Proof of Concept.

Independent R&D Engagement

Collaborated directly with the Founder to execute rapid prototyping cycles. Mandated to architect experimental frameworks testing the viability of Agentic AI and alternative data structures in financial modeling.

• Agentic Financial Interface Engineered a conversational finance engine using LangGraph and React. Implemented autonomous agents capable of retaining context and executing multi-step financial queries.
• Cross-Market Alpha Detection Developed a predictive PoC identifying correlations between prediction markets (Polymarket) and equity indices. Utilized Vector Embeddings and Cosine Similarity to map semantic events to stock price movements.

Research Associate, Trojan Sports Research Lab

Supported the lab’s strategic initiative to secure a partnership with the NFL. Responsible for the data foundation of a commercial Proof-of-Concept (POC) designed to demonstrate analytical value to league stakeholders.

• POC Data Architecture Curated a granular dataset mapping organizational hierarchies across franchises. This data layer served as the backbone for the predictive models used in the final commercial pitch to the NFL.

Research Fellow (Computational Science)

Investigated the intersection of physical systems and deep learning. Analyzed real-time spatio-temporal data from Beijing’s sensor network to model complex pollutant dispersion dynamics.

• Physics-Informed AI Synthesized the academic canon to design a novel forecasting model. Recognized by the institute for proposing PINN-based (Physics-Informed Neural Networks) solutions to improve prediction accuracy in sparse-data environments.

Lead Developer & Contributing Researcher

"Mapping storm surge risk for the Indian east coast using a Tropical Cyclone Surge Potential Index (TCSPI) model."
Co-architected a novel computational framework for real-time disaster risk assessment. Transformed theoretical hydrodynamics into a deployable digital asset for coastal management.

• Algorithmic Efficiency Engineered the interactive application for the TCSPI model, achieving a 75× reduction in compute time compared to traditional physics-based simulations while maintaining 99% model fidelity.
• Geospatial Intelligence Vectorized the complete Indian East Coast shoreline (LineString methodology) to enable precise approach-angle calculations, creating a reusable data standard for future risk zone analysis.
• Operational Impact Eliminated the dependency on synthetic track generation, enabling rapid "what-if" scenario planning for disaster response teams.

Research Associate (Economics & Strategy)

Led the "Visibility and Firm Productivity" initiative, a macro-economic study analyzing the invisible cost of environmental factors on corporate output.

• Workflow Orchestration Designed and executed end-to-end data pipelines to process granular geographic visibility data, completing the project ahead of schedule and creating the empirical basis for a new firm productivity framework.
• Invited Delegate (ISB Conference) Selected by the Principal Investigator to represent the research initiative at the ISB Accounting & Research Conference. Engaged with global academic leadership as a direct recognition of the project's accelerated delivery and strategic merit.