[ 01 / About ]
Master's student in Data Science and AI with 4+ years of industrial experience building efficient, scalable AI across product and service companies.
I'm Jai Shankar Krishna Murthy Neelavathi — an AI engineer who likes problems that end in a shipped system, not a slide deck. At Flam I led generative-AI work that placed human subjects photorealistically into new scenes and turned a wall-paint visualiser proof of concept into a £42,500 client contract. At Tata Elxsi I spent three and a half years building for Japanese industrial clients: multi-agent reporting systems, synthetic-data pipelines, natural-language robot control demoed at iREX 2023, and 6D pose estimation for reflective factory parts.
I'm now deepening that practice with an MSc in Data Science and AI at the University of Liverpool (Year in Industry), combining academic rigour — statistics, computational intelligence, AI ethics — with the production instincts of someone who has carried models from literature review to Docker container.
My work has been recognised with the Rising Star and Customer Appreciation awards, an IEEE National Level Best Project Award, and a published paper. The thread through all of it: AI should be responsible, measurable and useful.
[ 01.a / Education ]
Sep 2025 – Expected Sep 2027
University of Liverpool · Liverpool, UK
Relevant modules: Research in CS, Math and Stats for AI, Big Data Analysis for Social Media, Relational Databases, Data Mining and Visualisation, Computational Intelligence, Applied AI.
Aug 2017 – Aug 2021
Visvesvaraya Technological University · India
CGPA 8.40. Final-year project won the IEEE National Level Best Project Award.
[ 01.b / Awards & publication ]
Tata Elxsi — For delivering the 'Natural Language to Robotic Actions' project in record time for the Japanese client's demo at iREX 2023.
Tata Elxsi — In recognition of dedication and problem-solving ability during the first year.
IEEE — Brain Tumor Segmentation model deployed on a 4 GB Jetson Nano — undergraduate final-year project.
Published paper — March 2022. Peer-reviewed research applying deep learning to chest X-ray based COVID-19 detection.
[ 01.c / Frequently asked ]
Generative AI (diffusion models, LLMs, RAG, agentic systems), Computer Vision and NLP — with 4+ years of industry experience productionising AI at Tata Elxsi and Flam, including containerised inference services and GPU cost optimisation.
Yes. He is based in Liverpool, UK, pursuing an MSc in Data Science and AI at the University of Liverpool, and holds the right to work full-time in the UK (post May 2026), including the Year-in-Industry placement window.
≈35% GPU cost reduction on a generative human-placement pipeline, a ≈£42,500 client contract from a paint-visualisation proof of concept, ≈60% faster reporting via a multi-agent tracker, ≈19% project cost savings from synthetic data generation, and ≈80% less manual annotation time from a semi-automated tool.
Email jaishankarkn99@gmail.com, call +44 7818 143535, or connect on LinkedIn. His CV is downloadable from this site.