Binod M. Manandhar, PhD

B.Sc.,  Physics  — Amrit Science Campus, Kathmandu, Nepal (2002)

M.Sc., Physics  — Tribhuvan University, Kathmandu, Nepal (2005)

Ph.D., Physics  — University of Wisconsin Milwaukee, WI (2016)

CAMPEP Certificate in Medical Physics — Virginia Commonwealth University (2022)

Postdoctoral Training — Virginia Commonwealth University (2023)

Residency, Therapeutic Medical Physics — Medical College of Wisconsin (2025)

Dr. Binod Manandhar is an Assistant Professor in the Department of Radiation Oncology at the University of Maryland School of Medicine. He earned his Ph.D. in Condensed Matter Physics from the University of Wisconsin–Milwaukee and previously served as a Lecturer in Physics at multiple campuses within the University of Wisconsin System. As a graduate student, Dr. Manandhar focused on the synthesis and characterization of graphene-based nanomaterials. His research utilized high-resolution transmission electron microscopy (HRTEM) and synchrotron-based infrared micro-spectroscopy to investigate structural and optical properties at the nanoscale.

During his postdoctoral training, Dr. Manandhar specialized in treatment planning optimization and multi-institutional patient data analysis in radiation oncology. His work involved replacing conventional brachytherapy applicators with IMBT-driven Direction Modulated Brachytherapy (DMBT) applicators developed in collaboration with Varian Medical Systems. The primary objective of this research is to improve dose coverage to High-Risk Clinical Target Volume(HRCTV) and lower dose to Organs at Risks(OARs).

E C Mattson, M Unger, B Manandhar, Z Alavi, C J Hirschmugl” Multi-beam Synchrotron FPA Chemical Imaging: Impact of Schwarzschild Objective on Spatial Resolution,” Journal of Physics, Conference Series. (2013), 425:142001 DOI 10.1088/1742-6596/425/14/142001.

Suman Gautam, Alexander F. I. Osman, Dylan Richeson, Somayeh Gholami, Binod Manandhar, Sharmin Alam, William Y. Song. Attention 3D UNET for dose distribution prediction of high-dose-rate brachytherapy of cervical cancer: Intracavitary applicators. First published: 15 November 2024. https://doi.org/10.1002/acm2.14568

Suman Gautam, MS¹∙AlexanderF.Osman,MS²∙ Dylan Richerson, MS¹ ∙ Binod Manandhar, PhD¹ ∙ Sharmin Alam,  MS¹ ∙ William Y. Song, PhD^1. A 3D Deep Convolutional Neural Network for Dose Distribution Prediction of Intracavitary HDR Brachytherapy of Cervical Cancer. DOI: 10.1016/j.brachy.2023.06.136 

 Dylan Richeson, MS¹ ∙ Somayeh Gholami, PhD² ∙ Binod Manandhar, PhD¹ ∙ Sharmin Alam, MS¹ ∙ Suman Gautam, MS¹ ∙ Daniel Scanderbeg, PhD³ ∙ Catheryn Yashar, MD³ ∙ Joann Prisciandaro, PhD⁴ ∙ Shruti Jolly, MD⁴ ∙ Emma Fields, MD¹ ∙ William Y Song, PhD¹. Direction Modulated Brachytherapy Tandem Model Applicators for Treatment Planning of Multi-Institutional Cervical Cancer Cases. DOI: 10.1016/j.brachy.2023.06.120

Binod Manandhar, Ph.D¹ ∙ Somayeh Gholami, Ph.D² ∙ Dylan Richeson, MS³ ∙ Sharmin Alam, MS¹ ∙ Suman Gautam, MS¹ ∙ Daniel Scanderbeg, Ph.D⁴ ∙ Catheryn M. Yashar, M.D⁵ ∙ Joann Prisciandaro, Ph.D⁶ ∙ Shruti Jolly, MD⁷ ∙ Emma Fields, M.D¹ ∙ William Y. Song, Ph.D^1” Direction Modulated Brachytherapy Tandem Model Applicators for Treatment Planning of Multi-Institutional Cervical Cancer Cases: Removing Needles in Intracavitary-Interstitial Techniques. DOI: 10.1016/j.brachy.2023.06.047