Talks and presentations

2019 Leveraging historical reaction data to inform synthesis and synthesis design. Foundations of Process Analytics and Machine learning (FOPAM), Raleigh, NC.
Data-driven chemical synthesis design. Schrodinger, New York, NY.
Data-driven chemical synthesis design. BASF, Ludswighafen, Germany.
Leveraging reaction data to build predictive models of synthetic chemistry. Progress and Developments of Artificial Intelligence for Drug Design, IIT, Genoa, Italy.
Computer-aided chemical synthesis: progress and opportunities. AIChE Process Development Symposium, Houston, TX.
Designing synthetic routes using published reaction data and machine learning. Joint Center for Energy Storage Research: Redoxmer Workshop, Dedham, MA.
Computer assistance in organic synthesis planning and execution. Department of Chemical & Biomolecular Engineering, NUS, Singapore.
Computer assistance in organic synthesis planning and execution. Department of Chemical Engineering, MIT, Cambridge, MA.
Autonomous systems and big data in (chemical) discovery and development. Pfizer Executive Leadership Team, Cambridge, MA.
Computer assistance in organic synthesis planning and execution. Department of Chemical Engineering, Stanford University, Stanford, CA.
Computer assistance in organic synthesis planning and execution. Department of Chemical and Biomolecular Engineering, UC Berkeley, Berkeley, CA.
Machine learning approaches to synthesis planning. Pfizer, Groton, CT.
Computer assistance in organic synthesis planning and execution. Silicon Therapeutics, Boston, MA.
Computer assistance in organic synthesis planning and execution. Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ.
2018 Learning to plan and validate chemical syntheses from historical reaction data. The Practical Application of Artificial Intelligence in Drug Discovery & Development, Amgen, Cambridge, MA. Leveraging reaction data and machine learning to build predictive models of synthetic chemistry. ExScientia, Oxford, UK.
Learning to design and validate small-molecule synthetic routes from historical reaction data. AIChE Annual Meeting, Pittsburgh, PA.
Closed-loop reaction optimization in microscale oscillating droplets: an MINLP algorithm applied to Suzuki-Miyaura coupling catalyst selection. AIChE Annual Meeting, Pittsburgh, PA.
Photoredox iridium-nickel dual catalyzed decarboxylative arylation cross-coupling: from batch to continuous flow via self-optimizing segmented flow reactor. AIChE Annual Meeting, Pittsburgh, PA.
Leveraging historical reaction data to inform synthesis and synthesis design. 4th Annual Organic Chemistry Meeting of the Minds, Boston, MA.
Machine learning applications in synthesis. Machine Learning and Artificial Intelligence in Chemistry Mini-Symposium, Novartis Pharma AG, Cambridge, MA.
Machine learning in synthetic organic chemistry. Workshop on Deep Learning for Multiphase Chemistry, UCI, Irvine, CA.
Machine learning for synthetic chemistry. Deep Materials Summer School, TU Dresden, Dresden, Germany.
Automated system for knowledge-based continuous organic synthesis (ASKCOS): Data-driven pathway design and validation. 256th ACS National Meeting, Boston, MA.
Opportunities for applying machine learning to chemical synthesis and synthesis planning. An AI Immersion for IMED, AstraZeneca, Waltham, MA.
ML-driven pathway design and validation in automated synthesis. RSC Artificial Intelligence in Chemistry Symposium, London, UK.
Leveraging reaction data and machine learning to build predictive models. Scilligence Spring R&D Informatics Workshop, Cambridge, MA. .
Intelligent design of synthetic pathways in organic chemistry. MIT Intelligence Quest Launch, Cambridge, MA.
2017 On-demand medicinal chemistry and compound synthesis in oscillating droplets. AIChE Annual Meeting, Minneapolis, MN. 2017.
Machine learning for pathway validation in automated synthesis. NCATS Automated Chemical Synthesis Workshop, National Institutes of Health, Bethesda, MD. 2017.
Applying machine learning to synthesis design: Prediction of organic reaction outcomes. 254th ACS National Meeting, Washington, DC. 2017.
Machine learning for synthesis planning. Novartis Pharma AG, Cambridge, MA. 2017.
2016 Processes for continuous synthesis of pharmaceuticals. Poster session: ISCMP, Cambridge, MA. 2016.
2011 Modeling nitrogenase using rubredoxin from Pyrococcus Furiosus Poster session: Caltech SURF Seminar Day, Pasadena, CA. 2011.