About Me:
I am currently a medical student(class of 2028) at Howard University College of Medicine (HUCM). My journey in medicine is driven by a profound passion for leveraging technology, particularly Artificial Intelligence, to address health disparities and advance patient care.
I've had the privilege of contributing to impactful projects at esteemed institutions such as Stanford University, the University of California San Francisco (UCSF), the National Institutes of Health (NIH), and many more. These experiences have allowed me to focus on areas including predictive modeling for vaccine responses, investigating the role of viruses in cancer development, and applying Machine Learning(ML) Large Language Models (LLMs) in diagnosing Chronic Kidney Disease of Unknown Etiology (CKDu).
At HUCM, I am honored to serve as the first ever Chief AI Officer for the Health Innovation and Technology (HIT) interest group and as the VP of Research and Technology for my class. In these capacities, I am dedicated to fostering a vibrant community of learning and innovation. A key goal is to spearhead the establishment of the first HBCU Medical Student-led AI research center, aiming to cultivate diverse talent and perspectives in this rapidly evolving field.
Beyond my academic and research pursuits, I am also a skilled Santoor musician, performing with the Chakavak Ensemble, a soccer player, gamer, and an enjoyer of nature.
Research Journey
Explore my research experience across leading institutions, from AI applications in medicine to groundbreaking work in health disparities and predictive modeling.
HBMC Summer Intern
Stanford University - Department of Medicine (Nephrology)
Created ML models, and Investigated the use of LLMs to identify and predict Chronic Kidney Disease of Unknown Etiology (CKDu) in Sri Lanka under guidance Dr. Shuchi Anand and Dr. Maria Emilia Montez Rath.
SRTP Intern
University of California San Francisco - BCHI-Butte Lab
Conducted a meta-analysis on vaccine outcomes using the public dataset ImmPort, focusing on demographic effects on vaccine response. Developed AI/ML models to predict vaccine response using baseline cytokine data and demographics.
Special Volunteer
National Institutes of Health - NCI (Ambs Lab)
Contributed to the VirScan NCI-UMD case-control study, investigating viral roles in prostate cancer development with a focus on health disparities and racial factors (computational and benchside work).
Research Assistant
Howard University - Undergraduate AI/ML Team
Utilized wearable data and algorithms for early detection of illnesses like COVID-19, focusing on eradicating health disparities in wearable medicine. Earned CITI certification and completed 3 HarvardEdx TinyML courses.
Special Volunteer
National Institutes of Health - NIDDK (Lutas Lab)
Conducted research on how neuromodulation of neural circuits leads to long-lasting changes in motivated behaviors (e.g., eating) in mice.
SIP Intern
National Institutes of Health - NHLBI - Bioinformatics Lab
Intern in Laboratory of Bioinformatics and Computational Biology in the NHLBI. Used scientific techniques and R to analyze and compare patients data from AML cancer studies.
Publications & Presentations
Peer Reviewed Journals
- Ashktorab Y, et al. COVID-19 pediatric patients: symptoms, presentations, and disparities by race/ethnicity in a large, multi-center United States study. Gastroenterology. 2021 Apr;160(5):1842-1844.
- Brim A, Ashktorab Y, et al. Pediatric COVID-19 and Gastrointestinal Symptoms in Africa. Gastroenterology. 2021 Aug; 160(5):1842-1844. (Note: CV has same citation details as above, verify if this is a distinct publication or error in CV)
Oral Presentations
- Ashktorab Y. Current Landscape of AI Models With a Focus on Nephrology, Kidney Clinical Research Conference, Stanford University Department of Medicine, Nephrology, June 2025.
- Ashktorab Y. Learning Medicine and Coding with Al tools, Invited presentation, Stanford University Department of Nephrology Biostats Core Meeting, May 2025.
- Ashktorab Y, et al. Extracting and Analyzing Data Using Al Tools in ImmPort, FOCIS 2024 San Francisco, June 2024.
- Ashktorab Y, et al. Leveraging Machine Learning Models and Cytokines to Predict Vaccine Response: Exploring Demographic Influences, UCSF SRTP 2024 Research Symposium, August 2024.
- Exploring, Extracting, and Analyzing Clinical and Immunological Assay Data from ImmPort Using Al Tools, Role of Al in Immunology: Advancing Scientific Frontiers, FOCIS 2025 Virtual Education Symposium, June 2025.
Abstract Presentations
- Ashktorab Y, et al. COVID-19 pediatric patients: symptoms, presentations, and disparities by race/ethnicity in a large, multi-center United States study; Digestive Disease Week. May 2021. (Poster of Distinction)
- Ashktorab Y, et al. Leveraging Machine Learning Models and Cytokines to Predict Vaccine Response: Exploring Demographic Influences. AMA Research Challenge Poster Symposium; November 2024. doi: 10.48448/c05x-qq61.
- Ashktorab Y, et al. A Bioinformatic Analysis of an Unknown Ant Specimen Found in Washington D.C., Howard University Research Month, April 2023.
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