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Before starting TwinMind, I spent more than 6 years leading applied AI at Google X, JPMorgan, and Wolfram, specializing in time-series, NLP, and generative AI.Prior to that, I pioneered real-time AI for detecting gravitational waves from black hole mergers as part of the Nobel Prize–winning LIGO team. I also worked on high-performance computing at Los Alamos National Laboratory and the National Center for Supercomputing Applications (NCSA). I completed my PhD in Astrophysics from the University of Illinois Urbana-Champaign and Bachelor’s in Engineering Physics from IIT Bombay. I won the global ACM Graduate Student Research Competition, the LSST Data Science Fellowship, and the NVIDIA Fellowship.My long-term mission is to accelerate science and technology using AI.
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Cofounder And CeoTwinmindPalo Alto, Ca, Us -
Co-Founder & CeoTwinmind Sep 2023 - PresentPalo Alto, Ca, UsThe first proactive always-on AI with memory that continuously understands what’s happening around you. It enhances your intelligence in real-time, by predicting what you need to know, before you even have to ask (imagine Jarvis from Iron Man) -
Vice President, Applied Ai LeadJpmorgan Chase & Co. Sep 2020 - Aug 2023New York, Ny, UsLed projects across the firm on machine learning for time-series, natural language processing, LLMs and generative AI.- Time-series signal processing using deep learning methods including LSTMs, Neural ODEs, Temporal Fusion Transformers, etc. 1) real-time bond pricing - built the best performing model in the market 2) pricing mortgage-backed securities 3) hedging commodities swaps 4) forecasting oil pipeline flows 5) anomaly detection in debit transactions- NLP projects: 1) LLMs for extracting predictive market moving signals from news 2) semantic understanding of debit transactions 3) parsing trader/client chats to extract quantitative insights -
Ai Research ScientistGoogle X Oct 2018 - Aug 2020Led several confidential applied machine learning projects as a member of the AI center at Google X (the moonshot factory). Developed AI applications in domains including sensor fusion and signal denoising, 3D scanning/reconstruction (patent), genetic engineering, audio/speech processing, motor control optimization for robotic knees, EEG decoding, and forecasting energy consumption in the power grid
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Machine Learning ResidentGoogle X May 2018 - Sep 2018Worked at Google X, Alphabet's moonshot factory, on applied machine learning and AI research as part of the central machine learning team. Developed an ML solution for improving the wind, pressure, and temperature sensors in extreme atmospheric conditions for Project Loon (patent) and contributed to two other early-stage research projects
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Deep Learning / Ai ResearcherWolfram Jun 2017 - May 2018Champaign, Il, UsDeveloped deep learning technique based on sequence-to-sequence LSTMs with attention for converting natural language queries to precise machine-readable syntax in order to improve the WolframAlpha computational knowledge engine -
Graduate Research AssistantNational Center For Supercomputing Applications Aug 2015 - May 2018Urbana, Illinois, UsPioneered the application of deep learning in gravitational wave astrophysics as a member of the Nobel-prize winning LIGO group. Developed the first deep convolutional neural networks trained with gravitational waveforms and numerical relativity HPC simulations of merging black holes using the Einstein Toolkit on the petascale Blue Waters supercomputer, to build a real-time gravitational wave detection pipeline for LIGO.Published 5 first-author peer-reviewed papers and over 20 co-authored articles. Won the ACM Student Research Competition, the NVIDIA Graduate Fellowship, the CSE Fellowship, as well as several best paper and poster awards -
Research FellowLos Alamos National Laboratory May 2016 - Aug 2016Los Alamos, Nm, UsSelected as a Co-Design Fellow. Worked on HPC Smoothed Particle Hydrodynamics (SPH) simulations of neutron star mergers for studying kilonovae and r-process nucleosynthesis in the ejecta using supercomputers.Augmented the 2HOT HPC library by adding tabulated equations-of-state and optimized the nearest neighbor search algorithm by implementing domain-partitioning schemes based on Hilbert ordering using Charm++ and STAPL -
Research AssistantNonlinear Dynamics Lab, Department Of Physics, Iit Bombay Jul 2014 - Jun 2015Worked on computational nonlinear dynamics and chaos research projects with Prof. Punit Parmananda. Wrote senior undergraduate thesis on numerical simulations of Chimera States in systems of coupled mercury beating heart oscillators.
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Research InternUniversity Of Notre Dame May 2014 - Jul 2014Notre Dame, In, UsWorked on numerically analyzing the magnetohydrodynamic stability of astrophysical jets with Prof. Dinshaw Balsara and his group. Performed both symbolic computations with Mathematica and numerical simulations on parallel HPC clusters in C++/Fortran. Co-authored a journal publication
Daniel George, Ph.D. Skills
Daniel George, Ph.D. Education Details
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University Of Illinois Urbana-ChampaignAi / Astrophysics -
Indian Institute Of Technology, BombayEngineering Physics -
University Of Illinois Urbana-ChampaignAstronomy And Astrophysics -
Gregorian Public School - India
Frequently Asked Questions about Daniel George, Ph.D.
What company does Daniel George, Ph.D. work for?
Daniel George, Ph.D. works for Twinmind
What is Daniel George, Ph.D.'s role at the current company?
Daniel George, Ph.D.'s current role is Cofounder and CEO.
What is Daniel George, Ph.D.'s email address?
Daniel George, Ph.D.'s email address is da****@****ail.com
What is Daniel George, Ph.D.'s direct phone number?
Daniel George, Ph.D.'s direct phone number is +121772*****
What schools did Daniel George, Ph.D. attend?
Daniel George, Ph.D. attended University Of Illinois Urbana-Champaign, Indian Institute Of Technology, Bombay, University Of Illinois Urbana-Champaign, Gregorian Public School - India.
What skills is Daniel George, Ph.D. known for?
Daniel George, Ph.D. has skills like Machine Learning, Astrophysics, Wolfram Language, Mathematica, Supercomputing, General Relativity, Python, Deep Learning, C++, Computational Physics, Natural Language Processing, Data Science.
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