96 citations · 99 across the 10 of their papers we have counts for
12 papers
Extremal Chowla sets and their linear analogues: A human-AI mathematical investigation using Co-Scientist
Mohsen Aliabadi, Keith Driscoll, Elliot Krop +3
We introduce an extremal invariant associated with Chowla-type order conditions in finite groups. A nonempty subset of a finite group is called a Chowla set if every elemen…
An AI Co-Data-Scientist for Prioritizing Candidate Biomarkers from Wearable Sensor Data
Yubin Kim, Salman Rahman, Samuel Schmidgall +33
Wearable devices generate continuous physiological and behavioral data, but converting these signals into clinically reviewable biomarker hypotheses remains labor-intensive. We int…
A prospective clinical feasibility study of a conversational diagnostic AI in an ambulatory primary care clinic
Peter Brodeur, Jacob M. Koshy, Anil Palepu +45
Large language model (LLM)-based AI systems have shown promise for patient-facing diagnostic and management conversations in simulated settings. Translating these systems into clin…
Complementary Human-AI Clinical Reasoning in Ophthalmology
Mertcan Sevgi, Fares Antaki, Abdullah Zafar Khan +26
Vision impairment and blindness are a major global health challenge where gaps in the ophthalmology workforce limit access to specialist care. We evaluate AMIE, a medically fine-tu…
Efficient and Privacy-Preserving Binary Dot Product via Multi-Party Computation
Fatemeh Jafarian Dehkordi, Elahe Vedadi, Alireza Feizbakhsh +2
Striking a balance between protecting data privacy and enabling collaborative computation is a critical challenge for distributed machine learning. While privacy-preserving techniq…
Advancing Conversational Diagnostic AI with Multimodal Reasoning
Khaled Saab, Jan Freyberg, Chunjong Park +33
Large Language Models (LLMs) have demonstrated great potential for conducting diagnostic conversations but evaluation has been largely limited to language-only interactions, deviat…
Capabilities of Gemini Models in Medicine
Khaled Saab, Tao Tu, Wei-Hung Weng +64
Excellence in a wide variety of medical applications poses considerable challenges for AI, requiring advanced reasoning, access to up-to-date medical knowledge and understanding of…
Federated Variational Inference: Towards Improved Personalization and Generalization
Elahe Vedadi, Joshua V. Dillon, Philip Andrew Mansfield +3
Conventional federated learning algorithms train a single global model by leveraging all participating clients' data. However, due to heterogeneity in client generative distributio…
Efficient Coded Multi-Party Computation at Edge Networks
Elahe Vedadi, Yasaman Keshtkarjahromi, Hulya Seferoglu
Multi-party computation (MPC) is promising for designing privacy-preserving machine learning algorithms at edge networks. An emerging approach is coded-MPC (CMPC), which advocates…
Adaptive Gap Entangled Polynomial Coding for Multi-Party Computation at the Edge
Elahe Vedadi, Yasaman Keshtkarjahromi, Hulya Seferoglu
Multi-party computation (MPC) is promising for designing privacy-preserving machine learning algorithms at edge networks. An emerging approach is coded-MPC (CMPC), which advocates…
PolyDot Coded Privacy Preserving Multi-Party Computation at the Edge
Elahe Vedadi, Yasaman Keshtkarjahromi, Hulya Seferoglu
We investigate the problem of privacy preserving distributed matrix multiplication in edge networks using multi-party computation (MPC). Coded multi-party computation (CMPC) is an…
Adaptive Coding for Matrix Multiplication at Edge Networks
Elahe Vedadi, Hulya Seferoglu
Edge computing is emerging as a new paradigm to allow processing data at the edge of the network, where data is typically generated and collected, by exploiting multiple devices at…