Samuel G. Rodriques Email & Phone Number
@crick.ac.uk
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Who is Samuel G. Rodriques? Overview
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Samuel G. Rodriques is listed as Building an AI Scientist at FutureHouse, Inc. at FutureHouse, based in San Francisco, California, United States. AeroLeads shows a work email signal at crick.ac.uk and a matched LinkedIn profile for Samuel G. Rodriques.
Samuel G. Rodriques previously worked as Director and CEO at Futurehouse and Group Leader at The Francis Crick Institute. Samuel G. Rodriques holds Doctor Of Philosophy (Ph.D.), Physics from Massachusetts Institute Of Technology.
Email format at FutureHouse
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AeroLeads found 1 current-domain work email signal for Samuel G. Rodriques. Compare company email patterns before reaching out.
About Samuel G. Rodriques
I am an inventor and entrepreneur. In 2023, I launched FutureHouse, a new research lab in San Francisco focused on building an AI Scientist to accelerate research in biology and other complex sciences. I want science to move faster.Theoretical physics => Bioengineering => AI for scienceGrad student => Academic => Founder.
Listed skills include Physics, Applied Mathematics, Python, Research, and 12 others.
Samuel G. Rodriques's current company
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Samuel G. Rodriques work experience
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Group Leader
CurrentI ran an academic bioengineering lab, the Applied Biotechnology Lab, at the Francis Crick Institute. My lab will shut down in March 2025.
Entrepreneur In Residence
Researcher
I developed the Focused Research Organization model and worked on trying to launch a Focused Research Organization for connectomics.
Graduate Student (Physics)
I worked on a diverse array of projects in the Synthetic Neurobiology Group, including projects for :-Connectomics. Work is still in progress!-A method to record the history of gene expression into the sequence of RNA. Still in progress!-Recording neural activity at the single-cell level in humans, without damaging brain tissue. See: https://tinyurl.com/y2bd5kbb-A revolutionary new approach to 3D nanofabrication. See: https://science.sciencemag.org/content/362/6420/1281.abstract-A high-throughput method to map the distribution of cell types in a tissue sample. See: https://science.sciencemag.org/content/363/6434/1463.abstract
Master'S Student
As a Churchill Scholar, I worked in the Computational and Biological Learning Laboratory (CBL) in the Engineering Department at the University of Cambridge.-Studied the algorithms that the brain uses for predictive control of motor systems, with the goal of designing prostheses that can recapitulate the behavior of biological limbs.-On the side, applied insights from quantum information theory to gain new insights in classical information theory. (See "Probability Theory without Bayes' Rule," below. One additional manuscript is in preparation.)Through this research, I came to appreciate that neuroscience is fundamentally data-limited, and that we lack the tools required to obtain the high-resolution, high-coverage datasets that are necessary to decode the operation of the human brain.
Undergraduate (Physics)
I studied theoretical physics at Haverford College, and researched methods for calculating quantum entanglement. Quantum entanglement is a computational resource that distinguishes quantum mechanics from classical mechanics, and the ability to calculate upper and lower bounds on entanglement is essential for the design of quantum computers and the analysis of many-body quantum systems.-Applied traditional algorithms for calculating upper bounds on entanglement to study the role of entanglement in photosynthesis.-Developed a new algorithm for calculating an upper bound on entanglement that scales linearly in the size of the system, compared with traditional algorithms that scale with the 8th power of the size.-Performed the first upper bound calculations on arbitrary systems of 3 qubits.-Developed the only existing algorithm to calculate the true value of entanglement in an arbitrary mixed quantum state. (Paper in preparation.)
Undergraduate (Junior Year Abroad)
I spent my junior year abroad at Fitzwilliam College, University of Cambridge, taking courses in Part II Physics (final year undergraduate) and Part III Mathematics (graduate level):Exams:-Relativity (Part II Physics)-Thermal and Statistical Physics (Part II Physics)-Quantum Information Theory (Part III Mathematics)-Quantum Field Theory (Part III Mathematics)-Advanced Quantum Field Theory (Part III Mathematics)In addition, I wrote a Master's thesis entitled "Entanglement and Entropy." I fulfilled the requirements for a Master's of Advanced Studies in Mathematics, but there was a conflict in the University's Statutes and Ordinances that prevented them from awarding me the degree.
Samuel G. Rodriques education
Doctor Of Philosophy (Ph.D.), Physics
Mphil In Engineering, Neuroscience
Bachelor Of Science (Bs), Physics
Physics, Maths
Frequently asked questions about Samuel G. Rodriques
Quick answers generated from the profile data available on this page.
What company does Samuel G. Rodriques work for?
Samuel G. Rodriques works for FutureHouse.
What is Samuel G. Rodriques's role at FutureHouse?
Samuel G. Rodriques is listed as Building an AI Scientist at FutureHouse, Inc. at FutureHouse.
What is Samuel G. Rodriques's email address?
AeroLeads has found 1 work email signal at @crick.ac.uk for Samuel G. Rodriques at FutureHouse.
Where is Samuel G. Rodriques based?
Samuel G. Rodriques is based in San Francisco, California, United States while working with FutureHouse.
What companies has Samuel G. Rodriques worked for?
Samuel G. Rodriques has worked for Futurehouse, The Francis Crick Institute, Petri, Massachusetts Institute Of Technology, and University Of Cambridge.
How can I contact Samuel G. Rodriques?
You can use AeroLeads to view verified contact signals for Samuel G. Rodriques at FutureHouse, including work email, phone, and LinkedIn data when available.
What schools did Samuel G. Rodriques attend?
Samuel G. Rodriques holds Doctor Of Philosophy (Ph.D.), Physics from Massachusetts Institute Of Technology.
What skills is Samuel G. Rodriques known for?
Samuel G. Rodriques is listed with skills including Physics, Applied Mathematics, Python, Research, Mathematica, Matlab, Theoretical Physics, and Mathematical Modeling.
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