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Michel M. Maharbiz is a Professor in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley. He leads research on miniaturized bioelectronic interfaces, including neural dust implants and cyborg insects. He holds affiliations with the Berkeley Sensor & Actuator Center (BSAC), Center for Neural Engineering & Prostheses (CNEP), and SWARM Lab. His education includes a Ph.D. in EECS from UC Berkeley (2003) and a B.S. in EE from Cornell University (1997). Maharbiz's research integrates MEMS, ultrasonic systems, and synthetic biology to develop wireless neural interfaces, implantable sensors, and biohybrid devices. Key focus areas are neural dust technology for peripheral nerve recording, magnetoelastic strain sensors for medical applications, and electrochemical biosensing using bacterial flagellar motors. His publications emphasize neural interfaces, ultrasonic implants, and biomedical monitoring. Recent articles explore ultrasonic power delivery (2025), radiation detectors for oncology (2025), and fracture-healing smart plates (2019). Trends include miniaturization of wireless implants, closed-loop therapeutic systems, and novel biomaterials. Scientific Awards: McKnight Technological Innovations in Neuroscience Award (2017) Chan-Zuckerberg Biohub Investigator (2017) NSF CAREER Award (2009) MIT TR10 Top Emerging Technology (2009) Bakar Fellows Spark Award (2012) He directs the Maharbiz Lab, advancing neural dust and bioelectronic interfaces. Projects include impedance-based fracture monitoring, carbon fiber neural arrays, and hernia repair sensors. Funding includes NSF and industry partnerships for implantable device development.

• Neural Interfaces
• Micro/Nano Electro Mechanical Systems (MEMS)
• Biosystems & Computational Biology
• +3 more

Carmen Bergom, MD, PhD, is an Associate Professor of Radiation Oncology at Washington University School of Medicine (WashU Medicine), where she joined the faculty in 2020. She holds secondary appointments in the Division of Cancer Biology and the Siteman Cancer Center. Her research focuses on leveraging genetic models to improve radiation therapy efficacy while mitigating radiation-induced cardiotoxicity , particularly in breast cancer patients. Key areas include radiation biology , tumor microenvironment , and cardio-oncology . Recent publications highlight her work in genetic mapping of radiation sensitivity (e.g., rat chromosome 3 variants), innovative imaging techniques (e.g., integrin-targeted PET), and clinical trial design for cardiovascular risk stratification. Her laboratory has pioneered the first genetic studies of radiation-induced cardiac dysfunction. Scientific awards include the Michael Fry Research Award (2021) and recognition as a Top Doctor in America (2018, 2019). She serves as Chair of the ASTRO Science Council Scientific Review Panel and co-chair of the Clinical and Experimental Research in Radiation Oncology meeting at ESTRO. Dr. Bergom treats breast cancer patients clinically and mentors students across all levels (undergraduate to postdoctoral). Her work bridges basic research with clinical applications , aiming to develop biomarkers and therapeutic targets for radiation oncology.

• Radiation Oncology
• Breast Cancer
• Tumor Microenvironment
• +5 more

Zion Zibly, MD, MBA is an Associate Professor in the Department of Neurosurgery at Yale School of Medicine . He holds multiple leadership roles including Director of the Center of Neuromodulation , Director of the Center of Neurosurgical Cancer Pain , and Head of Stereotactic & Functional Neurosurgery and the Focused Ultrasound Institute . Previously served as Chair of Neurosurgery at Sheba Medical Center after graduating from Technion’s Faculty of Medicine (MD) and Coller School of Management (MBA). Research Interests: Specializes in Neuromodulation for movement disorders (Parkinson’s, tremors, dystonia), Deep Brain Stimulation , Gene Therapy for pediatric neurodegenerative conditions, Oncological Neurosurgery , and Neurological Pain Management . Combines Functional Neurosurgery with Focused Ultrasound technology. Scientific Contributions: Participated in pioneering Alzheimer’s brain stimulator procedures and Gene Therapy applications. Active member of the North American Association of Functional Neurosurgery and Israeli Neurosurgical Society . Clinical Expertise: Implantation of electrostimulators for Parkinson’s and essential tremor, treatment of Benign/Malignant CNS Tumors , and management of Neurological Pain Conditions . Affiliated with Yale Cancer Center and Center for Brain & Mind Health .

