Speaker Bios
Speaker Bios
Tyler Richards, MD
Tyler Richards, MD, is a neuroradiologist and Assistant Professor of Radiology at the University of Utah, where he directs initiatives in artificial intelligence and advanced imaging. He co-leads the Radiology AI Research Center, developing computational infrastructure and collaborative projects that accelerate translation of AI into clinical practice. His research focuses on developing and validating neuroradiology AI models with an emphasis on improving diagnostic accuracy and workflow efficiency.
Beatrice Knudsen, MD-PhD
Dr. Beatrice Knudsen earned her MD-PhD from Weill Cornell University and pursued a postdoctoral fellowship in molecular oncology at the Rockefeller University. She then completed her residency at New York Hospital and is board-certified in anatomic pathology. She has held faculty positions at New York Hospital, Fred Hutchinson Cancer Center, and Cedars-Sinai Medical Center. Currently, she serves as the Medical Director of Computational Pathology in the Department of Pathology and leads a research program in computational biomarkers. Originally from Vienna, she loves baking, eating pastries, photography, and exploring southern Utah on a mountain bike.
Ganesh Adluru, PhD
Ganesh Adluru, PhD, is an Associate Professor of Radiology and Imaging Sciences at the University of Utah, with a joint appointment in Biomedical Engineering. His research focuses on developing advanced cardiac MRI techniques, particularly ungated and free-breathing methods for quantitative myocardial perfusion. He has served as Principal Investigator on multiple NIH-funded projects aimed at improving detection of coronary artery disease and as Co-Investigator on collaborative studies of atrial fibrillation and heart failure.
Dr. Adluru has published extensively in leading journals, contributed to book chapters, and holds patents in MRI reconstruction methods. He is a Fellow of the Society for Cardiovascular Magnetic Resonance and an Associate Editor for the Journal of Magnetic Resonance Imaging. In addition to research, he is deeply engaged in mentoring graduate students and postdoctoral fellows.
Aik Choon (AC) Tan, PhD
Aik Choon (AC) Tan, PhD received his B.Eng. degree in Chemical/Bio-process Engineering from the University of Technology Malaysia, and his PhD. degree in Computer Science/Bioinformatics from the University of Glasgow, UK, in 2000 and 2005, respectively. Dr. Tan conducted his post-doctoral research training at the Johns Hopkins University School of Medicine from 2004 to 2009. He was an Assistant Professor at the University of Colorado Anschutz Medical Campus in 2009 and promoted to Associate Professor in 2013. Dr. Tan was recruited to the Moffitt Cancer Center in 2019 as the Vice-Chair of the Department of Biostatistics and Bioinformatics. In 2022, Dr. Tan was appointed as the inaugural Senior Director of Data Science at the Huntsman Cancer Institute, University of Utah. He holds the Jon M. and Karen Huntsman Endowed Chair in Cancer Data Science, Tenured Professor of Oncological Sciences and Biomedical Informatics. His research interests are translational bioinformatics and cancer systems biology, primarily by developing computational and machine learning methods for the analysis and integration of high-throughput cancer "omics" data in understanding and overcoming treatment resistance mechanisms in cancer. His lab acts as "connector" to provide seamless integration of computational and statistical methods in experimental and clinical cancer research. He has published >250 manuscripts, co-edited two bioinformatics and systems biology books, and a H-index of 74 (Google Scholar). Dr. Tan is the President of the MCBIOS society, a Senior Member of the ISCB, and Co-Chair of the Data Science Research Interest Group of the Oncology Research Information Exchange Network (ORIEN).
Akshay Chaudhari, PhD
Dr. Akshay Chaudhari, PhD, is an Assistant Professor of Radiology and Biomedical Data Science, and is currently the Interim Division Chief of the Integrative Biomedical Imaging Informatics section in Radiology. Dr. Chaudhari leads the Machine Intelligence in Medical Imaging research group at Stanford focusing on improving both the acquisition and analysis of medical images and related healthcare data. His group develops new self-supervised and representation learning techniques for multi-modal deep learning for healthcare using vision, language, and medical records data. Dr. Chaudhari’s research is funded by the NIH, ARPA-H, and several industry partners. He also serves as the Co-Director of Clinical AI at Stanford Radiology and as the Associate Director of Research and Education at the Stanford AIMI Center.
Tim Amrhein, MD
Dr. Tim Amrhein is a tenured Associate Professor in the Department of Radiology at Duke University Medical Center where he also serves as the Director of Spine Intervention. He completed residency training in Diagnostic Radiology at Duke, where he served as chief resident, and stayed to complete a Neuroradiology fellowship.
