Dr. Chayan Chatterjee is the A.I. for New Messengers Postdoctoral Fellow, jointly appointed by the Department of Physics and Astronomy and the Data Science Institute at Vanderbilt University. He earned his PhD in Physics from The University of Western Australia in 2023, following bachelor’s and master’s degrees in Physics from Presidency University, Kolkata, India. His research applies machine learning, frontier AI, and interpretable inference to gravitational-wave and multimessenger astronomy. His notable contributions include developing machine-learning pipelines for rapid gravitational-wave detection and sky localization, robust waveform reconstruction, and parameter estimation of binary black-hole mergers. He is a member of the LIGO–Virgo–KAGRA Collaboration and an affiliate of the ARC Centre of Excellence for Gravitational Wave Discovery (OzGrav), where he previously chaired the Gravitational-Wave Inference Program. He also serves as review chair for the LVK Data Quality Report. His honors include Vanderbilt University’s A.I. for New Messengers Postdoctoral Fellowship, the Lacy–Fischer Interdisciplinary Research Grant, the J. P. Macquart Best Student Talk Award, and the Australian Mathematical Sciences Institute Best Student Talk Award. Passionate about science communication and public outreach, he also received UWA’s Three Minute Thesis and People’s Choice awards.
Dr. Chayan Chatterjee is the A.I. for New Messengers Postdoctoral Fellow, jointly appointed by the Department of Physics and Astronomy and the Data Science Institute at Vanderbilt University. He earned his PhD in Physics from The University of Western Australia in 2023, following bachelor’s and master’s degrees in Physics from Presidency University, Kolkata, India. His research applies machine learning, frontier AI, and interpretable inference to gravitational-wave and multimessenger astronomy. His notable contributions include developing machine-learning pipelines for rapid gravitational-wave detection and sky localization, robust waveform reconstruction, and parameter estimation of binary black-hole mergers. He is a member of the LIGO–Virgo–KAGRA Collaboration and an affiliate of the ARC Centre of Excellence for Gravitational Wave Discovery (OzGrav), where he previously chaired the Gravitational-Wave Inference Program. He also serves as review chair for the LVK Data Quality Report. His honors include Vanderbilt University’s A.I. for New Messengers Postdoctoral Fellowship, the Lacy–Fischer Interdisciplinary Research Grant, the J. P. Macquart Best Student Talk Award, and the Australian Mathematical Sciences Institute Best Student Talk Award. Passionate about science communication and public outreach, he also received UWA’s Three Minute Thesis and People’s Choice awards.