• Neurosurgery
• Functional Neurosurgery
• Neuromodulation
• +3 more

Christin A. Knowlton, MD, MA serves as Associate Professor of Therapeutic Radiology at Yale School of Medicine, where she holds dual leadership roles as Vice Chair for Accreditation in Therapeutic Radiology and Medical Director of Smilow Cancer Hospital Care Center-Hamden. Her clinical practice focuses on delivering high-quality, patient-centered radiation oncology services with specialization in breast cancer, lung cancer, bone metastases, and thymoma treatments. Dr. Knowlton's educational background includes a BA from Oberlin College (1994), MA from New York University (1998), MD from SUNY at Stonybrook (2006), and residency training at Hahnemann University Hospital/Drexel University College of Medicine (2011). Her research program centers on optimizing radiation therapy protocols, with particular emphasis on hypofractionation techniques, stereotactic body radiation therapy (SBRT), and management of radiation-related toxicities including pneumonitis and esophagitis. Analysis of her 15 most recent publications reveals a consistent research trajectory focused on improving outcomes in thoracic and breast radiation oncology through dose optimization, toxicity prediction modeling, and innovative treatment approaches for oligometastatic disease. Her work frequently addresses the balance between therapeutic efficacy and radiation-induced complications, with growing emphasis on molecular risk assessment and personalized treatment planning. Smilow Luminary Award of Excellence in Patient Care (2019) National Comprehensive Cancer Network (NCCN) Fellows Recognition Program As a clinician-educator, Dr. Knowlton emphasizes the importance of patient communication and multidisciplinary teamwork, collaborating closely with nursing, physics, dosimetry, and therapy staff to deliver comprehensive cancer care. Her leadership in accreditation reflects her commitment to maintaining the highest standards in radiation oncology practice and education. Dr. Knowlton's clinical trial involvement, including the DD3 trial of dose-deescalated SBRT for centrally located lung cancer, demonstrates her active contribution to advancing evidence-based radiation oncology practice.

• Breast Cancer Radiotherapy
• Thoracic Radiotherapy
• Radiation Oncology
• +5 more

Dr. Sotirios Stathakis is Chief of Physics at the Mary Bird Perkins Cancer Center (2023–Present) and Associate Director of the Medical Physics Division at the University of Texas Health Science Center San Antonio (2017–2022). He holds an Adjunct Professor position at Louisiana State University's Department of Physics and Astronomy (2023–Present). His expertise lies in radiation oncology and medical physics, with a focus on patient-specific quality assurance, dose verification, and advanced treatment techniques like adaptive radiation therapy and SBRT. Education: Ph.D., Medical Physics, University of Patras (2005) M.S., Medical Physics, University of Aberdeen (1997) B.S., Physics (minor in Mathematics and Computer Science), University of Waterloo (1995) Research Interests: Patient-specific quality assurance Daily dose verification Treatment planning techniques Adaptive radiation therapy Stereotactic body radiation therapy (SBRT) Automation and workflow optimization in radiation oncology Publications: Over 20 peer-reviewed articles since 2020, focusing on topics like Monte Carlo simulations, AI-driven beam analysis, and AAPM task group recommendations for IMRT verification. Key themes include improving dose accuracy, equipment validation, and clinical implementation of advanced radiation technologies. Grants & Awards: Not explicitly listed in provided text. Labs/Teams: Collaborates with institutions like Fox Chase Cancer Center, South Texas Veterans Health Administration, and LSU on medical physics research and clinical applications.

