Semantic Machines is made up of a team of proven researchers, engineers and entrepreneurs with extensive track records in AI and natural language development. Our team has unique experience, previously having built core AI assistant technology for Apple and Google as well as leading award-winning academic research. Collectively, we have made pioneering contributions to natural language processing, speech recognition, speech synthesis, deep learning, semantic understanding, machine learning and linguistics.
Abby manages the AI Trainer team at Semantic Machines. Abby moved to Boston after graduating from Florida State University with a B.A. in English Literature and Psychology. Prior to joining Semantic Machines she worked at MIT as a librarian.
Adam received a B.S. in Computer Science and Physics from the University of British Columbia. As an undergraduate, he published papers in both planetary astronomy and natural language processing. He received his PhD in 2012 from UC Berkeley in Computer Science, specializing in machine learning and natural language processing. His studies were funded by fellowships from Google, UC Berkeley, and the Natural Sciences and Engineering Research Council of Canada (NSERC). His work on optimal parsing algorithms won the Best Paper Award from the Association for Computational Linguistics in 2009. After graduation, he worked as a research scientist at Google, focusing on natural language understanding and question answering. Outside of academics, Adam remains passionate about language and has studied 7 languages to varying degrees of fluency.
Data & Applied Scientist
Alan received a B.S. with Highest Distinction in Mathematics from Duke University in 2011, where he was a Faculty Scholar, awarded to three undergraduates across the university for outstanding scholarship, and where he won the departmental Julia Dale prize for excellence in mathematics. He went on to receive a PhD in Computer Science from MIT in 2015, funded by a National Science Foundation Graduate Research Fellowship. Alan has published over a dozen papers spanning mathematics, computer science, and medicine, including a paper proving NP-hardness of classic Nintendo games such as Mario and Zelda. After graduation, he worked as a quantitative analyst at a hedge fund in Boston.
Alex previously worked on deep learning for medical data at Bayes Impact and on English-to-SQL machine translation at Upshot. He received his B.A. in Applied Mathematics, B.A. in Computer Science, and M.S. in Computer Science from U.C. Berkeley.
Data & Applied Scientist Manager
Alexander Zotov is an experienced developer, applied scientist, and manager. He has been with Microsoft since 1996 and helped a multitude of projects such as Internet Explorer, Intentional Programming, Tablet PC, Live Labs Pivot, Bing Relevance and Ranking, and Cortana Language Understanding.
Andrei previously worked on modeling and platform scaling for Microsoft Cortana and on Async Media services for Microsoft Skype. He received his master’s degree in robotics from Moscow State University.
Andy oversees product management for the engineering and research efforts in Semantic Machines. He joined the team shortly after the acquisition and has also been driving the integration of its conversational AI technology into Microsoft. Andy is a twelve-year Microsoft veteran, previously working in various product management roles in Bing Relevance and language understanding and dialog systems in Bing and Cortana. Andy received a B.A. in Computer Science and Spanish from DePauw University and an M.S. in Computer Science from the University of Illinois at Urbana-Champaign.
Business Program Manager
Beth works with our Researchers and AI Trainers to develop tools and processes for data collection, with a focus on usability and delivering high quality data. Prior to joining Semantic Machines, Beth worked as a Senior Software Engineer for a wide range of companies from startups to large corporations. Her work includes geospatial data for navigation systems, CAD applications, and medical billing software. Beth holds a BS in Computer Science from the University of Wisconsin.
Executive Business Administrator
Bree is the executive business administrator for Dan Roth and the Semantic Machines team. She has been working at Microsoft for the past 7 years, and has many years of experience as an EA, project and business manager. Her former roles include positions at Myspace and Amgen.
Charles received a BA in computer science and mathematics from UC Berkeley, where he won the departmental Dorothea Klumpke Prize for outstanding mathematics scholarship. He has published papers on algebraic combinatorics and artificial intelligence applied to malware detection. After graduating from Berkeley, he worked at Google as a software engineer, where he focused on social search, voice search, and natural language understanding.
Chris received a BA in computer science and mathematics from UC Berkeley in 2011, and a PhD in Computer Science & Engineering from the University of Washington in 2017, advised by Dan Weld and Mausam. During his PhD, he regularly published papers at top venues revolving around the intelligent management of crowd-powered machine learning. He also spent two summers at Microsoft Research, where he worked on recommendation systems and metareasoning. In his free time, Chris enjoys playing the violin, and freelances with several professional orchestras in the Seattle area.
