Daniel George, Ph.D. Email & Phone Number

Palo Alto, CA, US

Palo Alto, CA, US

The 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)

New York, NY, US

Led 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).

Led 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.

Worked 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

Champaign, IL, US

Developed 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

Urbana, Illinois, US

Pioneered 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.

Los Alamos, NM, US

Selected 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.

Worked 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.

Notre Dame, IN, US

Worked 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

Doctor Of Philosophy (Phd), Ai / Astrophysics

Bachelor Of Technology (Btech), Engineering Physics

Master Of Science - Ms, Astronomy And Astrophysics

Education record