Selected Work

Projects that
move the needle.

Every project starts with a system problem. Every solution is measured by commercial impact.

Presentation on Biochar Market Growth
Impact Accounting | Environmental Externalities | Corporate Sustainability

Value Balancing Alliance (VBA) Capstone

Extending the VBA–Deloitte carbon valuation framework to the full set of environmental impact drivers — water, waste, air and water pollution, land use — to estimate short- and long-term internalization rates and the forces driving externalities to become internalities.

Program: Master in Applied Economics, IE University — Capstone Project 2025/2026

The Context

Environmental externalities are recognized as one of humanity's core challenges. Traditionally treated as "outside" the business system, many are increasingly being internalized through regulation, investor pressure, and demand- and supply-side market shocks. The Value Balancing Alliance (VBA) quantifies these externalities using the Environmental Profit and Loss (EP&L) approach, applying value factors such as the Social Cost of Carbon.

The Benchmark

This capstone builds on the September 2025 VBA–Deloitte paper "Aligning Carbon Valuation with Decision-Making" and extends its reasoning beyond carbon. The carbon benchmark illustrates the logic: the Social Cost of Carbon is currently estimated around USD 244/tCO₂, the EU ETS market price is roughly USD 80/tCO₂ — implying a regulatory internalization rate of ~33%. Corporate internal carbon prices and abatement costs sit around USD 39–46/tCO₂, representing a market internalization level of ~16–19%. Long-term, EU ETS prices are expected to exceed USD 250/tCO₂ by 2050, pushing the internalization rate above 100% of today's externality value.

The Application

My work applies this reasoning across the remaining environmental drivers, with a particular methodological focus on water consumption — using IPCC AR6 WG2 Chapter 4 as the scientific anchor. The output is a comparative framework of 2025-vs-2050 internalization rates per impact driver, per value-chain position, and per regional water-stress context, including payback-period analysis for proactive corporate investment under different internalization trajectories.

Impact Accounting Sustainability Carbon Pricing ESG Applied Economics
Climate Tech | Fintech | Carbon Markets | Co-founder

Vaayubon (VAYU)

An early-stage carbon removal startup turning India's agricultural waste into a dual-revenue engine. As Co-founder and CFO/CSO, I architected the unit economics, carbon credit pricing models, and the strategy for an AI-enabled Digital MRV infrastructure, targeting a highly scalable $76/tonne profit margin with a negative working capital cycle.

Traction: Pilot Proven (150+ Farmers) | IE Venture Day Sustainability Winner

The Problem

India burns 180 million tonnes of agricultural waste annually. Meanwhile, smallholder farmers are barely breaking even. Our model solves both issues simultaneously by turning a climate liability into a direct alternate revenue stream for farmers.

The Solution

Vaayubon collects farm waste and uses pyrolysis to create biochar—locking 2.5 tonnes of CO₂ per tonne produced. The viability of this model rests on monetizing waste: farmers receive an alternate source of income and subsidized biochar, while we generate carbon credits targeted at global tech and manufacturing firms.

The Execution

We successfully ran a pilot with 150+ farmers. I engineered the financial logic: alternate revenue streams for suppliers, forward offtake strategies commanding premium pricing, and a roadmap for a Digital MRV platform tracking batches via IoT and satellite to ensure strict compliance.

Financial Architecture Unit Economics AI / IoT Corporate Strategy
Quantitative Finance | Machine Learning | Econometrics

Factor-Neutral Pairs Trading Pipeline

A production-grade quantitative trading pipeline that screens the entire S&P 500 universe using DBSCAN unsupervised machine learning to identify fundamentally identical stock pairs. Each candidate pair is then subjected to Engle-Granger cointegration testing — a two-step econometric method that mathematically proves mean-reversion before any trade signal is generated. Out of 118,833 fundamental twin pairs tested, 28,429 passed the cointegration filter at a 90% confidence level.