Chuck has worked in academic, industrial, and government research laboratories on problems in the field of human language technology for more than two decades. Chuck’s research has spanned several areas including: speech recognition, natural language understanding, dialog systems, speaker diarization, and speaker identification. He has a broad range of experience including the following institutions: the Siri team at Apple, the International Computer Science Institute (ICSI) in Berkeley, the Human Language Technology Center of Excellence (HLT/COE) at Johns Hopkins University, and BBN Technologies. Chuck received his PhD from UC Berkeley in an interdisciplinary program incorporating the departments of Computer Science, Linguistics, and Psychology. He also holds a BA and MA from UC Berkeley, both in Linguistics. Chuck has published more than 70 papers and has authored several patents within the field of human language technology.
Co-founder and Operations Consultant
Damon has been a startup CFO for nearly 20 years. Prior to co-founding Semantic Machines, Damon was CFO of TeraDiode, Inc., Shaser BioScience Inc., and NeoSaej Corp. Before that, Damon was VP Finance and later CFO of Voice Signal, where he led the complex and successful acquisition by Nuance Communications, Inc. Damon began his career at PriceWaterhouseCoopers. He received his B.S. in Accounting from Southern New Hampshire University and is a C.P.A.
Co-founder and Technical Fellow
Dan Klein was co-founder, Chief Scientist and VP of Research at Semantic Machines and a recognized leader in the field of natural language processing. Dan is a full professor of computer science at UC Berkeley and was previously Chief Scientist at Adap.tv. Dan has published over 100 papers on a wide range of NLP and machine learning topics, including multiple award-winning results. He is a Microsoft Faculty Fellow, a Sloan Fellow, and a Marshall Scholar. He has received many awards including the ACM’s Grace Murray Hopper award (given to a single CS researcher each year), the NSF CAREER award, and the UC Berkeley Distinguished Teaching Award. Dan holds a PhD in computer science from Stanford University and a Masters in linguistics from Oxford.
Co-founder and CVP Semantic Machines
Dan was co-founder and CEO of Semantic Machines, a serial technology entrepreneur with a focus on building teams and companies that excel at research-intensive product innovation. His first startup, Voice Signal Technologies was a pioneer and industry leader in speech interfaces for mobile devices including the revolutionary iPhone. After Voice Signal was acquired by Nuance Communications [NASDAQ:NUAN] in 2007, Dan founded Shaser BioScience, a developer of consumer laser devices for dermatological applications. Shaser BioScience was acquired by Spectrum Brands [NYSE:SPB] in 2012. Dan received his B.S. in Biology from Trinity College, and is an inventor on more than 90 U.S. and foreign patents.
David works on novel applications of structured prediction and machine learning for building conversational agents. He earned a B.S. in Computer Science and Psychology from the University of Chicago in 2004, and a PhD in computer science from UC Berkeley in 2012. His research has focused primarily on syntactic analysis, especially as it relates to machine translation, but ranges over a wide variety of topics in AI, including variational inference for structured prediction, heuristic search for optimal planning, and video game AI (despite his expertise as an NLP researcher, his most widely publicized project to date is the Berkeley Overmind StarCraft agent). He also has a wide range of professional experience, including work as a software engineer at PEAK6 Investments in Chicago building systems for automated stock trading, as a research intern at SRI and Google working on applications of research in machine translation and natural language processing, and as a data scientist at Twitter working on user behavior analytics, text analysis, and information retrieval.
Co-founder and Researcher
David was a co-founder of Semantic Machines and received his PhD in Computer Science from UC Berkeley advised by Dan Klein. He is the recipient of the 2012 Google PhD Fellowship in Natural Language Processing, an NSF graduate research fellowship, the 2011 EECS Outstanding Graduate Student Instructor award, and a distinguished paper at EMNLP 2012. He has authored 15 publications at top conferences and has built and released numerous software systems, including the fastest high-accuracy constituency parser in the world, state-of-the-art parsers for 10 languages, the Breeze scientific computing library, and the award-winning Overmind StarCraft agent. He has a B.S. and M.S. from Stanford University, both in Symbolic Systems.
Business Data Analytics Specialist
Diana received her B.S. in Information Systems and Operations Management from George Mason University. Prior to Semantic Machines she worked at Microsoft as an Azure AI consultant then as a BI analyst for the MS Sales financial system.
