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AI Engineer with 1+ years in Quantitative Research & AI/ML
B Hari Charan Goud is an aspiring AI Engineer pursuing a B.Tech in Data Science and Artificial Intelligence. With 1.5 years of experience as a Quantitative Research Consultant at WorldQuant BRAIN, he specializes in developing trading alphas and leveraging LLMs for automated alpha generation. His expertise spans Python, deep learning frameworks, NLP, and machine learning, as demonstrated through impactful projects in chess commentary analysis, stock portfolio optimization, and adversarial defense in deepfake detection. He is proficient in generative AI and prompt engineering, actively contributing to the field with a strong foundation in core AI/ML concepts and practical application.
Indian Institute of Technology, Bhilai
B Tech · Data Science and Artificial Intelligence
August 1, 2022 – June 30, 2026
WorldQuant BRAIN
Quantitative Research Consultant
November 1, 2024 – Present
India
Reinfolio
June 7, 2026 – Present
Constructed a stock portfolio optimization system leveraging Deep Q-Networks (DQN) in Reinforcement Learning and LSTM-based neural networks, generating buy/hold/sell signals for selected NYSE listed stocks. Implemented a DQN framework to optimize asset portfolios based on historical data for a given stock set. The generated strategy achieved 7% return on investment.
View ProjectAdversarial De-Magnification
June 7, 2026 – Present
Developed a reinforcement learning-based defense on ResNet-50 to counter super-resolution adversarial attacks in deepfake detection. Boosted classification accuracy from 91.5% to 94.2%, reduced adversarial success rate, and achieved 87% recall with 13% false negatives, significantly improving model robustness.
View ProjectChess Commentary Analysis (ChessCommGen)
June 7, 2026 – Present
Developed a transformer-based model that generates natural language commentary for chess moves by leveraging board states and move history. Trained on 11.6K games (298K move-commentary pairs), to generate context-aware commentary using sequence modeling techniques.
View ProjectQuant Quest event - 3rd position
Algobulls (Kshitij, IIT Kharagpur)
January 1, 2025 – Present
Amazon ML Summer School
Amazon
January 1, 2024 – Present
Inter IIT Tech Meet 2024 - Algotrading problem statement
Inter IIT Tech Meet
January 1, 2024 – Present
Cultural Fit Analysis
The candidate's involvement in competitive coding clubs and design clubs, along with participation in inter-collegiate tech meets, suggests a proactive, collaborative, and achievement-oriented mindset. The diversity of projects, from chess commentary to algorithmic trading and adversarial defense, indicates a broad interest in various AI/ML applications, which aligns well with an innovative and research-driven culture. The part-time quantitative research role further demonstrates a practical, results-driven approach.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through complex project implementations and competitive achievements. The ability to work on diverse projects (NLP, Reinforcement Learning, Quantitative Finance) suggests adaptability and a proactive learning attitude. The part-time role at WorldQuant BRAIN indicates an ability to apply theoretical knowledge in a real-world, high-stakes environment. However, without direct interview data, specific communication and team collaboration skills cannot be fully assessed.