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Roberts Awardees

2023 - 2024 Awarded Projects

2022 - 2023 Awarded Projects
 

Combining DEFI & AI for Intelligent Credit Scoring  

Transforming the decentralized finance landscape and alleviating transaction risk via quantifying participant’s credit  

Project team: Leandros Tassiulas - Electrical Engineering, with Georgios Palaiokrassas, Jason Ofeidis, Aosong Feng, and Dr. Farooq Anjum
 

CRAIG: Computed Radiology Reporting with AI-assisted Generation

AI-assisted radiology report simplification & summarization

Project team: Arman Cohan - Computer Science / Sophie Chheang - Clinical Radiology and Biomedical Imaging (Co-PIs)

Deep learning for quantification of lower extremity flow & viability  

Project team: Albert Sinusas, MD - Biomedical Engineering, with Chi Liu, Carlos Mena, Kim Smolderen, Stephanie Thorn, Xenophon Papademetris

Disaggregated Clouds

Cost-effective and performant cloud platform and a radically new network-centric OS to manage it

Project team: Anurag Khandelwal - Computer Science, with Grace Jia, Seung-seob Lee, Ziming Mao, Yupeng Tang, Yanpeng Yu

Lagrange

Non-interactive cross-chain state proofs  

Project team: Charalampos Papamanthou - Computer Science, with Amir Rezaizadeh, co-founder and Ismael Hishon-Rezaizadeh, co-founder

Moir AI Sciences

Controlling cellular dynamics with artificial intelligence

Project team: Smita Krishnaswamy - Computer Science & Genetics, with Christine Chaffer, Manik Kuchroo

Physics_Based Algorithm MRI

Inexpensive large-scale AI for prostate cancer using MR physics

Project team: Gigi Galiana & Hemant Tagare - Radiology & Biomedical Imaging and Biomedical Engineering (Co-PIs), with Jeff Weinreb, John Onofrey 

SNIP / SNAP

User-centric presentation of hybrid information using large language models

Project team: Dragomir Radev - Computer Science, with Yixin Liu, Linyong Nan, Yujie Qiao, Wenfei Zhou 

ZIPNet

Anonymous Broadcast Made Practical with TEEs

Project team: Fan Zhang - Computer Science, with and Ian Miers (Asst. Prof at UMD)

ZK4ALL

Establishing a standard programming framework for working efficiently with cloud-ready zero-knowledge proofs

Project team: Ruzica Piskac - Computer Science with Timos Antonopoulos, Ning Luo, Yuyang Sang, Xiao Wang