A Scientific Leader Building Strategy and Technology Innovations• Built an AI/ML strategy and a platform to deploy AI/ML for medicinal chemistry• Led the effort to evaluate and exploit AI/ML for retrosynthesis, route planning, and reaction condition prediction to enable• Developed initiatives to strengthen core computational chemistry capability for binding free energy prediction and virtual screening.• Established partnerships with technology leaders such as PostEra, XtalPi, MIT, and Stanford University and other partners.Lead and mentor a team of diverse talent to delivery computational application to impact project delivery for broad target families.• The team delivered multiple late-stage clinical candidates in disease areas of oncology, neurosciences, cardiovascular and metabolic disease, including SARS-CoV-2 Mpro inhibitor Nirmatrelvir.A Computational scientist with a proven track record of project impact• Co-developed Central Nervous System Multiparameter Optimization (CNS MPO) for designing drug-like molecules with aligned CNS permeability and ADMT attributes. The CNS MPO and similar algorithms have been used broadly across industry.• Possess a strong technical expertise in structure-based drug design and in silico DMPK modeling. Pioneered in silico-first approach in projects where in silico ADMET models are used in design, in vivo compound selection and dose projection.• Directly contributed to clinical candidates for broad targets such as in Proteases, Kinase, Phosphodiesterase, and GPRC target families of multiple disease areas: BACE, PDE10A, PDE9, GlyT1 Transporter, AMPA Receptor, SARS-CoV-2 MPro