Div has worked on language education and audiobook software at Amazon, information retrieval and linguistic processing software at SAS, search engines at AltaVista, and the WordNet lexical database at the Princeton cognitive science laboratory. He received his B.S.E. in Computer Science at Princeton.
Software Engineering Manager
Prior to joining Semantic Machines, Dmitrij lead a team of applied scientists and engineers building novel dialogue systems and improving Cortana's language understanding within what is now Microsoft's MSAI group. He holds a B.S and M.S. in Computer Science from MIT, where he completed a thesis in program analysis systems for malware detection, under the supervision of Martin C. Rinard. During his time at MIT, he interned at a variety of technology and trading firms, and sold a recruiting start-up to a Greylock-funded company Readyforce.
Hao Fang received his Ph.D. in Electrical Engineering from University Washington advised by Prof. Mari Ostendorf. His research interests are conversational AI, natural language processing, and deep learning. He is a recipient of 2018 College of Engineering Student Research Award at the University of Washington. In 2017, he led the UW Sounding Board team which won the inaugural Alexa Prize. He obtained his Master degree from University of Alberta, and Bachelor degree from Beijing University of Posts and Telecommunications.
Data & Applied Scientist
Ilya previously worked on conversation understanding and search relevance tools in different teams at Microsoft and on the Meta Programming System at JetBrains. Ilya received his B.S and M.S in Applied Mathematics and Computer Science from St. Petersburg State Polytechnical University.
Izabela received a M.S. in Computer Science and Management from MIT in 2018 and M.S. in Product Engineering from SUTD (Singapore) in 2019. Her research focused on creating a framework on how to evaluate AI products: human-centric vs human-like. While at MIT she worked closely with Erik Brynjolfsson under The MIT Initiative on the Digital Economy where she conducted research on how AI and robotics effect work automation. She previously worked at Amazon Robotics, various start-ups and in venture capital, where she performed due diligence on AI start-ups and defined the firm’s strategy on AI start-ups investment. Outside of research, Izabela has eclectic projects experience ranging from being a member of World Economic Forum as a Global Shaper, working on VR projects, using Machine Learning to detect art forgery, and working with various start-up accelerators and incubators around the world.
Jacob is an assistant professor at MIT and a researcher at Semantic Machines. His research focuses on language learning as a window into reasoning, planning and perception, and on more general machine learning problems involving compositionality and modularity. Jacob earned his Ph.D. from UC Berkeley, his M.Phil. from Cambridge (where he studied as a Churchill scholar) and his B.S. from Columbia. He has been the recipient of an NSF graduate fellowship, a Facebook fellowship, and paper awards at NAACL and ICML.
Jason received a Ph.D. in Computer Science from UC Berkeley in 2011, advised by Prof. Stuart Russell. While at Berkeley, he published papers in leading venues on diverse topics including bioinformatics, machine learning, robotics, search algorithms, and AI planning. He has improved machine translation quality at Google, hacked robots at Willow Garage, and lead an engineering team to build machine learning and NLP systems for personalized news ranking at Prismatic. Jason is a Siebel Scholar, the lead author and maintainer of several widely used Clojure libraries, and an onsite finalist in the Google Code Jam international programming competition.
Jayant’s research interests are in natural language understanding and he has published numerous papers in top venues in this area. He received his B.S. in computer science from MIT and his Ph.D. in Computer Science from Carnegie Mellon University in 2015, advised by Prof. Tom Mitchell.
Data & Applied Scientist
Jean has experience in developing both commercial spoken dialogue systems and text analytics products, and works on projects focused on both speech and dialogue at Semantic Machines. Previously, Jean was a Software Engineer at Intel working to bring the Intel Real Speech dialogue technology to market in the Oakley Radar Pace product. Prior to that she was a Senior Linguistic Specialist at the SAS Institute where she developed taxonomies for sentiment analysis in multiple languages. Jean’s academic research spans the fields of language acquisition, syntax, semantics and sentence processing. She has been a peer mentor to senior technical females and a panelist at women’s conferences. Jean has a BA in International Business from the University of Georgia, an MA in Applied Linguistics from Boston University and a PhD in Theoretical Linguistics from the University of Connecticut.
