Seek AI Labs is a team of researchers working on developing and studying machine learning methods for natural language processing of data, computational pragmatics, semantic parsing, and information retrieval. We are working to build a true Natural Language Interface to Data (NLID).
A former quant, Sarah founded Seek AI in 2021. Sarah most recently led the consumer data team at Citadel's Ashler Capital. Prior to joining Citadel, Sarah led enterprise data product development at two startups, Edison and Predata, which both exited. Sarah started her career as a quant at ITG developing algorithmic trading strategies. Sarah has a Master in Finance degree from Princeton and dual Bachelor's degrees in Astrophysics and Business Economics from UCLA.
Raz joined Seek AI in March 2022 and has served in the roles of founding NLP Research Scientist and Director of AI. Prior to Seek, they worked on research in lexical semantic change detection and NLP applications for indigenous and low-resource languages. At Seek, Raz is interested in how semantic parsing and computational pragmatics may be employed to answer valuable business questions. Raz holds a MS in Computational Linguistics from Montclair State University and a BA in Philosophy and History of Mathematics from St John’s College.
Utkarsh is a graduate student in Computer Engineering with a focus in Machine Learning at NYU. Utkarsh is originally from India and prior to joining Seek has worked in the field of VR for Cosm Immersive and developed live streaming applications. As a NLP researcher at Seek, Utkarsh will be focused on leveraging Large Language Models to understand and automate answering business queries.
Graduating with a degree in Artificial Intelligence from the University of Edinburgh last year, Reilly joined Seek AI in October 2022. While attending university he co-founded a successful events management company in addition to working as a Software Engineer and Data Scientist. At Seek he is focusing on NLP Research and Engineering, helping to build the foundation of our products.
An engineering leader with 10+ years of experience building data analytics and business intelligence software, José is responsible for overseeing the architecture, development, and security of Seek AI’s web platform and products, managing the engineering organization and leading all aspects of the development lifecycle. Most recently, he was Senior Director of Engineering at Numerator (acquired by Kantar), and has previously worked at Oracle and GE Healthcare. He has a Bachelor of Science degree in Electrical Engineering and Computer Science from MIT.
Erik joined Seek in early 2023 as a Research Scientist. He works on reinforcement learning and evaluation in service of generating useful code with language models. Prior to Seek, he researched counterfactual reinforcement learning in the CausalAI lab at Columbia University, researched reinforcement learning for equity trading at Columbia Business School, and built a product for the census bureau. He holds undergraduate degrees in pure and applied math, as well as a master's degree in machine learning from Columbia. He plays a lot of chess and basketball, but never at the same time.
Claire is a Group Leader at the University of Tuebingen, in the Cluster of Excellence Machine Learning for Science. She was awarded an Emmy Noether award under the AI Initiative call in 2022. Her research is on sequential decision making. It mostly spans bandit problems, and theoretical Reinforcement Learning, but her research interests extend to Learning Theory and principled learning algorithms. While keeping in mind concrete problems, she focuses on theoretical approaches, aiming for provably optimal algorithms. Previously, she was a Research Scientist at DeepMind in London UK since November 2018 in the Foundations team lead by Prof. Csaba Szepesvari. She did a post-doc in 2018 with Prof. Alexandra Carpentier at the University of Magdeburg in Germany while working part-time as an Applied Scientist at Amazon in Berlin. She received her PhD from Telecom ParisTech in October 2017, under the guidance of Prof. Olivier Cappé.
Panos Ipeirotis is a Professor and George A. Kellner Faculty Fellow at the Department of Technology, Operations, and Statistics at the Leonard N. Stern School of Business of New York University. His research focuses in the areas of crowdsourcing, machine learning, web data management, and social media analytics. He is widely regarded as the world's leading expert in building human-machine loop systems, that integrate human and machine intelligence to generate outcomes that are better than what humans alone or machines alone can achieve. He has also received more than ten “Best Paper” awards and nominations, and a CAREER award from the National Science Foundation. For his contributions in the field of social media, user-generated content, and crowdsourcing, he received the 2015 Lagrange Prize in Complex Systems.
