Niranth Sai

AI Researcher

Varanasi, Uttar Pradesh, India2 yrs 6 mos experience

AI ML PractitionerAI Enabled

Key Highlights

Expert in high-frequency trading and quantitative strategy development.
Proficient in ultra-low latency programming and machine learning.
Research experience in reinforcement learning and autonomous systems.

Stackforce AI infers this person is a Fintech expert with a strong focus on quantitative trading and machine learning.

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Skills

Core Skills

Algorithmic TradingHigh-frequency TradingMachine Learning

Other Skills

Artificial Intelligence (AI)C++Computer VisionDeep LearningDeep Reinforcement LearningHyperparameter OptimizationNeural NetworksPattern RecognitionReinforcement LearningRobot ManipulationRoboticsUltra Low Latency

About

As a Quantitative Researcher and a Financial Engineer, I specialize in high-frequency trading (HFT) and quantitative strategy development. With a strong foundation in machine learning, algorithmic trading, and ultra-low latency programming, I’ve successfully designed and deployed high-performing trading strategies at Plutus Research. My work emphasizes efficient strategy life cycles—from research and backtesting to real-time deployment and continuous optimization across multiple markets. Alongside my work in trading strategy, my research background spans autonomous systems, reinforcement learning, and hyperparameter optimization, with hands-on experience as a DAAD-WISE Scholar at the University of Freiburg and TU Darmstadt. I aim to leverage advanced machine learning and quantitative methods to design impactful solutions in the trading and finance industry, particularly in quantitative trading, risk management, and asset pricing. I am continuously motivated to explore opportunities that blend cutting-edge research with high-impact industry applications. Feel free to connect if you’re interested in discussing advancements in trading technology, financial engineering, or any collaborative research opportunities

Experience

Plutus research private limited

Quantitative Analyst

Jul 2022 – Jan 2025 · 2 yrs 6 mos · Bengaluru, Karnataka, India

Demonstrated proficiency across the entire trading strategy lifecycle, including in-depth research, rigorous development, deployment, and ongoing maintenance to optimize strategy performance
Developed ultra-low latency code leveraging advanced C++ techniques, achieving over 90% reduction in latency for core trading strategies
Oversaw live monitoring and maintenance of trading strategies during market hours, ensuring optimal performance through real-time adjustments and troubleshooting

Ultra Low LatencyAlgorithmic TradingHigh-Frequency TradingMachine LearningC++

Albert-ludwigs-universität freiburg im breisgau

DAAD-WISE Scholar at Machine Learning Lab

Jul 2021 – Sep 2021 · 2 mos · Freiburg, Baden-Württemberg, Germany

Presented a novel pipeline for Automatic Hyperparameter Optimization in model-free Reinforcement Learning using Population-based Bandits with backtracking
Our method was able to outperform the vanilla PBT and PB2 techniques. We showcased our work in the Configuration and Selection of Algorithms(COSEAL) workshop 2021

Technische universität darmstadt

Visiting Undergraduate Researcher at Intelligent Autonomous Systems Group

May 2021 – Jul 2021 · 2 mos · Darmstadt, Hesse, Germany

Developed a novel pipeline for extracting priors from human demonstration videos to accelerate learning on robot manipulation tasks; captured video demonstrations of block stacking to train a skill-prior module
Applied the conventional PPO with an entropy bonus where the entropy term is substituted with a negated KL divergence term between the policy prediction and the output of the skill-prior module to gain priors

Robotics club, iit (bhu) varanasi

Secretary

Sep 2020 – Sep 2021 · 1 yr

Directed a spectrum of educational events, including workshops, student competitions, and mentoring sessions, fostering a dynamic learning environment for skill development and innovation
Co-founded a research group within the club, focusing on early-career research-based projects and initiated seminars featuring industry experts to encourage innovation and knowledge sharing among students