Brandon Edwards

According to our database, Brandon Edwards authored at least 13 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

A Technical Policy Blueprint for Trustworthy Decentralized AI.

Hasan Kassem, Sergen Cansiz, Brandon Edwards, Patrick Foley, Inken Hagestedt, Taeho Jung, Prakash Narayana Moorthy, Michael O'Connor, Bruno Rodrigues, Holger Roth, Micah J. Sheller, Dimitris Stripelis, Marc Vesin, Renato Umeton, Mic Bowman, Alexandros Karargyris

CoRR, December, 2025

The MICCAI Federated Tumor Segmentation (FeTS) Challenge 2024: Efficient and Robust Aggregation Methods for Federated Learning.

Akis Linardos, Sarthak Pati, Ujjwal Baid, Brandon Edwards, Patrick Foley, Kevin Ta, Verena Chung, Micah Sheller, Muhammad Irfan Khan, Mojtaba Jafaritadi, Elina Kontio, Suleiman A. Khan, Leon Mächler, Ivan Ezhov, Suprosanna Shit, Johannes C. Paetzold, Gustav Grimberg, Manuel Nickel, David Naccache, Vasilis Siomos, Jonathan Passerat-Palmbach, Giacomo Tarroni, Daewoon Kim, Leonard L. Klausmann, Prashant Shah, Bjoern H. Menze, Dimitrios Makris, Spyridon Bakas

CoRR, December, 2025

2024

Federated learning as a catalyst for digital healthcare innovations.

Guang Yang, Brandon Edwards, Spyridon Bakas, Qi Dou, Daguang Xu, Xiaoxiao Li, Wanying Wang

Patterns, 2024

Privacy preservation for federated learning in health care.

Sarthak Pati, Sourav Kumar, Amokh Varma, Brandon Edwards, Charles Lu, Liangqiong Qu, Justin J. Wang, Anantharaman Lakshminarayanan, Shih-han Wang, Micah J. Sheller, Ken Chang, Praveer Singh, Daniel L. Rubin, Jayashree Kalpathy-Cramer, Spyridon Bakas

Patterns, 2024

Privacy-Enhancing Collaborative Information Sharing through Federated Learning - A Case of the Insurance Industry.

Panyi Dong, Zhiyu Quan, Brandon Edwards, Hans Shih-Han Wang, Runhuan Feng, Tianyang Wang, Patrick Foley, Prashant Shah

CoRR, 2024

Efficient Privacy Auditing in Federated Learning.

Hongyan Chang, Brandon Edwards, Anindya S. Paul, Reza Shokri

Proceedings of the 33rd USENIX Security Symposium, 2024

2023

Attri-Fed: A GIB Framework for Attribute-Based Privacy and Communication-Efficient Federated Learning.

Ahmet Faruk Saz, Yashas Malur Saidutta, Faramarz Fekri, Mustafa Riza Akdeniz, Brandon Edwards, Nageen Himayat

Proceedings of the 24th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2023

2022

Federated Learning Enables Big Data for Rare Cancer Boundary Detection.

Sarthak Pati, Ujjwal Baid, Brandon Edwards, Micah J. Sheller, Hans Shih-Han Wang, G. Anthony Reina, Patrick Foley, Alexey Gruzdev, Deepthi Karkada, Christos Davatzikos, Chiharu Sako, Satyam Ghodasara, Michel Bilello, Suyash Mohan, Philipp Vollmuth, Gianluca Brugnara, Chandrakanth J. Preetha, Felix Sahm, Klaus H. Maier-Hein, Maximilian Zenk, Martin Bendszus, Wolfgang Wick, Evan Calabrese, Jeffrey D. Rudie, Javier E. Villanueva-Meyer, Soonmee Cha, Madhura Ingalhalikar, Manali Jadhav, Umang Pandey, Jitender Saini, John Garrett, Matthew E. Larson, Robert Jeraj, Stuart Currie, Russell Frood, Kavi Fatania, Raymond Y. Huang, Ken Chang, Carmen Balaña Quintero, Jaume Capellades, Josep Puig, Johannes Trenkler, Josef Pichler, Georg Necker, Andreas Haunschmidt, Stephan Meckel, Gaurav Shukla, Spencer Liem, Gregory S. Alexander, et al.

CoRR, 2022

2021

OpenFL: An open-source framework for Federated Learning.

G. Anthony Reina, Alexey Gruzdev, Patrick Foley, Olga Perepelkina, Mansi Sharma, Igor Davidyuk, Ilya Trushkin, Maksim Radionov, Aleksandr Mokrov, Dmitry Agapov, Jason Martin, Brandon Edwards, Micah J. Sheller, Sarthak Pati, Prakash Narayana Moorthy, Hans Shih-Han Wang, Prashant Shah, Spyridon Bakas

CoRR, 2021

The Federated Tumor Segmentation (FeTS) Challenge.

Sarthak Pati, Ujjwal Baid, Maximilian Zenk, Brandon Edwards, Micah J. Sheller, G. Anthony Reina, Patrick Foley, Alexey Gruzdev, Jason Martin, Shadi Albarqouni, Yong Chen, Russell Taki Shinohara, Annika Reinke, David Zimmerer, John B. Freymann, Justin S. Kirby, Christos Davatzikos, Rivka R. Colen, Aikaterini Kotrotsou, Daniel S. Marcus, Mikhail Milchenko, Arash Nazeri, Hassan M. Fathallah-Shaykh, Roland Wiest, András Jakab, Marc-André Weber, Abhishek Mahajan, Lena Maier-Hein, Jens Kleesiek, Bjoern H. Menze, Klaus H. Maier-Hein, Spyridon Bakas

CoRR, 2021

GaNDLF: A Generally Nuanced Deep Learning Framework for Scalable End-to-End Clinical Workflows in Medical Imaging.

Sarthak Pati, Siddhesh P. Thakur, Megh Bhalerao, Ujjwal Baid, Caleb M. Grenko, Brandon Edwards, Micah J. Sheller, Jose Agraz, Bhakti Baheti, Vishnu Bashyam, Parth Sharma, Babak Haghighi, Aimilia Gastounioti, Mark Bergman, Bjoern H. Menze, Despina Kontos, Christos Davatzikos, Spyridon Bakas

CoRR, 2021

2020

Toward Few-step Adversarial Training from a Frequency Perspective.

Hans Shih-Han Wang, Cory Cornelius, Brandon Edwards, Jason Martin

CoRR, 2020

2018

Multi-institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation.

Micah J. Sheller, G. Anthony Reina, Brandon Edwards, Jason Martin, Spyridon Bakas

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018