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Multi-disciplinary researcher and engineer at the intersection of data science, machine learning, and health technology. I build systems that turn complex health data into meaningful, personalised insights — and I'm deeply interested in the theoretical foundations that make intelligent systems trustworthy and generalisable. My background spans Computer Engineering, Finance, and Data Science, giving me a systems-level view that informs how I approach problems — from autonomous vehicle localisation to wellness personalisation engines. Research interests
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At Healf — designing data and ML infrastructure that powers evidence-backed wellness recommendations:
- Evidence Graph — scalable ML system connecting products to mechanisms, biomarker outcomes, and research-grade claims
- Wellness Personalisation Engine — algorithms integrating biomarker, behavioural, and preference data with quantifiable confidence scores
- Healf Outcomes Program — real-world cohort studies measuring pre/post biomarker shifts to establish the "Healf Recommended" standard
- Analytics Pipelines — unified health, commerce, and marketing data models across Snowflake + dbt
| Degree | Institution | Period | Highlights |
|---|---|---|---|
| MSc Data Science | University of Southampton, England | 2023 – 2024 | Dissertation: 77/100 · Presidential International Scholarship |
| MBA — Finance | Savitribai Phule Pune University, India | 2020 – 2022 | Business Analytics · Quantitative Techniques · MIS |
| B.E. Computer Engineering | Savitribai Phule Pune University, India | 2016 – 2020 | ML · AI · Cloud Computing · HPC |
| Role | Company | Period | Location |
|---|---|---|---|
| Analytics Engineer | Healf | Nov 2025 – Present | London, UK |
| Healthcare Specialist | The Boots Group | Feb 2025 – Nov 2025 | UK |
| Exam Invigilator | University of Southampton | Dec 2024 – Present | UK |
| Associate Consultant | Infosys | Jun 2022 – Aug 2023 | India |
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MSc Dissertation Localisation of Autonomous Vehicles using LiDAR Sensor University of Southampton · 77/100 Dr. Daniel Clark & Dr. Luis-Daniel Ibáñez Novel mathematical model with derivative analysis reducing localisation errors by 95% over K-Means, ICP, and Convex Hull on KITTI-CARLA. |
Publication — Springer (2021) Blockchain-Based Grievance Management System Advances in Intelligent Systems and Computing
DOI: Decentralised Hyperledger Fabric solution with hierarchical auto-escalation for transparent grievance handling. |
Patent — India (2019) Grievance Redressal System Pub. No. 38/2019 · 20 Sep 2019 Classification: G06Q 10/00, G06Q 50/00 Blockchain-powered, tamper-proof automated platform with multi-level accountability and immutable audit trails. |
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LiDAR AV Localisation — MSc Dissertation
95% reduction in localisation error vs standard baselines. GPS-free autonomous navigation on KITTI-CARLA.
Hidden Markov Models — Stock Prediction
Probabilistic framework for bullish, bearish and volatile market regime detection from time-series data.
Forest Fire Simulation
Agent-based percolation model with real-time sensitivity analysis across density, wind and tree types.
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Blockchain Grievance Redressal — Published + Patented
4-tier system, 40% improvement in data security. REST API with Flask + React + PostgreSQL.
UAV Quadcopter with ML
Autonomous drone with real-time object detection, +20% tracking accuracy, +30% flight performance.
Gravitational Wave Analysis
Spark DAG framework with RF + MLP classifiers for astrophysical event lineage tracking.
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Languages
ML & AI
Data Engineering
Cloud & DevOps
"Ketan demonstrated exceptional dedication and intellectual capacity throughout the MSc programme. His dissertation earned an impressive mark of 77/100, reflecting his deep understanding of the subject matter and ability to engage with complex technical concepts. He was also one of 25 recipients of the Southampton Presidential International Scholarship — a competitive award for academically excellent international students."
— Prof. Luis-Daniel Ibáñez, Programme Lead MSc Data Science · University of Southampton