• Radiation Oncology
• Medical Physics
• Treatment Planning Techniques
• +5 more

Pedro A Hermida de Viveiros, MD serves as an Assistant Professor in the Department of Medicine, Division of Hematology and Oncology at Northwestern University's Feinberg School of Medicine. His clinical practice focuses on solid tumor oncology with specialized expertise in sarcomas and precision medicine approaches. His research interests center on clinical development of novel therapeutic strategies for sarcomas and gastrointestinal stromal tumors (GIST), emphasizing biomarker-driven treatments and molecularly targeted therapies. Key areas include IDH1-mutant chondrosarcoma management, neoadjuvant response assessment in sarcomas, and immunotherapy-radiotherapy combinations for metastatic disease. Analysis of his recent publications reveals a consistent focus on translating molecular targets into clinical applications, particularly through phase 1-3 trials of targeted agents like ivosidenib and IDRX-42. His work bridges radiological assessment, pathological response, and precision oncology frameworks for rare solid tumors. Professional engagements include active membership in major oncology societies: American Society of Clinical Oncology (ASCO) Connective Tissue Oncology Society (CTOS) Sociedade Brasileira de Oncologia Clínica (SBOC) European Society for Medical Oncology (ESMO) He currently leads four active clinical trials through the Robert H. Lurie Comprehensive Cancer Center, including the CHONQUER phase 3 study of ivosidenib for IDH1-mutant chondrosarcoma and first-in-human trials of novel agents for advanced solid tumors and GIST. His work integrates translational research with clinical trial design to advance personalized treatment paradigms.

• Oncology
• Sarcoma Research
• Precision Medicine
• +3 more

Dan Nguyen, Ph.D., is a faculty member in the Department of Radiation Oncology at UT Southwestern Medical Center, where he is part of the Division of Medical Physics and Engineering. He is a founding member of the Medical Artificial Intelligence and Automation (MAIA) Laboratory, collaborating closely with Dr. Steve Jiang to advance AI applications in radiotherapy. His work focuses on deep learning for treatment planning, dose prediction, auto-segmentation, and adaptive radiotherapy. Ph.D. in Biomedical Physics, University of California, Los Angeles (UCLA), 2017 Mentor: Dr. Ke Sheng Faculty appointment at UT Southwestern since 2017 Dr. Nguyen’s research is centered on applying artificial intelligence to solve critical challenges in radiation oncology. His primary interests include deep learning-based dose prediction, auto-segmentation of anatomical structures, optimization of treatment plans, and real-time adaptive radiotherapy. He has pioneered work in direct aperture optimization, 4π radiotherapy, and uncertainty quantification in AI models. His research bridges the gap between AI innovation and clinical implementation, with a focus on improving plan quality, reducing planning time, and enhancing accessibility for less experienced clinicians. The most recent publications (2023–2025) demonstrate a consistent trend in developing fast, accurate, and robust deep learning models for radiotherapy. Key themes include dose prediction with transfer and meta-learning, adaptive segmentation using test-time optimization, uncertainty assessment in AI predictions, and mathematical modeling of radiotherapy-immunotherapy synergy. These works span high-impact journals in medical physics, AI, and oncology, reflecting interdisciplinary innovation. While no specific scientific awards are listed, Dr. Nguyen’s leadership in the MAIA Lab and extensive publication record in top-tier journals indicate significant recognition in the field of medical physics and AI in medicine. Dr. Nguyen has co-authored numerous studies involving mentoring and collaborative research, particularly with trainees and junior faculty in the MAIA Lab. His work is supported by institutional and likely federal funding, given the scale and scope of AI deployment studies. He has contributed to large-scale collaborative efforts such as OpenKBP-Opt, involving international teams evaluating knowledge-based planning pipelines. The MAIA Laboratory is a multi-investigator research group focused on innovating, developing, and applying artificial intelligence technologies to empower clinicians—especially those with less experience or limited resources—for improved patient care. The lab’s work spans machine learning, deep learning, reinforcement learning, and mathematical modeling in radiation oncology.

• Medical Physics
• Artificial Intelligence in Medicine
• Radiation Therapy Treatment Planning
• +7 more

Yading Yuan, PhD is an Associate Professor of Radiation Oncology (Physics) at Columbia University Irving Medical Center and a member of the Data Science Institute. He holds a PhD in medical physics from the University of Chicago (2010) and completed clinical residency at Harvard Medical Physics Program (2013). His research focuses on AI-driven innovations in radiation oncology, including automated medical image analysis systems, federated learning frameworks for tumor segmentation, and data-driven approaches to personalized cancer treatment. He is certified by the American Board of Radiology and licensed in New York State. Education: PhD in Medical Physics (University of Chicago, 2010); Clinical Residency (Harvard Medical Physics Program, 2013). Research interests include: automated knowledge-based treatment planning, large-scale clinical AI systems, medical image reconstruction algorithms, and panomics integration for precision oncology. His work emphasizes translating data science advancements into clinical practice to improve patient outcomes. Key trends in his publications include federated learning for privacy-preserving medical AI, tumor segmentation in multi-modal imaging (PET/CT, MRI), and AI-driven prediction of treatment outcomes and recurrence risks. Recent work emphasizes decentralized learning architectures and cross-institutional collaboration systems. Scientific Awards: Distinguished Reviewers 2013 (selected by peer review committees) Advising/grants: No specific student names or grant details listed in provided text. His work is supported through institutional and collaborative research initiatives. Labs/teams: Active member of Columbia's Data Science Institute and Radiation Oncology department, contributing to interdisciplinary medical AI research groups.

