Early-Career Funding for Improving the Long-Term Future — Scholarship Support (2022)
- Organization:
- Early-career funding for individuals interested in improving the long-term future
- Award Date:
- 02/2022
- Amount:
- $3,486,983
- Purpose:
- To support work and study related to improving the long-term future.
Open Philanthropy recommended a total of approximately $3,486,983 over two years in flexible support to enable early-career individuals to pursue work and study related to improving the long-term future.[1] Open Philanthropy sought applications for this funding here. Recipients include:
- Fatima Afzali, self-study related to AI safety
- Emefa Agawu, career development
- Liam Alexander, 12-month think tank placement
- Riley Baird, Bachelor of Science (Honours) in post-quantum cryptography at UNSW Canberra
- Francesco Barbera, Master’s in Machine Learning at the University of Cambridge
- Christina Barta, JD at Columbia Law School with a focus on emerging tech governance
- Caroline Baumöhl, Master’s in Practical Ethics at Oxford University
- Julia Broden, living expenses during a Master's in Statistics and Data Science at LMU Munich
- Thomas Bueler-Faudree, Congressional internship
- Mattia Cecchinato, DPhil in Philosophy at the University of Oxford
- Alan Chan, PhD in Computer Science at Mila
- Jonathan Cunningham, Master's in Economics at the University of Texas at Austin
- Harrison Durland, Internship with a member of Congress
- Nicholas Emery, teaching buyout for PhD in Political Economy at UCLA
- Tim Farrelly, self-study related to AI safety
- Olumurejiwa Fatunde, coding bootcamp and Fellowship in Global Journalism at the University of Toronto
- Connall Garrod, Master’s in Machine Learning and Machine Intelligence at the University of Cambridge
- Daniel Gitu, self-study related to AI safety
- Manon Gouiran, research on moral circle expansion at the University of Edinburgh
- Aidan Goth, self-study related to AI safety and global priorities, and the first year of a PhD in Economics
- Ben Greenberg, self-study related to AI safety
- Benjamin Harack, PhD in International Relations at the University of Oxford
- Julian Hazell, self-study related to AI governance
- Fynn Heide, self-study and research on international politics and policy
- Max Heitmann, BPhil in Philosophy at the University of Oxford
- Robert Huben, self-study and blogging related to AI safety
- Gemma Irving, Master's in International Relations at King's College London
- Ole Jorgensen, Master's in Machine Learning at University College London
- Bartu Kaleagasi, Master's in International Affairs at Columbia University
- Jacek Karwowski, PhD in Computer Science at the University of Oxford
- Konstantinos Konstantinidis, self-study related to nuclear risk
- Petra Kosonen, PhD in philosophy at the University of Oxford
- Kay Kozaronek, self-study related to AI safety
- Sabrina Küspert, MSc in Economics for Development at the University of Oxford
- Joseph Kwon, work on projects related to AI safety
- Ali Ladak, PhD in Psychology at the University of Edinburgh
- Chris Lakin, career development
- Patrick Leask, Master's in Computer Science at the University of Liverpool
- Gavin Lee, Research visit at Ought
- Jiamin Lim, Master’s in Machine Learning at Australia National University
- Hain Luud, Master’s in Cybersecurity at ETH Zurich
- Aidan Mackenzie, congressional internship
- Yusuf Mahmood, JD at Harvard
- Fauna Mahootian, self-study related to deep learning and AI safety
- Mantas Mazeika, PhD in Computer Science at the University of Illinois Urbana-Champaign
- Fergus McCormack, self-study related to AI governance
- Brian Muhia, self-study related to AI safety
- Nikhil Mulani, self-study related to corporate governance and longtermist investing
- Thomas Orton, PhD in Computer Science at the University of Oxford
- Jack Parker, Master’s in Data Analytics and Machine Learning at Duke University
- Balint Pataki, Master’s in Public Policy at the University of Oxford
- Tarmo Pungas, Master's in Artificial Intelligence at the University of Amsterdam
- Arvind Raghavan, internship with the Causal AI Lab at Columbia University
- Javier Ramirez, Master's in Machine Learning at ETH Zurich
- Tilman Räuker, self-study related to AI safety
- Jeremy Rubinoff, self-study related to AI safety
- María Sánchez, Master's in Mathematics, Vision, and Learning at the Institut Polytechnique de Paris
- Anita Sangha, self-study related to existential risks and longtermism
- Elias Schmied, self-study related to AI safety
- Alexandra Souly, Master's in Machine Learning at University College London
- Oliver Sourbut, PhD in Autonomous Intelligent Machines and Systems at the University of Oxford
- Holly Stevens, internship at Brookings Institution
- Mrigyen Sawant, Master's in Machine Learning at TU Munich
- Aaron Tucker, PhD in Computer Science at Cornell University
- Anish Upadhayay, participation in an online course on deep reinforcement learning
- Gautam Vyas — Master’s in Economics at the University of Oxford
- Junshi Wang, research internship on causal inference at Cambridge and semester abroad at the University of California, Berkeley
- Daphne Will, self-study related to AI safety
- Michael Yang, self-study related to technology policy and AI policy
- Rustam Zayanov, Master’s in Data Science and Engineering at Instituto Superior Técnico
- Angela Zhong, internship at the United States Mission to the United Nations
Open Philanthropy is still in the process of finalizing scholarship recipients and will update the list above as recipients are confirmed.
This falls under Open Philanthropy's work aimed at growing the community of people working to improve the long-run future.