At the moment, my professional endeavors focus primarily on generative ai with a interest in diffusion and LLM models. I have also worked at the intersection of machine learning and the life sciences, including years spent in the wet-lab developing various biomedical projects for point-of-care diagnostics, medical devices, drug therapeutics and delivery nanoplatforms. I have been awarded multiple SBIR grants for building novel ideas from the ground up. The experiences have given me a unique insight into the data-generating process.

Through my work at Gilead, Genentech, Novartis and other startups (big and small), I have been able to leverage my creativity, curiosity and problem-solving skills to help develop unique machine learning solutions to challenging and impactful problems. The results of which have provided actionable insights and discoveries that benefited patients and research.

In my spare time, I like to hike, bike, visit museums and learn about new developments in the machine learning community including reading about variational, deep learning and bayesian ideas. I've traveled across Europe, Asia and soon hope to road trip across the states.

I frequently choose to come out of my comfort zone to work on new opportunities, technologies and projects that have great impact. Prior experiences and interests include deep learning, reinforcement learning, meta-learning, natural language, bayesian ideas, causality, drug discovery and genomics.

I also tend to look forward to cool conversations, collaborations, and playing chess - any takers?

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Interested in hiking, tennis, latte's (decaf), cars, machine learning or biology? Let's chat!