Team

 
  NOEL HOLLINGSWORTH   Noel was previously the Director of Data at Second Spectrum, where in 2016 he was named to the Forbes 30 under 30 for his work with spatial-temporal pattern recognition. He worked with 14 NBA teams to improve their game plans and leverage player movement data for a competitive advantage. Noel is a graduate of MIT where he earned a Master’s of Engineering with a focus on machine learning and a B.S. in Computer Science.

NOEL HOLLINGSWORTH

Noel was previously the Director of Data at Second Spectrum, where in 2016 he was named to the Forbes 30 under 30 for his work with spatial-temporal pattern recognition. He worked with 14 NBA teams to improve their game plans and leverage player movement data for a competitive advantage. Noel is a graduate of MIT where he earned a Master’s of Engineering with a focus on machine learning and a B.S. in Computer Science.

  JANE CHEN-LIANG   Jane previously worked as Business Development Manager at Ovia Health, working to build advertising and market research partnerships with consumer product and pharmaceutical companies. Prior to that, she worked at Saint-Gobain, first as a R&D Engineer in abrasives and then as Technical Sales Manager in structural ceramics and ceramic coatings. Jane is a graduate of MIT where she earned a B.S. in Materials Science and Engineering.

JANE CHEN-LIANG

Jane previously worked as Business Development Manager at Ovia Health, working to build advertising and market research partnerships with consumer product and pharmaceutical companies. Prior to that, she worked at Saint-Gobain, first as a R&D Engineer in abrasives and then as Technical Sales Manager in structural ceramics and ceramic coatings. Jane is a graduate of MIT where she earned a B.S. in Materials Science and Engineering.

  AVI KEJRIWAL   Avi was previously an Operations Analyst at MET International, where he developed data collection and processing tools. He has experience in statistical modeling and machine learning through his completion of the Metis program.  He has previously done research in materials science, having studied the effects of nanoparticles in semiconductor films.  Avi is a graduate of Washington University in St. Louis where he earned a Master's and B.S. in Electrical Engineering.

AVI KEJRIWAL

Avi was previously an Operations Analyst at MET International, where he developed data collection and processing tools. He has experience in statistical modeling and machine learning through his completion of the Metis program.  He has previously done research in materials science, having studied the effects of nanoparticles in semiconductor films.  Avi is a graduate of Washington University in St. Louis where he earned a Master's and B.S. in Electrical Engineering.

 
  JASON HIRSHMAN   Jason was previously at Stanford University where he received a Master’s in Computer Science and a B.S. in Mathematics. He was selected for the Stanford A.I. Innovation Group, which sought to apply machine learning in impactful ways. Jason's prior industry experience includes building software at Palantir to model data from Syrian refugee camps and working with the World Bank on their proposal review process.

JASON HIRSHMAN

Jason was previously at Stanford University where he received a Master’s in Computer Science and a B.S. in Mathematics. He was selected for the Stanford A.I. Innovation Group, which sought to apply machine learning in impactful ways. Jason's prior industry experience includes building software at Palantir to model data from Syrian refugee camps and working with the World Bank on their proposal review process.

  BRYAN CHEONG   Bryan was previously a researcher at Stanford University and the Taiwan Institute of Economic Research. His previous work ranged from optimizing algorithms for fast-charging Lithium-ion batteries to modeling multilingual natural language data.  Bryan is a graduate of Stanford University where he earned a Master's in Materials Science and Engineering and a B.S. with Honors in Mathematical and Computational Science.

BRYAN CHEONG

Bryan was previously a researcher at Stanford University and the Taiwan Institute of Economic Research. His previous work ranged from optimizing algorithms for fast-charging Lithium-ion batteries to modeling multilingual natural language data.  Bryan is a graduate of Stanford University where he earned a Master's in Materials Science and Engineering and a B.S. with Honors in Mathematical and Computational Science.

  WILL TASHMAN   Will was previously a Product Design Engineer at Apple, where he created, developed, and integrated key design features in ground-breaking laptops. While at Apple, he worked in large-scale assembly plants to implement design features and processes that were optimized for mass-production environments. Will is also a graduate of MIT where he earned a B.S. in Materials Science and Engineering and minor in Mechanical Engineering.

WILL TASHMAN

Will was previously a Product Design Engineer at Apple, where he created, developed, and integrated key design features in ground-breaking laptops. While at Apple, he worked in large-scale assembly plants to implement design features and processes that were optimized for mass-production environments. Will is also a graduate of MIT where he earned a B.S. in Materials Science and Engineering and minor in Mechanical Engineering.

  ERIC ZELIKMAN   Eric is a current student at Stanford University and a B.S. candidate in Symbolic Systems. Eric has previously worked at a survey-focused AI startup as a full-stack engineer and at a chemical process control company doing software and mechanical engineering. At Stanford, he conducts machine learning research, with focus on distributional representations and natural language processing. He is also an editor-in-chief of the Stanford Undergraduate Research Journal.

ERIC ZELIKMAN

Eric is a current student at Stanford University and a B.S. candidate in Symbolic Systems. Eric has previously worked at a survey-focused AI startup as a full-stack engineer and at a chemical process control company doing software and mechanical engineering. At Stanford, he conducts machine learning research, with focus on distributional representations and natural language processing. He is also an editor-in-chief of the Stanford Undergraduate Research Journal.

  DYLAN CABLE   Dylan received a B.S. in Mathematics from Stanford, where he was awarded the Sterling Award as one of the top 25 members of the graduating class. Previously, Dylan has done research in probability theory, where he solved an open problem about randomly interacting particles. Dylan has published a paper in  Journal of Neuroscience , where his mathematical and experimental analysis challenged the conclusions of a common method for analyzing fMRI data.

DYLAN CABLE

Dylan received a B.S. in Mathematics from Stanford, where he was awarded the Sterling Award as one of the top 25 members of the graduating class. Previously, Dylan has done research in probability theory, where he solved an open problem about randomly interacting particles. Dylan has published a paper in Journal of Neuroscience, where his mathematical and experimental analysis challenged the conclusions of a common method for analyzing fMRI data.

  ARJUN SRINIVAS   Arjun was previously a founder of Innova Dynamics (Acq. TPK Holdings Co. Ltd.), a functional materials company, where he served as Chief Strategy Officer and Board Director. Business Week recognized him as one of “America's Best Young Entrepreneurs.” Arjun holds degrees from the University of Pennsylvania in Economics/Finance and Materials Science and Engineering and holds 12 granted US patents. 

ARJUN SRINIVAS

Arjun was previously a founder of Innova Dynamics (Acq. TPK Holdings Co. Ltd.), a functional materials company, where he served as Chief Strategy Officer and Board Director. Business Week recognized him as one of “America's Best Young Entrepreneurs.” Arjun holds degrees from the University of Pennsylvania in Economics/Finance and Materials Science and Engineering and holds 12 granted US patents.