S
Simanta Gautam
About
Detail
Co-Founder & CEO
New York, United States
Résumé
Jobs
verified_user
0% verified
Co-Founder & CEOAlpen LabsJun 2022 - Current (4 years 1 month)Alpen Labs is developing the economic foundations for the Internet. Our mission is to build financial infrastructure and cryptographic systems that elevate individual agency and expand financial access for billions of people.- AI LeadPalantir TechnologiesMay 2020 - May 2022 (2 years 1 month)Joined via Synapse acquisition Led Edge AI & ML Infrastructure
- Research Scientist InternClarifaiJun 2016 - Aug 2016 (3 months)Designed and developed cutting-edge deep learning models for image and video understanding. https://www.clarifai.com/
- Founder & CTOSynapse Technology Corporation acquiredJan 2016 - Dec 2020 (5 years)Artificial intelligence and computer vision company focused on security & defense applications. - Raised over $6 million from Founders Fund, In-Q-Tel, 8VC, etc., - led the product, engineering, and research efforts to create the world's first AI product commercially deployed on security X-ray machines, - managed multi-million dollar government contracts as the Principal Investigator (PI), - assembled a diverse patent portfolio on deep learning technology applied to security checkpoints, - took the company through an acquisition by Palantir.
- HResearcherHarvard Computational Cognitive Neuroscience LabJan 2016 - Dec 2017 (2 years)- Worked on successor representations, subgoal inference, and hierarchical deep reinforcement learning. - Formulated a new deep reinforcement learning approach known as deep successor reinforcement learning (spotlight at 2016 NIPS Deep Reinforcement Learning Workshop).
- Software Development InternMicrosoftJan 2016 - Feb 2016 (2 months)Worked on machine learning research and development for Microsoft Azure. In particular, explored transfer learning with pre-trained convolutional neural networks as fixed feature extractors.
- Research Scientist InternAmazonJun 2015 - Aug 2015 (3 months)Worked on natural language understanding (NLU) and dialog management research.
- Computer Vision InternNASA Goddard Space Flight CenterJan 2015 - Feb 2015 (2 months)Developed unsupervised deep learning models to extract high-level spectral features for hyperspectral image classification. Improved long-standing performance benchmarks on hyperspectral imagery.
- MResearch InternMIT Computer Science and Artificial Intelligence LaboratoryJun 2014 - Dec 2014 (7 months)Worked on speaker diarization and deep learning with the Spoken Language Systems group. Developed in-house, GPU-accelerated software for deep learning built on top of Theano.
- Research InternMIT Media LabFeb 2014 - Apr 2014 (3 months)Designed metaheuristics for the Pick up and Delivery Problem in application to a region in Bangalore. Collaborated with other students on developing a simulation software that dynamically generates optimal bus routes on the Bangalore map as customers make pick-up and delivery requests from their smartphones.
Education
verified_user
0% verified
- Computer ScienceMassachusetts Institute of Technology
Projects (professional or personal)
verified_user
0% verified
- MMESA Autonomous Sailing TeamMy team of five won first place in the Sailboat International Robotic Sailing Regatta 1-meter class with a custom-built autonomous sailboat. The boat, named WHIFF, won first place in every autonomous event as well as the Innovation Award for her six-segment 3D-printed hull. My contributions included hull, sail, and internal structural mechanical design and basic aero- and hydro-dynamic analysis, fabrication, and some project management. Our boat's control system was built around an Arduino Mega 2560 microcontroller and used an integrated GPS, wind velocity, and compass sensor to accurately navigate between GPS waypoints.
Awards
verified_user
0% verified
- AI 100 SelectionCB InsightsMar 2020Synapse Technology selected as 100 most promising AI startups in the world by CB Insights based on patent activity, business relations, investor profile, news sentiment analysis, proprietary Mosaic scores, market potential, competitive landscape, team strength, and tech novelty.
- Forbes 30 Under 30ForbesJan 2020Selected as one of the 30 entrepreneurs under 30 years old in Enterprise Technology.
- Stanford $100k Startup Challenge WinnerStanford UniversityMay 2018First Prize for the 2018 Stanford BASES $100k Challenge given to Synapse Technology.
- UMIT Media Lab Medical Incubation PrizeUMass Venture Development CenterNov 2014Developed an image recognition system to classify dermatological images on an iOS platform at the MIT Undergraduate Healthcare Hackathon.
- IWinner of the 2013 International Robotic Sailing RegattaInternational Robotic Sailing RegattaJun 2013Designed and built a fully autonomous, 1-meter sailboat from scratch with a team of four other students. Developed the waypoint navigation algorithm which allowed our boat to win every autonomous event at this collegiate competition.
- ITwo-Time International Award Winner in MathematicsIntel International Science and Engineering FairMay 2013In 2011, awarded Second Place Grand Prize in Mathematics for an independent research in number theory. In 2013, again awarded Second Place Grand Prize among over 1600 finalists for a mathematics research in spherical codes optimization. Also recognized by the American Mathematical Society with a Karl Menger Memorial Award.
- CResearch Science Institute ScholarCenter for Excellence in EducationAug 2012One of 75 students selected among 3000 students to participate in Research Science Institute. Worked under the supervision of the MIT Mathematics Department on an open mathematical optimization problem, called the spherical codes problem. Received top recognition at a national symposium and an international science fair.
Publications
verified_user
0% verified
- NDeep Successor Reinforcement LearningNIPS WorkshopJun 2016Learning robust value functions given raw observations and rewards is now possible with model-free and model-based deep reinforcement learning algorithms. There is a third alternative, called Successor Representations (SR), which decomposes the value function into two components -- a reward predictor and a successor map. The successor map represents the expected future state occupancy from any given state and the reward predictor maps states to scalar rewards. The value function of a state can be computed as the inner product between the successor map and the reward weights. In this paper, we present DSR, which generalizes SR within an end-to-end deep reinforcement learning framework. DSR has several appealing properties including: increase
- MA Novel Approach to the Spherical Codes ProblemMIT MathematicsSep 2012A spherical code is a finite set of points on the surface of a sphere in n dimensional space. The spherical codes problem asks for the maximum number of points in a spherical code where the angle between any two points with respect to the center is at least α. A traditional approach to this problem is to define an energy function for a spherical code as the sum of the inverse distance power of every pair of points and to optimize for minimum energy. However, a method to globally minimize the energy function for any given parameters is unknown, especially for spherical codes in higher dimensions. In our work, we improve the optimization by imposing certain symmetry groups on the spherical codes, as most configurations are invariant under ref