Naveen Arunachalam ML Scientist, Nosis Bio Email: naveen DOT t DOT arun AT gmail DOT com GitHub: @naveenarun

I am currently an ML Scientist at Nosis Bio. Our mission is to end all chronic disease. I completed my PhD at MIT in the Kulik Group, where I worked on ML-guided chemical discovery. My PhD research was supported by the NSF, DARPA, and the Office of Naval Research. Personal Information Ph.D. (MIT) 2023; B.S. (Caltech) 2018 Teaching Fall, 2020, 10.585: Engineering Nanotechnology (TA) Spring, 2018, ChE 105: Dynamics and Control of Chemical Systems (TA) Winter, 2018, ChE 103b: Transport Phenomena (TA) Fall, 2017, ChE 15: Introduction to Chemical Engineering Computation (TA) Spring, 2017, ACM 95b/100b: Applied and Computational Mathematics (TA) Fall, 2016, ChE 62: Separation Processes (TA) Winter, 2016, Ch1b: General Chemistry (TA) Research I am interested in advancing AI- and ML-accelerated virtual screening of novel therapeutics, whereby safe and effective medicines are rapidly discovered on demand for any disease. I have worked on several areas in the design of novel matter, including: Mathematically calculating the properties of novel molecules using GPUs Database [web] of >100k molecules and their properties Inferring trends and design principles from chemical data [web] Accelerating design by using machine learning to calculate chemical properties in milliseconds (rather than hours, in the case of GPU calculations) [pdf] Reducing the number of GPU calculations needed to train machine learning models [web, web] Helping humans interactively co-create new molecules with trained ML models MolSimplify Lite [web] - design tool for transition metal complexes MOFSimplify [web, pdf] - design tool for metal-organic frameworks Helping humans guide state-of-the-art AI model architectures (transformers), which are used in molecular design [web]