Software Engineering Manager
Jesse leads development of end-user applications, conversational data acquisition, and cloud infrastructure for distributed AI agent technology. He enjoys a wide range of areas in software development, from building delightful user interfaces to optimizing the last few microseconds out of low-level code. Jesse started in the games industry before leaving become a software contractor, where he built websites of every sort, Mac apps for scientific research, and a cat-entertaining robot (it used lasers). Just prior to joining Semantic Machines, he was leading teams building world-class iPhone and iPad apps for flight pricing, photo manipulation, event planning, news reading, and more.
John previously worked on the Watson project at IBM specializing in a range of fields including machine learning, NLP, conversational systems, and front end development of tools and consumer applications. He received his B.S. in Computer Science, B.S. in Mathematics, and M.S. in Applied Mathematics and Statistics from Georgetown University.
Prior to joining Semantic Machines, Josh worked as a Software Engineer at TripAdvisor where he focused on optimizing service data processing as well as developing models to predict click-through rates based on profile activity. Josh has a BS in computer engineering from Iowa State University where he also worked as a research assistant developing mobile applications, games for a local startup, and presented at an ICSE workshop on distributed software development.
Business Program Manager
Kate works with the natural language generation team at Semantic Machines. Her prior experience includes Web Development, WCAG/508 Accessibility Compliance, Quality Assurance, and Data Analysis. Kate has a B.S. from Bellevue University.
Business Program Manager
Kellie has been with Semantic Machines since 2016, initially analyzing and compiling data as an AI trainer. She has since joined the natural language generation team, where she builds and maintains the textual aspects of the interacting with the AI. She also teaches AI trainers how to use related NLP tools. Kellie has a B.A. from U.C. Davis.
Business Program Manager
Prior to joining Semantic Machines, Kristin spent 2 decades in Retail Software development, working with major retailers such as Victoria's Secret, Jo-Ann Fabrics, Staples, and Nike. In her role as a Business Program Manager for Semantic Machines, she has used her experience with Quality Assurance, Business Analysis, and Software Development to help develop and improve the process of collecting the data required for machine learning.
Co-founder and Researcher
Larry was a co-founder and CTO of Semantic Machines and has more than 30 years of experience at the forefront of speech and language R&D. He was the Vice President of Research at Dragon Systems, the premier innovator in the field of speech recognition for personal computers. Under his leadership, Dragon released Dragon NaturallySpeaking, the first continuous speech dictation product. He went on to serve as Vice President of Core Technology at Voice Signal Technologies, a successful startup that developed speech recognition and synthesis for mobile phones. After the acquisition of Voice Signal by Nuance Communications, Larry became Nuance’s Vice President of Research for mobile devices. Most recently, he was Chief Speech Scientist for Siri at Apple. He is the author of more than 25 patents and many influential scientific papers. Larry has a BA from Swarthmore College, an MA from Columbia University, and a PhD in applied mathematics from MIT.
Leah received a B.A. in Computer Science and Economics from UC Berkeley. Prior to joining Semantic Machines, Leah worked as a backend developer on the product security team at Twitter and as a full-stack web developer at Hired Inc.
Mike started research in speech recognition over 20 years ago as an early member of Dragon Systems working on the first version of Dragon NaturallySpeaking. He then joined Voice Signal as a senior researcher and later led a research team at Nuance. Michael has worked on a broad range of speech technology projects from very large research systems (DARPA SwitchBoard and Broadcast News evaluations) to commercial applications such as LVCSR, speaker identification, wake-up word recognition, and audio mining. He received a BA in Mathematics from Cambridge University, and a PhD in Theoretical Physics from Princeton, and held a two-year research fellowship at Harvard.
Mikko is an experienced Product Management leader with experience in both large companies - such as Amazon, Microsoft, and Expedia - as well as startups. Mikko’s area of interest and expertise is customer experience and customer service. Mikko has managed the build of popular customer-facing products such as Bing Local Search and Amazon Online Gift Card Mall. Mikko also managed the product portfolio and agent toolset for Expedia’s Customer Service division and has extensive knowledge of contact center operations. Mikko holds a B.S. (Economics & Finance) and M.S. (Mgt Information Systems) degrees from Clarkson University, as well as an MBA from Yale School of Management.
Percy was Lead Scientist at Semantic Machines and is an Assistant Professor of Computer Science at Stanford University. His research spans theoretical machine learning to practical natural language processing; topics include semantic parsing, question answering, machine translation, online learning, method of moments, approximate inference, Bayesian modeling, and deep learning. He has over 60 publications appearing in top venues and has received several paper awards. Percy received a B.S. in computer science from MIT and a Ph.D. from UC Berkeley in 2011. After graduation, he spent one year at Google, where he was one of the founding members of the semantic parsing team. His awards include an IJCAI Computers and Thought Award (2016, given to a single AI researcher every two years), an NSF CAREER Award (2016), a Sloan Research Fellowship (2015), and a Microsoft Research Faculty Fellowship (2014).
