications
Google Scholar · 86 citations · h-index 5 · i10-index 5
Teaching
- Deep Learning (NYU Courant, DS-GA 1008), Fall 2025. Teaching Assistant to Prof. Yann LeCun and Prof. Alfredo Canziani.
- Deep Learning (NYU Courant, DS-GA 1008), Fall 2026. Graduate Student Assistant to Prof. Yann LeCun and Prof. Alfredo Canziani.
- Applied Research in Discrete Optimization (NYU Tandon, IE-GY 9113A), Fall 2026. Course Assistant with Prof. Kimberly Villalobos Carballo.
- Forecasting, Modeling, and Future AI (Lens Academy), Fall 2026. Instructor. Cohort of ~20.
Honors and Awards
- iCan Research Summit 2024, Scholarship Awardee
- Merit Scholarship, SRMIST
- Best Entrepreneur Award (2025), HydroMind (acquired by 6th Element Inc)
- Best Project Award, TechKnow 2021
Selected Certifications
- Deep Learning
- SAR Data Processing and its Application with Special Emphasis on RISAT-1A / EOS-4
Service
- Board Member and Research Member, Enactus SRM (May 2022 – Sep 2025)
- Mentor and Advisor, International Society for Learning and Empowerment, Chennai (Nov 2023 – May 2024)
- Global Member, Internet Society
Skills
- Research Areas. Agent Foundations, World Modelling, Mechanistic Interpretability, AI Safety.
- Methods. Causal tracing, activation patching, circuit extraction, probing, PEFT (LoRA, adapter layers, prompt tuning), SHAP and LIME, OOD detection.
- ML Frameworks. PyTorch, Hugging Face Transformers, scikit-learn.
- Languages. Python (primary), C++, JavaScript / TypeScript, SQL.
- Systems. FastAPI, PostgreSQL, FAISS, Docker, AWS, Git.