• Artificial Intelligence in Radiation Oncology
• Medical Imaging Analysis
• Data Science Applications in Healthcare
• +3 more

Huixiao Chen is an Assistant Professor and Clinical Medical Physicist II in the Department of Therapeutic Radiology at Yale School of Medicine. She holds a primary appointment in Therapeutic Radiology and is actively engaged in clinical and research activities related to radiation oncology physics. Assistant Professor, Department of Therapeutic Radiology, Yale School of Medicine Clinical Medical Physicist II, Therapeutic Radiology Education: Resident, Yale University (2016) Postdoctoral Fellow, Harvard University (2013) Postdoctoral Fellow, Virginia Commonwealth University (2011) PhD, University of Heidelberg, Germany (2010) MS, Zhejiang University, China (1998) BS, Zhejiang University, China (1995) Huixiao Chen's research centers on medical physics in radiation oncology, with a focus on treatment planning optimization, dosimetry, and image-guided radiotherapy. Her work includes the development and evaluation of advanced radiotherapy techniques such as VMAT and SBRT, with applications in spine, lung, and prostate cancers. She has contributed to improving the accuracy of dose calculations using Monte Carlo methods and has explored the impact of patient motion on treatment delivery. Her research also extends to the design of clinical devices to support safe and effective radiotherapy for diverse patient populations. Her recent publications demonstrate a consistent focus on enhancing the precision and efficiency of radiotherapy. Key themes include multicriteria optimization in treatment planning, dosimetric validation of radiochromic films, and the development of supportive devices for image-guided radiotherapy. These works reflect a strong commitment to advancing clinical medical physics through both computational and engineering innovations. Scientific Contributions: Characterization of GafchromicTM EBT4 film for clinical dosimetry Design of a small-footprint couch-top support for heavy patients in IGRT Application of multicriteria optimization in VMAT planning for spine and prostate cancers Comparison of Monte Carlo vs. pencil beam algorithms in lung SBRT Analysis of diaphragm motion effects on spine SBRT Huixiao Chen has collaborated with researchers such as Emily Draeger and Zhe Jay Chen on various projects. While no formal students or grants are listed, her role as a clinical medical physicist and faculty member suggests active mentorship and potential involvement in funded research. She is a key contributor to the medical physics team at Yale, ensuring high standards in treatment planning and delivery.

• Medical Physics
• Radiation Oncology
• Therapeutic Radiology
• +7 more

Xiaofeng Liu is an Assistant Professor at Yale University School of Medicine in the Departments of Radiology & Biomedical Imaging and Biomedical Informatics & Data Science. He is also an Associate Member at the Broad Institute of MIT and Harvard. Previously, he held faculty positions at Harvard Medical School and research roles at Massachusetts General Hospital and Beth Israel Deaconess Medical Center. PhD in Mechatronics from University of Chinese Academy of Sciences Dual Bachelor's degrees in Automation (Wang-Daheng Elite Class) and Communication from University of Science and Technology of China His research integrates trustworthy AI, medical imaging, and data science to improve diagnosis, prognosis, and treatment monitoring for neurological disorders, cancer, and cardiovascular diseases. Key focus areas include domain adaptation techniques, diffusion models, and interpretable AI systems. Led special issues in IEEE Transactions on Pattern Analysis and Medical Image Analysis Developed novel frameworks like Ordinal UDA and Memory-Consistent Adaptation Scientific accolades include the Trailblazer R21 Award (NIBIB), OpenAI Research Award, and National Artificial Intelligence Research Resource Pilot Award. He serves as Associate Editor for IEEE Transactions on Neural Networks and Learning Systems and actively contributes to MICCAI and NIH review panels. His lab at Yale (XLiu Lab) investigates neural basis of intelligence to inspire AI development, with applications in brain tumor segmentation, cardiac imaging, and cross-modal medical diagnostics.

