Savannah Jennifer Thais

Assistant Professor, City University of New York

Joined

August 2021

Names

Savannah Jennifer Thais (Preferred)

Savannah Thais

Emails

****@gmail.com (Confirmed)

Personal Links

Google Scholar

DBLP

Career & Education History

Assistant Professor

City University of New York (cuny.edu)

2025 – Present

Principal Researcher

Columbia University (columbia.edu)

2022 – 2025

Researcher

Princeton University (princeton.edu)

2019 – 2022

PhD student

Yale University (yale.edu)

2014 – 2019

Advisors, Relations & Conflicts

Postdoc Advisor

G.J. Peter Elmer

2019 – 2022

Expertise

ai policy

ai governance

ai regulation

an and policy

ai for policy

2022 – Present

geometric deep learning

graph neural networks

2019 – Present

ai for science

ai and physics

inductive bias

philosophy of science

2016 – Present

Publications

Holonic Science: A New Framework for Benchmarking AI Scientists
Nathan Suri, Savannah Jennifer Thais
- NeurIPS2025-AI4Science Poster
- Readers: Everyone
Integration of Generative AI in the Digital Markets Act: Contestability and Fairness from a Cross-Disciplinary Perspective
Ayse Gizem Yasar, Andrew Chong, Evan Dong, Thomas Krendl Gilbert, Carlos Mougan, Xudong Shen, Shubham Singh, Ana-Andreea Stoica, Savannah Jennifer Thais
- RegML 2024
- Readers: Everyone
AI Ethics Education for Scientists
Savannah Jennifer Thais
- NeurIPS2023-AI4Science Poster
- Readers: Everyone
Equivariant Graph Neural Networks for Charged Particle Tracking
Daniel Murnane, Savannah Thais, Ameya Thete
- Published: 01 Jan 2023, Last Modified: 12 May 2023
- CoRR 2023
- Readers: Everyone
Graph Neural Networks in Particle Physics: Implementations, Innovations, and Challenges
Savannah Thais, Paolo Calafiura, Grigorios Chachamis, Gage DeZoort, Javier M. Duarte, Sanmay Ganguly, Michael Kagan, Daniel Murnane, Mark S. Neubauer, Kazuhiro Terao
- 2022 (modified: 06 Jun 2022)
- CoRR 2022
- Readers: Everyone
Applications and Techniques for Fast Machine Learning in Science
Allison McCarn Deiana, Nhan Tran, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Scott Hauck, Mia Liu, Mark S. Neubauer, Jennifer Ngadiuba, Seda Ogrenci Memik, Maurizio Pierini, Thea Aarrestad, Steffen Bähr, Jürgen Becker, Anne-Sophie Berthold, Richard J. Bonventre, Tomas E. Muller Bravo, Markus Diefenthaler et al. (27 additional authors not shown)
- 2022 (modified: 06 Jun 2022)
- Frontiers Big Data 2022
- Readers: Everyone
Graph Neural Networks for Charged Particle Tracking on FPGAs
Abdelrahman Elabd, Vesal Razavimaleki, Shi-Yu Huang, Javier M. Duarte, Markus Atkinson, Gage DeZoort, Peter Elmer, Scott Hauck, Jin-Xuan Hu, Shih-Chieh Hsu, Bo-Cheng Lai, Mark S. Neubauer, Isobel Ojalvo, Savannah Thais, Matthew Trahms
- 2022 (modified: 06 Jun 2022)
- Frontiers Big Data 2022
- Readers: Everyone
Symmetry Group Equivariant Architectures for Physics
Alexander Bogatskiy, Sanmay Ganguly, Thomas Kipf, Risi Kondor, David W. Miller, Daniel Murnane, Jan T. Offermann, Mariel Pettee, Phiala Shanahan, Chase Shimmin, Savannah Thais
- 2022 (modified: 16 Apr 2023)
- CoRR 2022
- Readers: Everyone
Data Science and Machine Learning in Education
Gabriele Benelli, Thomas Y. Chen, Javier M. Duarte, Matthew Feickert, Matthew J. Graham, Lindsey Gray, Dan Hackett, Philip C. Harris, Shih-Chieh Hsu, Gregor Kasieczka, Elham E Khoda, Matthias Komm, Mia Liu, Mark S. Neubauer, Scarlet Norberg, Alexx Perloff, Marcel Rieger, Claire Savard, Kazuhiro Terao, Savannah Thais et al. (3 additional authors not shown)
- 2022 (modified: 24 Apr 2023)
- CoRR 2022
- Readers: Everyone
Understanding Historical, Socio-Economic, and Policy Contributions to COVID-19 Health Inequities
Savannah Thais, Shaine Leibowitz, Allie Saizan, Ashay Singh
- Published: 01 Jan 2022, Last Modified: 12 May 2023
- ISCRAM 2022
- Readers: Everyone

View all 22 publications

Co-Authors

View all 327 co-authors