Results Badge: 28,429 Cointegrated Pairs Found
Python DBSCAN Engle-Granger yfinance statsmodels
01 — AI Fintech

Wall‑Et

AI-powered voice and photo-based budgeting tool that delivers predictive financial insights.

The Problem

Traditional budgeting tools introduce too much friction for young professionals and underserved users, leading to poor financial tracking and literacy.

The Solution

I built an AI-powered budgeting application designed to remove data-entry friction entirely. Through Wall‑Et, you can speak directly into the app to break down your expenses and plan your monthly budget. Whether you use voice commands or simply take a picture of a bill, the AI automatically sorts the data into different categories and assigns it.

The Execution

Leveraging third-party AI automation tools, LLM APIs, Lovable, and Supabase, I architected a workflow that transforms unstructured voice commands and photo inputs into structured, predictive financial insights.

Python LLM Orchestration Computer Vision NLP Fintech
02 — Green Finance AI

System Shift Portfolio

AI-driven green investment diversification model for ESG-aligned portfolio optimization.

The Problem

Traditional green finance often focuses too narrowly on end-products. Green investments frequently fail because they only benefit the green companies themselves, making the broader stakeholder chain less stable.

The Solution

I developed System Shift Portfolio, an AI-driven financial portfolio application. The app gathers environmental data from European firms and allows you to swipe through them based on your personal preferences. Once completed, it shows you exactly which Earth System Boundary you are primarily targeting with your investment.

The Execution

SSP helps you determine how to allocate your funds across the entire stakeholder chain — from the suppliers who provide materials to the green companies, all the way to the customers who buy their products and services. The tool ensures everyone in the ecosystem remains aligned and financially stable, driving long-term environmental impact while effectively hedging financial risks.

AI Modeling ESG Portfolio Theory Python Finance
03 — Corporate Strategy

Hyundai España AI Strategy

Finalist AI-led customer retention strategy with a projected +45% retention lift.

The Challenge

As part of a month-long Tech Venture Lab consulting project, my team was tasked with finding a technological solution to combat customer churn and increase retention, even after the four-year free service period had ended.

The Approach

We adopted a rapid prototyping methodology, pressure-testing our assumptions early and pivoting when initial data demanded it. I led the quantitative strategy, defining core business KPIs such as Customer Acquisition Cost (CAC) and Payback Periods to ensure the technical solution was commercially viable.

The Impact

We developed an AI-driven strategic solution aimed at increasing customer retention and loyalty by 45%. We were selected as finalists, and I co-presented the final implementation roadmap directly to the CTO and CEO of Hyundai España.

AI Strategy Customer Retention Automotive C-Suite Advisory
04 — International Trade

$3.5M Trade Line Launch

End-to-end execution of an international paper trade line across the SAARC region.

The Problem

I independently identified a critical upstream supply gap for Kraftliner paper in the SAARC region. Local manufacturers couldn't meet quality benchmarks, creating dependency on fragmented import channels.

The Solution

Recognizing this unmet need, I didn't just write a market report — I took action and leveraged a network of European paper mills to connect supply with South Asian demand. I independently managed the logistics and structured a cross-border trade line at FOUREM Global FZE.

Commercial Impact

$3.5 million in revenue generated through end-to-end execution of the international trade line across the SAARC region.

Trade Execution Supply Chain SAARC B2B Sales
05 — Market Research

$100K Funding Study

Led a 500-person primary research initiative that secured pre-series investor funding.

The Problem

Data without a narrative is just noise. A sustainable footwear line lacked the market validation data required to attract pre-series investment. Investor confidence was low due to absence of quantitative demand evidence.

The Solution

At GSRV and Associates, I spearheaded a primary market study involving over 500 surveys to test the viability of the sustainable footwear line. By translating raw consumer preferences into a robust financial feasibility model, I built the data foundation for the investment case.

Commercial Impact

Successfully secured $100,000 in pre-series funding. The research became the foundation for the company's retail expansion strategy and subsequent fundraising rounds.

Market Research Data Analysis Investor Relations Strategy

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