Astarag Mohapatra

United States

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Summary

🤩

Rockstar

Astarag Mohapatra is a Machine Learning Engineer with 5 years of experience based in San Francisco, blending deep reinforcement learning, data engineering and applied NLP into production systems. He is an active open-source contributor to notable projects like FinRL and Stanford’s DSPy, where he integrated Google Trends into financial RL workflows and built Binance data pipelines while applying Optuna for hyperparameter tuning. In industry roles he delivered measurable impact—cutting monitoring costs 10x at BeiGene, reducing release time from 2 hours to 45 minutes at Salesken, and improving trading Sharpe by 13% in research. His mechanical engineering undergraduate background and a 4.0 Master's in Computational Science, sparked by an AlphaGo-inspired curiosity, give him a cross-disciplinary, experimentally driven approach to solving real-world ML problems.

6 years of coding experience

Github Skills (22)

apim10

dsym10

python10

finance10

pandas10

binance10

fintech10

api10

data-processing10

deep-reinforcement-learning10

jupyter-notebook10

data-acquisition10

data-integration10

optuna10

data-analysis10

Programming languages (3)

JavaJupyter NotebookPython

Github contributions (5)

AI4Finance-Foundation/FinRL

Sep 2021 - Dec 2022

FinRL: Financial Reinforcement Learning. 🔥

Role in this project:

Back-end Developer & Data Engineer

Contributions:3 reviews, 49 commits, 14 PRs in 1 year 3 months

Contributions summary:Astarag's primary contribution involves developing a Python script to download Binance cryptocurrency data within a specified date range. This script leverages the Binance API and utilizes libraries like requests, json, and pandas to retrieve and process the data into a usable format. The user's code also includes a class to handle the data retrieval process. Additionally, the user optimized hyperparameters using Optuna, indicating work on the data processing pipeline and model training process.

stable-baselinesdrl-frameworkdeep-reinforcement-learningsecfinance

AI4Finance-Foundation/FinRL-Meta

Nov 2021 - Aug 2022

FinRL®-Meta: Dynamic datasets and market environments for FinRL.

Role in this project:

Data Scientist

Contributions:1 review, 12 commits, 2 PRs in 9 months

Contributions summary:Astarag contributed to the project by integrating Google Trends data into the FinRL framework and demonstrating its usage with the DOW Jones index. The user's work involved the modification of existing notebooks to incorporate and process external data sources. The contributions include the implementation of a custom data processor to integrate trends data and adapt FinRL to incorporate it, showing the user's ability to extend the existing framework for new analyses. This demonstrates a focus on expanding FinRL's data ingestion capabilities.

data-drivenfinancialdrl-trading-agentsmetaversereinforcement-learning

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