Sam’s research focuses on language understanding, and especially on developing deep learning techniques for working with graph representations of natural language semantics. He received his Ph.D. in Language and Information Technologies from Carnegie Mellon University in 2019, and his B.A. in Mathematics from Cornell University in 2004. Prior to graduate school, Sam worked on adaptive learning at Knewton, subject-based social media at Sulia, played jazz piano and poker around Chicago and the Caribbean, and worked as a freelance production assistant on TV commercials.
Data & Applied Scientist
Prior to joining Semantic Machines, Smriti worked on search and ranking projects within Microsoft. Before that, she was managing the machine learning pipeline for a New York startup focused on real-time summarization. Smriti has a Master’s in Computer Science from SUNY Buffalo where she helped develop an AI-powered rehabilitation device for neurological injury, advised by Dr. Ifeoma Nwogu. Her work was published in AAAI's Joint Workshop on Health Intelligence.
Steven has worked in academic and industrial research laboratories on problems in speech processing for more than two decades. Steven started his career at Dragon Systems working on large vocabulary continuous speech recognition. He then joined Voice Signal, and after its acquisition by Nuance, became a member of its mobile device speech recognition research organization. He later joined the Speech and Language Technology Group within Cisco System's Emerging Technologies. Prior to joining Semantic Machines he was the Director of Speech Research at the International Computer Science Institute (ICSI). Earlier in his career, he was a mathematician who specialized in algebraic topology. He obtained his PhD in mathematics at the University of Warwick and was a Marshall Scholar. Steven is an author of many influential papers in the field of speech and language technology.
Theo works on across across the technology stack at Semantic Machines. Over his career, Theo has engineered distributed systems at scale, worked on highly concurrent financial systems, and built tools and processes to coordinate the efforts of hundreds of software engineers. Theo holds a G.E.D. from the State of Maine.
Manager of Learning and Development
Wendy works on learning and development for human AI Trainers, using her expertise in applied research to support the team’s growth and drive development of the next generation of conversational AI. Before joining Semantic Machines, Wendy began her career at the Human and Chimpanzee Communication Institute (CHCI) working with international researchers. While working for CHCI, Wendy earned two advanced degrees in psychology from Central Washington University. She applied these skills working with public schools and non-profits to create inclusive educational programming to meet diverse educational needs. During this time, she completed a Ph.D. in Special Education at the University of Washington and a post-doctoral research fellowship at the University of Kansas. Wendy draws upon her experience as a university faculty leader, a cross-disciplinary researcher, and a technical support center director to guide collaborative work and meet rapidly evolving needs.
In addition to his work at Semantic Machines, Yu will join the faculty of the Ohio State University in 2020. His research intersects data mining and natural language processing towards the overarching goal of democratizing data science, i.e., enabling non-technical users to enjoy data science capabilities with the help of advanced AI techniques. His research interests include semantic parsing, dialogue systems, knowledge bases, transfer learning, and deep learning, with over 20 publications in top venues on these topics. Yu received his bachelor degree in computer science from Tsinghua University and Ph.D. from UC Santa Barbara in 2018.
Yuchen received B.E. in Computer Science from Tsinghua University, and his M.A. in Statistics and PhD in Computer Science from UC Berkeley. Before joining Semantic Machines, Yuchen was a post-doc researcher at Stanford University. Yuchen’s research interests span natural language processing, machine learning and optimization. He has published numerous papers in top venues. His work on non-convex optimization won the Best Paper Award from the Conference on Learning Theory (COLT) in 2017. Yuchen was the recipient of a Baidu PhD Fellowship in 2015-2016.
At Semantic Machines, Zach’s work focuses on systems and API design. He has written many open source libraries in Clojure and Java, dealing with streaming data, network communication, and functional data structures. He regularly gives talks that distill academic topics down for an industry audience, including distributed systems design, queueing theory, font rendering techniques, naming, design theory, and studies of abstraction within the social sciences. Many of these same topics were covered in his recent book, Elements of Clojure. Zach holds a B.S. in Computer Science from UC Irvine.