Welcome to My Mind

Data Scientist | Quantitative Researcher

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About Me

Hi! I'm a passionate data scientist and quantitative researcher with a background in software development and machine learning. My journey in the world of data and AI has been driven by curiosity and a desire to solve complex problems through innovative approaches.

Currently, I'm pursuing my Master's degree in Data Science at Johns Hopkins University, where I'm focusing on advanced machine learning techniques, deep learning, and financial data analysis. My research interests include reinforcement learning, time series forecasting, and quantitative finance.

With experience spanning from software development at Oracle to quantitative research at JP Morgan and machine learning engineering at Quantify Capital, I bring a unique blend of technical expertise and domain knowledge to every project I undertake.

I have been fascinated by the perception of universe through the cognitive inference and with an eye of engineering. Keen in solving real world problems via application of machine learning technologies.

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Professional Experience

2021 - 2024

Quantitative Researcher

Developed quantitative execution algorithms for global markets. Conducted advanced research leveraging NLP and (LLMs) to extract actionable insights from unstructured financial data. Enhanced execution strategies through statistical modeling and broker optimization within OMS/EMS frameworks. Collaborated with portfolio managers and traders to support real-time analytics and address high-impact ad-hoc data requests. Designed volume forecasting models to improve execution efficiency and modeled market impact.

2020 - 2021

Software Developer

Developed client-specific customizations and enhancements of Oracle's core products, aligning with bespoke client requirements. Resolved critical production issues for a major corporate bank in India ensuring smooth flow across business functions. Managed and executed data migration projects for clients, ensuring seamless module integration and functionality.

2019 - 2020

Quantitative Researcher

Developed ML-driven trading algorithms across equities, indices, and options. Delivered customized backtesting reports to international clients, supporting a 5x fund growth and 60% ROI. Mentored traders in Python, algorithmic trading, and machine learning fundamentals.

Projects

Project 4

Vision-Language Transformers for Clinical Report Generation

A deep learning pipeline that generates clinical reports from chest X-rays by combining DenseNet121 for visual encoding with BioGPT for medical text generation. Trained on the IU X-Ray dataset, it leverages prompt-based generation and mixed-precision training to deliver accurate and clinically relevant reports.

Python LLM Medical Imaging Deep Learning
Project 2

SmartAlgo: ML-Driven Trading System

Built a fully automated trading system using LSTM-based models for minute-level forecasting and real-time signal generation. Integrated live market APIs, high-frequency execution logic, and SQL-based trade logging. Optimized transaction costs through intelligent limit order handling and maker-taker fee modeling.

Python SQL Machine Learning Quantitative Finance
Project 1

Autonomous Navigation System

A dynamic Android-based control system integrated with MATLAB to enable real-time autonomous navigation for quadruped robots combining mobile flexibility with intelligent path planning and obstacle avoidance.

Robotics Computer Vision MATLAB Hardware
Project 3

Smart Order Routing

Developed a Smart Order Router (SOR) that dynamically splits large orders across market centers using a stochastic optimization framework inspired by the Cont and Kukanov model. The system simulates real-time execution decisions based on queue-depth, fill probability, and latency considerations, minimizing expected implementation shortfall. Implemented a queue-based cost function to optimally allocate shares between market and limit orders under execution risk constraints

Python Quantitative Finance Stochastic Processes Optimization
Project 5

Commercial Website

A fully immpersive and commercial website built using modern web technologies (HTML, CSS, JavaScript). Designed for a professional business presence, it includes a homepage, product/service showcase, contact form with email integration, and mobile-first design. Deployed via epizy and integrated with Google Analytics for performance tracking.

HTML CSS JS Web Development

Technical Publications & Research

Autonomous Real-Time Navigation Based on Dynamic Line and Object Detection

30 June 2020. Springer Singapore

Adarsh Prabhudesai,Pavan Rayar, Samruddhi Pai, Shaival Parikh

This research introduces a mobile-based solution for real-time path correction in autonomous quadruped robots using visual feedback. The system processes environmental cues to detect deviations and transmits corrective actions wirelessly, enabling accurate and adaptive navigation. With minimal hardware requirements, the approach offers versatile applications in robotics, automotive systems, smart manufacturing, and assistive technologies.

Robotics Computer Vision
Paper Code

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Math Challenge Game

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Draw a Line to Fit the Data

Click and drag to draw a line through the scatter plot. Try minimizing the error!

Classification Challenge

Draw a decision boundary

Skills & Expertise

Programming Languages

Python
R
Java
JavaScript
SQL
C++

Machine Learning

Deep Learning
Reinforcement Learning
NLP
Time Series Analysis
Computer Vision
Ensemble Methods

Data Science Tools

TensorFlow
PyTorch
Scikit-learn
Pandas
NumPy
Matplotlib/Seaborn

Quantitative Finance

Algorithmic Trading
Risk Management
Portfolio Optimization
Statistical Arbitrage
Option Pricing
Monte Carlo Simulation

Get In Touch

I'm always open to new opportunities, collaborations, or just a friendly chat about data science, machine learning, or quantitative finance. Feel free to reach out!

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