Dr. Amrhein leads a team of spine researchers focusing on Spontaneous Intracranial Hypotension and CT guided pain interventions. He has been first author or a co-author on more than 85 peer-reviewed publications and has written multiple book chapters. His work has been published in JAMA Neurology, PLOS Med, Nature: NPJ Digital Medicine, Radiology, American Journal of Radiology, Headache, and the American Journal of Neuroradiology with features in the popular press ranging from national outlets such as the New York Times and Reuters to the local press (WRAL). Dr. Amrhein’s research has been supported through multiple grants including several highly competitive national foundation awards: the RSNA Research Scholar Grant, ASNR Comparative Effectiveness Award, Spine Intervention Society Research Grant, the American Heart Association Bugher Fellowship, and a Spinal CSF Leak Foundation Grant. Further, Dr. Amrhein has helped to pioneer the use of photon counting CT for the detection of CSF-venous fistulas in patients with SIH, greatly impacting the lives of those with this debilitating condition.
Dr. Amrhein has lectured nationally and internationally with invited talks in the Netherlands, Brazil (JPR), Canada, and regularly at RSNA, ASNR, ARRS, and ASSR. He has served in multiple society leadership roles including as ASSR Vice President (current), ASSR Research Committee Chair (current), ISSCL Treasurer (current), ASSR Treasurer, and RSNA Neuroradiology Educational Exhibits Chair.
Taylor Webb, PhD
Taylor Webb, PhD is an assistant professor of Radiology and Imaging Sciences at the University of Utah. He is developing non-invasive neuromodulation therapies to treat mental health disorders—with an emphasis on developing guidance techniques to ensure robust treatment outcomes. Dr. Webb received his PhD from Stanford University where he studied the propagation of ultrasound through the human skull. During his postdoctoral fellowship, completed at the University of Utah, Dr. Webb demonstrated the capacity of ultrasound delivered to the lateral geniculate nucleus to modulate awake behavior in a nonhuman primate model.
Amit Gupta, MD
Dr. Amit Gupta, MD, is an academic radiologist specializing in Cardiothoracic Imaging with a primary focus on integrating AI-driven diagnostics and advanced imaging techniques to enhance patient care. Dr. Gupta is triple board-certified, holding certifications from the American Board of Radiology (ABR), the American Board of MR Safety (ABMS), and the American Board of Imaging Informatics (ABII).
He is an Associate Professor of Radiology and Modality director of Diagnostic Radiography at University Hospitals Cleveland Medical Center/Case Western Reserve University. He also serves as Division Chief for Cardiothoracic Division and has joint appointments in the Departments of Internal Medicine and Biomedical Engineering. He is a passionate educator and strong advocate for advancing imaging techniques, modalities, and software for image interpretation, with expertise in Spectral Detector CT, 3D Printing, Radiomics, and PET/MRI. His present work focuses on methods to improve adoption and streamlining the integration of AI algorithms into routine clinical practice at University Hospitals.
Andrew E. Anderson, PhD
Dr. Anderson is a Professor and Division Chief of Research in the Department of Orthopaedics at the Spencer Fox Eccles School of Medicine at the University of Utah. He holds adjunct appointments in the Department of Biomedical Engineering and Department of Physical Therapy and Athletic Training and is affiliate Faculty at the Scientific Computing and Imaging Institute. He grew up in Brighton, Michigan and earned his BS in Biomedical Engineering at Michigan Tech University. In 2000, he completed a research internship at the Mayo Clinic, Department of Orthopaedics. In 2001, he pursued his dream of living in the mountains and attended the University of Utah for his PhD in Biomedical Engineering. He accepted a faculty position at the University of Utah Orthopaedics Department in 2007. In 2011, he served as a Visiting Scholar at the Stanford Neuromuscular Biomechanics Lab, where he acquired proficiency in muscle modeling.
Daniel Polak, PhD
Daniel Polak, PhD is an MRI physicist with nine years of experience in magnetic resonance imaging research and development, including over five years at Siemens Healthineers. He currently serves as a Senior Staff Scientist in the United States.
Daniel earned both his Master’s degree and Ph.D. in Physics from Heidelberg University. During his doctoral studies, he was a visiting researcher at Massachusetts General Hospital (MGH) and the Massachusetts Institute of Technology (MIT), focusing on advanced neuroimaging research.
Before his current role, Daniel worked as an application developer with the global Siemens Neuro Team in Erlangen, Germany, where he specialized in advanced MRI techniques such as accelerated imaging, deep learning–based image reconstruction, and motion correction. He contributed to the development and clinical evaluation of multiple works-in-progress (WIP) packages, which led to commercial products including Wave-CAIPI and SAMER motion correction.
Talmage L. Shill, MD
Talmage L. Shill, MD is a Clinical Radiologist with the Breast Imaging Team at the University of Utah. He also serves on the Clinical AI Committee where they discuss the hurdles and advantages of implementing AI in the clinical setting.