Sarah Nagy
CEO
Bio
A former quant, Sarah founded Seek AI in 2021. Sarah most recently led the consumer data team at Citadel's Ashler Capital. Prior to joining Citadel, Sarah led enterprise data product development at two startups, Edison and Predata, which both exited. Sarah started her career as a quant at ITG developing algorithmic trading strategies. Sarah has a Master in Finance degree from Princeton and dual Bachelor's degrees in Astrophysics and Business Economics from UCLA.
Raz Besaleli
Bio
Raz joined Seek AI in March 2022 as the founding NLP Research Scientist and then as Director of AI Research in March 2023. Prior to Seek, they worked on research in lexical semantic change detection and NLP applications for indigenous and low-resource languages. At Seek, Raz is interested in how semantic parsing and computational pragmatics may be employed to answer valuable business questions. Raz holds a MS in Computational Linguistics from Montclair State University and a BA in Philosophy and History of Mathematics from St John’s College.
Utkarsh Shekhar
Bio
Utkarsh is a graduate student in Computer Engineering with a focus in Machine Learning at NYU. Utkarsh is originally from India and prior to joining Seek has worked in the field of VR for Cosm Immersive and developed live streaming applications. As a NLP researcher at Seek, Utkarsh will be focused on leveraging Large Language Models to understand and automate answering business queries.
Reilly Goddard
Bio
Graduating with a degree in Artificial Intelligence from the University of Edinburgh last year, Reilly joined Seek AI in October 2022. While attending university he co-founded a successful events management company in addition to working as a Software Engineer and Data Scientist. At Seek he is focusing on NLP Research and Engineering, helping to build the foundation of our products.
José Pacheco
VP of Engineering
Bio
An engineering leader with 10+ years of experience building data analytics and business intelligence software, José is responsible for overseeing the architecture, development, and security of Seek AI’s web platform and products, managing the engineering organization and leading all aspects of the development lifecycle. Most recently, he was Senior Director of Engineering at Numerator (acquired by Kantar), and has previously worked at Oracle and GE Healthcare. He has a Bachelor of Science degree in Electrical Engineering and Computer Science from MIT.
Erik Skalnes
Bio
Erik joined Seek in early 2023 as a Research Scientist. He works on reinforcement learning and evaluation in service of generating useful code with language models. Prior to Seek, he researched counterfactual reinforcement learning in the CausalAI lab at Columbia University, researched reinforcement learning for equity trading at Columbia Business School, and built a product for the census bureau. He holds undergraduate degrees in pure and applied math, as well as a master's degree in machine learning from Columbia. He plays a lot of chess and basketball, but never at the same time.
Claire Vernade
Bio
Claire is a Group Leader at the University of Tuebingen, in the Cluster of Excellence Machine Learning for Science. She was awarded an Emmy Noether award under the AI Initiative call in 2022. Her research is on sequential decision making. It mostly spans bandit problems, and theoretical Reinforcement Learning, but her research interests extend to Learning Theory and principled learning algorithms. While keeping in mind concrete problems, she focuses on theoretical approaches, aiming for provably optimal algorithms. Previously, she was a Research Scientist at DeepMind in London UK since November 2018 in the Foundations team lead by Prof. Csaba Szepesvari. She did a post-doc in 2018 with Prof. Alexandra Carpentier at the University of Magdeburg in Germany while working part-time as an Applied Scientist at Amazon in Berlin. She received her PhD from Telecom ParisTech in October 2017, under the guidance of Prof. Olivier Cappé.
Panos Ipeirotis
Bio
Panos Ipeirotis is a Professor and George A. Kellner Faculty Fellow at the Department of Technology, Operations, and Statistics at the Leonard N. Stern School of Business of New York University. His research focuses in the areas of crowdsourcing, machine learning, web data management, and social media analytics. He is widely regarded as the world's leading expert in building human-machine loop systems, that integrate human and machine intelligence to generate outcomes that are better than what humans alone or machines alone can achieve. He has also received more than ten “Best Paper” awards and nominations, and a CAREER award from the National Science Foundation. For his contributions in the field of social media, user-generated content, and crowdsourcing, he received the 2015 Lagrange Prize in Complex Systems.
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