Bobak Mosadegh Laboratory

Associated Lab Members

Bobak Mosadegh Photo
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Bobak MosadeghPh.D.
  • Associate Professor of Biomedical Engineering in Radiology
  • DICI Director

Bobak Mosadegh received his B.S. and M.S. in biomedical engineering from the University of California, Irvine.  He performed undergraduate and graduate-level research in Professor Noo Li Jeon’s lab, working on gradient-generating microfluidic devices. Dr. Mosadegh received his Ph.D. from the University of Michigan, Ann Arbor while working in the lab of Shuichi Takayama.  His research involved developing microfluidic integrated circuits and various cell patterning methods using aqueous two-phase systems and microfluidic devices.  Under the  guidance  of George M. Whitesides, Dr. Mosadegh performed his postdoctoral training at Harvard University and the Wyss Institute of Biologically Inspired Engineering.  His research focused on developing two technologies: i) a 3D paper-based cell culture system to study the effects of ischemic gradients on cancer cells and cardiomyocytes, and ii) actuators and control systems for soft robotics. Dr. Mosadegh started as an assistant professor in the Department of Radiology, Weill Cornell Medicine (WCM), in Nov. 2014. He is currently an associate professor. He is a member of the Dalio Institute of Cardiovascular Imaging, and convener  for the International Organization for Standardization (ISO) working group on cardiac occluders. 

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Mohsen AnnabestaniPh.D.
  • Postdoctoral Associate in Radiology

Mohsen Annabestani, Ph.D., earned his M.S. in biomedical engineering from Ferdowsi University of Mashhad in 2013 and his Ph.D. in electrical engineering in 2018, both focusing on soft actuators. During his Ph.D., he spent six months at Harvard University researching soft robotic catheters. From 2018 to 2021, he worked at Sharif University of Technology, contributing to soft sensors, actuators, biosensors, wearable devices, and microfluidics, while supervising B.S. and M.S. students. In 2021, Dr. Annabestani joined the Bioinspired Soft Robotics group at the Istituto Italiano di Tecnologia as a postdoctoral research fellow, collaborating on designing growing robots inspired by plant movement. Currently, he is a postdoctoral research associate at Weill Cornell Medicine, focusing on mixed reality visualization for cardiac interventions and soft robotics for biomedical applications. With expertise in biomedical engineering and artificial intelligence, Dr. Annabestani aims to address healthcare challenges by integrating soft robotic systems with intelligent algorithms and signal processing. He has also lectured on electric circuits, signal processing, machine learning, and engineering mathematics.

Alexandre Caprio
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Alexandre Caprio
  • Research Associate in Radiology

Alex Caprio obtained his M.S. in biomedical engineering from the Faculty of Medicine in Nancy, France. He subsequently had several internships and positions, providing him expertise in medical device development and testing. While at the Dalio Institute, he has acquired skills in 3D printing, image segmentation, image analysis, computer-aided design, soft robotics and stretchable electronics. He contributes to most projects in the labs of both Dr. Mosadegh and Simon Dunham. 

Mousumi Dhara
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Mousumi Dhara
  • Laboratory Supervisor in Radiology

Mousumi Dhara manages purchasing, regulatory affairs and operations for the Biomedical Engineering and Brain Health Imaging Institute in the Department of Radiology. Prior to this, she was the biorepository coordinator in the Head and Neck Cancer Division at Johns Hopkins University, and in Tissue Procurement Services at the Memorial Sloan Kettering Cancer Center Department of Pathology. 

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Sepehr JanghorbaniPh.D.
  • Postdoctoral Associate in Radiology
Sepehr Janghorbani, Ph.D., is a postdoctoral associate at Weill Cornell Medical College and the DALIO Institute. Before this, he obtained his Ph.D. from the computer science department of Rutgers University under the supervision of Gerard De Melo. Sepehr’s research lies at the intersection of deep learning, computer vision, and natural language processing. His research spans a wide range of topics in machine learning, including self-supervised learning and its applications in visual and language understanding, probabilistic generative modeling, multimodal vision-language models, and the evaluation and mitigation of biases in AI models. He is currently focusing on the design and development of deep generative models, with a particular emphasis on medical data applications. Before starting his Ph.D., Sepehr earned his B.Sc. in computer engineering from Sharif University of Technology. In addition to his academic work, he has been part of machine learning research and development teams at prominent companies, including Apple, Disney Research, and Dataminr, contributing to the design and development of various self-supervised vision and language understanding models. Sepehr’s scholarly work has been published in top conferences and journals, including ICLR, NAACL, EACL, and AAMAS. He also serves as a peer reviewer for several conferences and journals, including ACL, ICLR, AAAI, EMNLP, EACL, TIP, and TCSVT, and as a program committee member for the Web Conference.

Lab Goals 

The Mosadegh Lab has recently focused on developing next-generation medical devices for surgical and minimally invasive procedures. These devices are designed to provide unprecedented performance by leveraging enabling technologies such as 3D printing, soft robotics, machine learning and mixed reality. Historically, the lab also has expertise in soft robotic actuators and control systems for many applications, as well as in microfluidics and 3D cell-culture for applications in drug discovery using organs-on-chips platforms. 

Collaborators

Aiden Sherry
Yiyun Wang
Sidarth Wadwa
Jessica Goldstein

Research Projects

The overall goal of this project is to develop a mixed reality (MR) and deep learning (DL)-based system for intra-operative image guidance for interventional procedures conducted under fluoroscopy. This unique guidance...

Most benign tumors are uterine fibroids in women, especially African American women. Today, doctors counsel women using flat magnetic resonance imaging (MRI)  images, but fibroids can grow on multiple uterine planes, and 2D imaging does not accurately...

The goal of this project was to develop a patient-specific occluder for the left atrial appendage (LAA), as a stroke prevention device for atrial fibrillation (...

Award or Grant: National Heart Lung and Blood Institute (NHLBI), 1 R61 HL156153-01 (2021-2023)

Prior Associated Grant: Non-occluding Zero-Thickness Inflatable Sensor Arrays for Conformable Mapping and Ablation

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Heart disease is the top U.S. cause of mortality, with 600,000 deaths annually. Its high prevalence is responsible for 1/6 of health care costs, which in 2010 w...

Weill Cornell Medicine
Department of Radiology
525 East 68th Street New York, NY 10065