Stanford University
Showing 1,751-1,760 of 6,598 Results
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Raul Garreta Tompson
Graduate, Stanford Center for Professional Development
BioI'm a tech entrepreneur, passionate about Artificial Intelligence (AI), with extensive experience in Machine Learning, Natural Language Processing and Robotics.
I started in Machine Learning back in 2005, building an artificial Go player with Neural Networks and Reinforcement Learning. That was ten years before AlphaGo used the same principles :)
Then worked on a bunch of companies including programming video games and implementing firmware for implantable medical devices.
In 2007 I started lecturing Machine Learning and NLP as a professor at the Computer Science Institute of UDELAR for 9 years.
In 2009 I co-founded Tryolabs, Python dev shop specialized in building products with AI.
In 2013 I co-authored with PhD Guillermo Moncecchi a technical book about an introduction to applied Machine Learning with Python programming language.
In 2014 I founded and led MonkeyLearn to make Machine Learning and NLP accessible to all companies and users. I raised a total of $4.2m from top tier Venture Capital and angel investors in Silicon Valley. I led all R&D and business operations, selling our product to top companies in the US.
In 2020 I finished my master thesis in Artificial Intelligence, "Data Efficient Deep Learning Models for Text Classification", where I compared multiple state of the art models, including language models.
In 2022 I exited MonkeyLearn to Medallia and joined as Sr Director leading AI research and development.
I'm an active investor, I invest in public markets but also in private companies, particularly tech startups and software product companies. I'm also LP in two venture capital funds, Uncork Capital and Garuda Ventures.
Currently researching and building on Artificial Intelligence for Robotics. -
Matthias Garten
Assistant Professor of Microbiology and Immunology and of Bioengineering
Current Research and Scholarly InterestsWith a creative, collaborative, biophysical mindset, we aim to understand the ability non-model organisms to interface with environment to a point at which we can exploit the mechanisms finding cures against diseases and use the mechanisms as tools that we can use to engineer the environment. By developing approaches that allow a quantitative understanding and manipulation of molecular transport our research makes non-model organisms accessible to researchers and engineers.
Specifically, we are studying how the malaria parasite takes control over red blood cells. By learning the biophysical principles of transport in between the host and the parasite we can design ways to kill the parasite or exploit it to reengineer red blood cells. The transport we study is broadly encompassing everything from ions to lipids and proteins. We use variations of quantitative microscopy and electrophysiology to gain insight into the unique strategies the parasite evolved to survive. -
Aimee Garza
Faculty Administrator, Computer Science
Current Role at StanfordCS DEI Program Coordinator
