Hi 👋, I'm Aditya

Interested in the intersection of Machine Learning, Statistics, and Quantitative Research in finance.

🎓 Education

• Masters in Science - Computer Science & Statistics (Data Science Track) at Harvard University (Aug 2024 - Dec 2025)
• Financial Mathematics Concentration - Cross Registered at MIT Sloan
• BE in Computer Science from BITS Pilani (Distinction) (Aug 2019 - June 2023)

💼 Work Experience

• Quant Research Consultant at WorldQuant (May 2024 - Aug 2024)
• Machine Learning & Data Engineer at Rostrum Grand Asset Management (Jan 2023 - May 2024)

📝 Research Work

• Cost Efficient Stock Forecasting with Enhanced LightGBM And Optuna Framework, IEEE International Conference MoSICom 2022 [PDF]
• Dynamic Beta Variability in Foreign Exchange Returns Using Instrumented PCA: National Undergraduate Research, Abu Dhabi, 2022 [PDF]
• Credit Risk Assessment Model for UAE’s Commercial Bank: A Machine Learning Approach: National Undergraduate Research, Abu Dhabi, 2021 [PDF]
• Deep Learning-Based Smart Parking Management System and Business Model: Springer Journal, CVIP 2020
• Lithium-Ion Battery Life Prediction from Initial Stage-Cycles Using ML: Intellectual Property Right [PDF]
• Real-Time Drowsiness Detection Using Computer Vision and Raspberry Pi to Prevent Car & Road Accidents: Intellectual Property Right [PDF]

🚀 Projects (I do during weekends)

Quant Projects (along with research papers for reference)

• Jane Street Market Prediction Challenge on Kaggle
• Realized Volatility Prediction Challenge by Optiver on Kaggle
• Nasdaq Closing Price Prediction Challenge by Optiver on Kaggle
• My research findings as a Quantitative Researcher at WorldQuant (non-confidential):
  • Momentum and Reversal using the Instrumented Principal Component Analysis

Feel free to reach out at [email protected]