Stanford University
Showing 1,751-1,800 of 6,647 Results
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Lorenza Garau Paganella
Postdoctoral Scholar, Mechanical Engineering
BioLorenza was born in Italy in 1997 and is currently a postdoctoral fellow at Stanford University with Prof. Chaudhuri, supported by an SNSF fellowship. Her research focuses on engineering biomaterials to investigate cell–extracellular matrix interactions and mechanotransduction in 2D and 3D cell cultures, aiming to advance biomedical understanding of tissue remodeling and disease.
Lorenza obtained her PhD (2024) in Mechanical and Process Engineering from ETH Zurich, where she developed hydrogel scaffolds and protocols for protein isolation to study cell behavior in engineered microenvironments.
Before her PhD, Lorenza completed her MSc at ETH Zurich and BSc at University of Trieste in Process Engineering, graduating both cum laude. During this time her focus was on biomaterials for drug delivery which she complemented with an internship in Roche. She has worked in interdisciplinary teams combining engineering and biology and is motivated by research that bridges fundamental science with clinical impact. -
Harold Gardon
Masters Student in Aeronautics and Astronautics, admitted Autumn 2025
BioFrench student specializing in mechanical engineering. Passionate about basketball and aerospace, I am pursuing a Master of Science in Aeronautics and Astronautics and hope to specialize in rocket propulsion.
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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
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Danielle Juliane Gaspar
Student Services Officer 2, Computer Science
Current Role at StanfordStudent Services Officer 2, Computer Science Department
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Michael Genesereth
Associate Professor of Computer Science
BioGenesereth is most known for his work on Computational Logic and applications of that work in Enterprise Management, Computational Law, and General Game Playing. He is one of the founders of Teknowledge, CommerceNet, Mergent Systems, and Symbium. Genesereth is the director of the Logic Group at Stanford and the founder and research director of CodeX - the Stanford Center for Legal Informatics.
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Chen Geng
Ph.D. Student in Computer Science, admitted Autumn 2023
BioI'm a CS Ph.D. student at Stanford, advised by Prof. Jiajun Wu. My research lies at the intersection between Graphics, 3D Vision, and Machine Learning. Previously, I got my bachelor's degree in Computer Science at the School of Computer Science and Chu Kochen Honors College, Zhejiang University. During my undergraduate, I was fortunate to work closely with Prof. Xiaowei Zhou and Prof. Jiajun Wu on several research projects.
You can find more information on my homepage: https://chen-geng.com -
Madison George
Ph.D. Student in Bioengineering, admitted Autumn 2023
Current Research and Scholarly InterestsExertional compartment syndrome (ECS) is a painful condition characterized by abnormally high muscle compartment pressures induced by exercise. The diagnostic procedure for ECS requires the insertion of a needle into the muscle to directly quantify pressure, which is a barrier to both patients and clinicians. We will develop and evaluate new MRI technologies to (1) increase understanding of the pathophysiology of this condition and (2) Improve clinical diagnosis of ECS.
