Jonathan Mckinney Email & Phone Number | 15 years experience developing machine learning models, including AutoML frameworks and training and deploying large-language models. * #2 top LLM developer in world in 2023: https://huyenchip.com/llama-devs * Co-developed h2oGPT at h2o.ai: https://github.com/h2oai/h2ogpt -- Large Language training and generation framework including chatbot. * Co-developed DriverlessAI at h2o.ai -- AutoML framework for multi-modal models (NLP, image, tabular, etc.) 20 years of experience building world-class mathematical algorithms and astrophysical models, and executing them on massively parallel systems to explain and predict real-world data. * >100 peer-reviewed scientific publications in top journals, including Science * >10000 refereed citations with refereed h-index > 50 (http://bit.ly/1Pve92Y and http://bit.ly/1PAsiKR) * ~3 million in grant funds as Principle Investigator, ~9 million as co-PI * ~15 students advised (at Harvard/Stanford, now with prestigious fellowships) * ~20 graduate and undergraduate courses taught * ~70 invited conference talks and public lectures * ~4 international teams, as senior member, involving ~500 people * ~120 million cpu-hours of computing time awarded, worth ~4 million Designed and Built: http://github.com/pseudotensor * Deep Learning Projects: CNNs and LSTMs to predict video, faster convergence for gradient descent, and new architectures. Using Tensorflow, Theano, and Matlab. Astrophysics Simulation Projects: * Built: (90% as designer and developer): HARMRAD/HARM: World-leading massively parallel general relativistic radiation plasma simulation and analysis codes (600k lines of code). Impact: used by >50 researchers in >100 articles. * Built: (95% as primary designer/developer): Many projects: fluid, radiation, optimization, nonlinear solving, signal processing, simulated annealing, Markov chain Monte Carlo, visualization. Impact: used by dozens of researchers in >100 articles. * Scaling: (as 100% designer/developer) Run on >100k cores, with petabytes of data * Languages/APIs used: C, Python, C++, Fortran, MPI, OpenMP, CUDA, OpenCL, OpenACC, Matlab/Mathematica and parallel debuggers (Intel Inspector) * Algorithm Projects: (as 100% designer/developer): tensor algebra solutions to general relativistic inversion problem, radiation/fluid numerical optimization, integro-PDE solvers

Jonathan Mckinney

15 years experience developing machine learning models, including AutoML frameworks and training and...
Mountain View, California, United States

*50 free lookup(s) per month.

No credit card required.

Jonathan Mckinney’s Email jonathan.mckinney@h2o.ai

Jonathan Mckinney’s Phone Numbers +1 650-227-****

Get JONATHAN’s Phone Number (For Free)

Social Media

Jonathan Mckinney’s Location Mountain View, California, United States

Jonathan Mckinney’s Current Industry H2o Ai

Jonathan Mckinney’s Prior Industry University Of Maryland | Stanford University | Slac National Accelerator Laboratory | Harvard University | University Of Illinois At Urbana Champaign

Not the Jonathan Mckinney you were looking for?

Find accurate emails & phone numbers for over 700M professionals.

Work Experience

H2o Ai

Director of Research

2017-03-01 00:00:00 - Present

University Of Maryland

Professor of Physics

2012-07-01 00:00:00 - 2019-12-01 00:00:00

Stanford University

Visiting Scholar

2016-12-01 00:00:00 - 2018-12-01 00:00:00

Slac National Accelerator Laboratory

SciDAC (Scientific Discovery through Advanced Computing) postdoc fellow

2010-01-01 00:00:00 - 2011-01-01 00:00:00

Harvard University

Harvard Institute for Theory and Computation (ITC) Postdoc Fellow

2004-09-01 00:00:00 - 2007-05-01 00:00:00

University Of Illinois At Urbana Champaign

NASA Graduate Fellow

1998-09-01 00:00:00 - 2004-09-01 00:00:00

Skills

No Skills Available

Languages

No Languages Available

FAQ About Jonathan Mckinney

Jonathan Mckinney is located at
Mountain View, California, United States

Jonathan Mckinney is a 15 years experience developing machine learning models, including AutoML frameworks and training and deploying large-language models. * #2 top LLM developer in world in 2023: https://huyenchip.com/llama-devs * Co-developed h2oGPT at h2o.ai: https://github.com/h2oai/h2ogpt -- Large Language training and generation framework including chatbot. * Co-developed DriverlessAI at h2o.ai -- AutoML framework for multi-modal models (NLP, image, tabular, etc.) 20 years of experience building world-class mathematical algorithms and astrophysical models, and executing them on massively parallel systems to explain and predict real-world data. * >100 peer-reviewed scientific publications in top journals, including Science * >10000 refereed citations with refereed h-index > 50 (http://bit.ly/1Pve92Y and http://bit.ly/1PAsiKR) * ~3 million in grant funds as Principle Investigator, ~9 million as co-PI * ~15 students advised (at Harvard/Stanford, now with prestigious fellowships) * ~20 graduate and undergraduate courses taught * ~70 invited conference talks and public lectures * ~4 international teams, as senior member, involving ~500 people * ~120 million cpu-hours of computing time awarded, worth ~4 million Designed and Built: http://github.com/pseudotensor * Deep Learning Projects: CNNs and LSTMs to predict video, faster convergence for gradient descent, and new architectures. Using Tensorflow, Theano, and Matlab. Astrophysics Simulation Projects: * Built: (90% as designer and developer): HARMRAD/HARM: World-leading massively parallel general relativistic radiation plasma simulation and analysis codes (600k lines of code). Impact: used by >50 researchers in >100 articles. * Built: (95% as primary designer/developer): Many projects: fluid, radiation, optimization, nonlinear solving, signal processing, simulated annealing, Markov chain Monte Carlo, visualization. Impact: used by dozens of researchers in >100 articles. * Scaling: (as 100% designer/developer) Run on >100k cores, with petabytes of data * Languages/APIs used: C, Python, C++, Fortran, MPI, OpenMP, CUDA, OpenCL, OpenACC, Matlab/Mathematica and parallel debuggers (Intel Inspector) * Algorithm Projects: (as 100% designer/developer): tensor algebra solutions to general relativistic inversion problem, radiation/fluid numerical optimization, integro-PDE solvers

Jonathan Mckinney currently works in the H2o Ai |

No Languages Available

Jonathan Mckinney has prior
experience in the following industries:
University Of Maryland | Stanford University | Slac National Accelerator Laboratory | Harvard University | University Of Illinois At Urbana Champaign

Jonathan Mckinney has the following professional experience:
H2o Ai | University Of Maryland | Stanford University | Slac National Accelerator Laboratory | Harvard University | University Of Illinois At Urbana Champaign