Vahid Tarokh

Harvard University, Harvard University Press, Duke University

Papers

Total Citations

H-Index

About

Vahid Tarokh is a pioneering researcher whose work spans the intersection of biomedical engineering, wireless communications, and artificial intelligence. His key research areas include intra-body electromagnetic propagation, medical microrobotics, and offline reinforcement learning for robotics. Tarokh’s major contributions include groundbreaking experimental and modeling work on the effective complex permittivity of human tissues, which is critical for enabling radio-frequency tracking of medical micro-robots in minimally invasive procedures. He also developed adaptive localization techniques for wireless capsule endoscopy, advancing the field of gastrointestinal diagnostics by allowing precise tracking of capsules inside the body. More recently, Tarokh has ventured into AI-driven robotics, proposing a novel method to improve Decision Transformers for offline reinforcement learning in stochastic environments—a common challenge in real-world robotic applications. While his citation counts are still growing, with his most-cited paper reaching 9 citations, his work represents foundational steps in merging electromagnetic theory with biomedical robotics. His notable achievements include pioneering in vivo and in situ measurement methodologies that challenge the oversimplified homogeneous-body assumption, and his adaptive localization techniques have opened new avenues for non-invasive medical diagnostics.