Postdoc
University of Iowa
Flagstaff, AZ, United States
Dr. Zachary Urdang MD PhD is currently a postdoctoral scholar in the department of Otolaryngology at The University of Iowa where he focuses on cochlear implant electrophysiology, data science, and machine learning. He earned his MD/PhD at Oregon Health and University where he was drawn to hearing research, ototoxicity/protection, and head and neck cancer outreach where he earned 'honors in diversity equity and inclusion.' After completing an intern residency year in general surgery at Oregon Health and Science University he joined Thomas Jefferson University to pursue postdoctoral studies in otolaryngology. During this time, he completed a professional certificate in data science, Python coding, machine learning, and artificial intelligence with Massachusetts Institute of Technology; his postdoctoral research has focused heavily on big-data and -omics topics. During his training, Dr. Urdang has earned multiple grants from the NIH, AOS/ANS, AHNS, PhRMA Foundation, and others. At Jefferson he has served on the IRB committee. Clinically, Dr. Urdang serves Jefferson's 'Clinical Research Unit' where clinical trial patients are seen; he also frequently works with the otolaryngology department clinically/surgically as needed. He is a lead organizer and advocate for Head and Neck Cancer screening initiatives at Jefferson. He is also an active journal reviewer consistently reviewing articles for high profile and otolaryngology specific journals. He has mentored students from the undergraduate through post-graduate levels with a proven track record focusing on students from underserved/underrepresented backgrounds. Having research experience on every level of the translational spectrum (molecules to clinical trials) Dr. Urdang seeks to serve as a translational research ambassador to advocate and advance health topics most applicable to advancing the health of our world's most vulnerable and disadvantaged peoples. He seeks a translational practice serving diverse populations focusing on those populations which have historically faced disproportionate adversity.
Head and Neck Cancer Screening Value Enhancement Via Machine Learning to Predict Diagnoses
Monday, September 30, 2024
9:54 AM – 10:00 AM EDT
Disclosure(s):
faculty for this accredited education activity has no relationship(s) with ineligible companies to disclose.
Ototoxicity Monitoring: The Evolution of a Protocol for Head and Neck Cancer Patients
Monday, September 30, 2024
1:36 PM – 1:42 PM EDT
Disclosure(s):
faculty for this accredited education activity has no relationship(s) with ineligible companies to disclose.