I am an entrepreneurial-minded, technology-driven, problem-solving enthusiast, who is on a journey to fulfill his dreams of making 10,000 peoples lives better everyday with the product that he helps create. I call if the 10,000 Dream.
I am someone who loves to know and implement the bleeding edge of his interests in technology. I am an advert clean code maniac, who loves to implement the perfect (sigh) application. #refactorAsYouWrite
I love photography and learning new ways to better my leadership skills (Triple-crowned Toastmaster 😎) in the societies/clubs in which I hold positions of responsibility. I specifically enjoy collaborating with people on problem that need deep thinking.
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🧑💻 Applied Scientist 👨🏫
📍 San Francisco, CA 🌉
📆 Feb 2023 - now
As an applied Scientist my primary work is two folded:
Firstly, I collaborate with other researchers on building machine learning models meant to improve Ripple's solutions for facing digital asset markets. This requires me to apply my ML modeling and statistical analysis skills to translate business problems into machine learning problems in order to develop optimal solutions. Project in this domain include - creating Anomaly Detection model as a service for real time payments/trade data. Creating models for payment orchestration. Models analyzing market micro-structure.
Secondly, I contribute to tooling that allows for the above models to be built/experimented on at scale using our own Experimentation Bench. Once a good enough model is built, I also contribute to making sure the models are seamlessly deployed into production. This allows me to tackle real-world issues such as missing or inconsistent data, its latency, and data cleanness efforts. Continuous deployment and experimentation keeps me close to the source of truth, its speculations, and its results.
Apart from the above, I also lead and collaborate on the AI (read LLM) application efforts in the company on varied use cases. Our latest effort is on LLM fine tuning (or its need thereof) to help builders with improving code coverage across our proprietary codebase in our own style of codebase maintenance.
🙇♂️ Graduate Research Assistant 🧐
📍 Pittsburgh, PA ⛷️
📆 Aug ‘22 - May ‘23
I am working on a Few Shot discriminative feature representation learning model for audio classification with minimal data.
🧑🔬 Applied Science Intern 💰
📍 San Francisco, CA 🌁
📆 May ‘22 - Aug ‘22
Working with the wonderful ML/AI Applied science team at Ripple for Automated Trading use case.
BRB asking my manager how much can I disclose 😄
🧑🏫 Teaching Assistant 🙇♂️
📆 May ‘22 - now