• Artificial Intelligence
• Deep Learning
• Medical Imaging
• +5 more

Brian Kavanagh, MD, MPH is a Professor and Department Chair of Radiation Oncology at the University of Colorado Anschutz Medical Campus School of Medicine. He serves as Department Chair and maintains clinical practice at multiple UCHealth locations including the University of Colorado Cancer Center, Cherry Creek Medical Center, Longs Peak Medical Center, and the Rocky Mountain Gamma Knife Center. His leadership extends to serving as Chair of the American Society for Radiation Oncology since 2017. MD, Tulane University School of Medicine (1988) MPH, Tulane University (1988) BSE, Tulane University (LA) (1984) Internship: Tulane University Program (1989) Residency: Duke University Hospital Program, Radiation Oncology (1993) Dr. Kavanagh's research primarily focuses on stereotactic body radiation therapy (SBRT), functional lung avoidance radiation therapy using 4DCT-ventilation imaging, and treatment of brain metastases from oncogene-driven lung cancers. His work bridges clinical practice, medical physics innovation, and outcomes research, with particular emphasis on optimizing radiation therapy techniques while minimizing toxicity. Recent publications demonstrate his leadership in developing novel approaches to image-guided radiation therapy, including antiscatter grid technology for CBCT imaging and functional avoidance techniques for lung cancer treatment. Analysis of Dr. Kavanagh's recent publications (2019-2024) reveals a strong focus on precision radiation therapy for lung cancer and brain metastases. His research spans technical innovations in medical physics (such as 2D antiscatter grid development), clinical trials evaluating functional avoidance radiation therapy, and studies examining outcomes for patients with oncogene-driven cancers. A significant portion of his work addresses the integration of radiation therapy with targeted therapies for lung cancer with brain metastases, reflecting the evolving treatment paradigms in this field. Top Doctor, 5280 Magazine (2023) Dr. Kavanagh has been instrumental in developing national radiation oncology curriculum frameworks through stakeholder consensus processes. His leadership in the American Society for Radiation Oncology has positioned him to influence practice guidelines and educational standards in the field. His research has been supported through multi-institutional clinical trials and collaborations with major cancer centers across the United States. Dr. Kavanagh leads research efforts in the Rocky Mountain Gamma Knife Center and contributes to the University of Colorado Cancer Center's radiation oncology program. His work with 4DCT-ventilation imaging has established a clinical research program focused on functional avoidance radiation therapy, which aims to preserve lung function while effectively treating tumors.

• Radiation Oncology
• Stereotactic Body Radiation Therapy
• Functional Lung Avoidance Radiation Therapy
• +7 more

Patricia Peter, MD, is an Assistant Professor of Medicine (Endocrinology) and Quality Improvement and Patient Safety Coordinator at Yale School of Medicine. She specializes in diabetes, thyroid disorders, and hormone-related conditions. Dr. Peter holds board certifications in Internal Medicine and Endocrinology, Diabetes, and Metabolism. Her clinical practice focuses on personalized diabetes management, thyroid diseases, and transgender health. She completed her MD at Yale University School of Medicine (2011), residency at Harvard Medical School/Beth Israel Deaconess Medical Center (2014), and endocrinology fellowship at Yale-New Haven Hospital (2016). Dr. Peter’s research investigates diabetes treatment strategies, healthcare cost optimization, and hormone therapy impacts. Notable work includes studies on SGLT inhibitors in type 1 diabetes, personalized management of type 2 diabetes, and thyroid cancer radiotherapy. She actively participates in committees such as the Inpatient Glycemic Management Steering Committee and the Section of Endocrinology Education Committee. Her academic contributions span peer-reviewed journals, book chapters, and commentaries, emphasizing translational research and clinical guidelines. Dr. Peter’s clinical affiliations include the Yale Diabetes Center and Smilow Cancer Hospital, where she integrates research and patient care to improve outcomes in endocrinology and metabolic disorders.

• Diabetes Care
• Endocrinology
• Thyroid Disorders
• +5 more

Kelli Connolly is an Associate Research Scientist at the Yale School of Medicine, Yale University. Her research focuses on cancer immunology, with a particular emphasis on tumor immunity, T cell biology, and neoantigen-driven immune responses. She develops and utilizes mouse models to investigate mechanisms underlying anti-tumor immunity, including T cell exhaustion, tertiary lymphoid structures in cancer, and the role of stem-like T cells in sustaining immune responses. Her work bridges basic immunology and translational cancer research, aiming to improve immunotherapy strategies. Key Collaborations: Works closely with researchers like Nikhil Joshi, Gena Gora Foster, and Julie F. Cheung. Research Themes: Neoantigen expression, tumor-draining lymph node dynamics, and combination therapies targeting the immune microenvironment. Her studies highlight the importance of lineage fidelity in CD8 T cells and the role of transcription factors like KLF2 in suppressing exhaustion. She also explores how modulating chemokine axes (e.g., CCR2/CCR5) enhances radiotherapy efficacy. Connolly’s contributions span preclinical models for lung and pancreatic cancers, emphasizing the interplay between tumor biology and immunological mechanisms. Publications span journals like Science , Cell , and Nature Biotechnology , reflecting her impact in cancer immunology and translational research.

• Cancer Immunology
• Immunotherapy
• Tumor Microenvironment
• +3 more

Hyun-soon Chong is a Professor of Chemistry at the Lewis College of Science and Letters , Illinois Institute of Technology. The Chong group focuses on interdisciplinary research spanning organic synthesis, medicinal chemistry, and nuclear medicine to develop targeted therapeutics for cancer and neurodegenerative diseases. Education : B.S. from Kyung Hee University, Ph.D. from the University of North Texas Research interests include: Organic synthesis using aziridinium ions Development of bifunctional chelators for radiotherapy/imaging Bioconjugate chemistry for antibody-drug conjugates Targeted cancer therapies and diagnostics Nuclear medicine applications with isotopes like Cu-64, Y-90, and Lu-177 Key publication trends show expertise in chelation chemistry, bioconjugation, and radiopharmaceutical development. The group has advanced aziridinium ion-based methodologies and created novel agents with preclinical efficacy. Labs/teams: The Chong group specializes in synthetic strategies for enantiomerically enriched molecules and biomedical chelators. Contact: chong@illinoistech.edu

• Organic synthesis
• Medicinal chemistry
• Bioconjugate chemistry
• +7 more

Dr. Chad J. Brenner is an Associate Professor in the Department of Otolaryngology-Head and Neck Surgery and Pharmacology at the University of Michigan Medical School. He also directs the U-M Program in Cellular and Molecular Biology, the Otolaryngology Clinical Laboratory (CLIA), and the Head & Neck Oncology Program. His research focuses on developing liquid biopsy tools for cancer detection and precision therapy, particularly in HPV-driven head and neck cancers. Key roles include membership in the Rogel Cancer Center, Kresge Hearing Research Institute, and Center for Computational Medicine & Bioinformatics. Education: B.S. in Biomedical Engineering, M.S. in Bioelectrical Engineering, and Ph.D. in Cellular and Molecular Biology from the University of Michigan, with doctoral work on prostate cancer mechanisms. Research Interests: HPV integration and cancer heterogeneity Urine- and blood-based liquid biopsies for real-time cancer monitoring Combination immunotherapy strategies for improving checkpoint inhibitor responses Genetic engineering to identify cancer vulnerabilities Clinical trial innovation for adaptive therapies Recent Work Highlights: Development of the MyHPVscore blood test for HPV-related head and neck cancer detection, and exploration of tumor-immune interactions through PD-L1 and T-cell profiling. Ongoing projects include PET-guided radiotherapy optimization and multi-omics analyses of tumor heterogeneity. Labs & Teams: Leads the Michigan Otolaryngology and Translational Oncology (MiOTO) lab and collaborates with interdisciplinary teams across computational medicine, immunology, and clinical oncology.

• Head and Neck Cancer
• HPV-Driven Oncogenesis
• Liquid Biopsy Technologies
• +5 more