School of Medicine
Showing 1-16 of 16 Results
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Vasiliki (Vicky) Bikia
Postdoctoral Scholar, Biomedical Informatics
BioDr. Vasiliki Bikia is a Fellow at the Institute for Human-Centered Artificial Intelligence and Postdoctoral Scholar at Stanford University, working with Prof. Roxana Daneshjou. She received her Advanced Diploma degree in Electrical and Computer Engineering from the Aristotle University of Thessaloniki (AUTH), Greece, in 2017, and her Ph.D. degree in Biomedical Engineering from the Swiss Federal Institute of Technology of Lausanne (EPFL), Switzerland, in 2021. Her Ph.D. research addressed the clinical need for providing non-invasive tools for cardiovascular monitoring leveraging machine learning and physics-based numerical modeling.
Her current work focuses on developing large multimodal models to enhance biomarker identification and patient outcome prediction. At Stanford, she has also contributed to the Stanford Spezi framework, designing and prototyping the Spezi Data Pipeline tool for enhanced digital health data accessibility and analysis workflows. Her research interests include health algorithms, clinical and digital biomarkers, machine learning, non-invasive monitoring, and the application of large language models for personalized healthcare, predictive analytics, and enhancing patient-clinician interactions. -
Hejie Cui
Postdoctoral Scholar, Biomedical Informatics
BioDr. Hejie Cui is a postdoctoral researcher at the Stanford Center for Biomedical Informatics Research at Stanford University. Her research focuses on the intersection of machine learning, data mining, and biomedical informatics. At Stanford, Dr. Cui works on large language model (LLM) evaluation and post-training for healthcare. Dr. Cui has authored and co-authored several publications in top computer science and interdisciplinary venues, including NeurIPS, KDD, AAAI, CIKM, TMI, and MICCAI. Her work contributes to advancing the application of artificial intelligence in healthcare and improving the understanding of complex biomedical data. Dr. Cui was selected as a Rising Star in EECS in 2023. She has also received numerous awards, including the Fellowship of 2021 CRA-WP Grad Cohort for Women, Student Travel Grant Award for MICCAI'22, NSF Travel Grant for CIKM'22, and NeurIPS AI4Science Travel Award for NeurIPS'22. Dr. Cui holds a Ph.D. in Computer Science from Emory University (2024) and a B.Eng. in Computer Science and Engineering from Tongji University (2019). During her graduate studies, she gained industry experience through internships at Microsoft Research and Amazon Science.
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François Grolleau
Postdoctoral Scholar, Biomedical Informatics
BioFrançois Grolleau MD, MPH, PhD is a Postdoctoral Scholar at the Stanford Center for Biomedical Informatics Research. His research work centers on developing and evaluating computational systems that use retrieval-augmented language models and other advanced methods from statistics and machine learning to assist medical decision-making.
François is a certified Anesthesiologist and Critical Care Medicine specialist from France. He holds an MPH degree and a PhD in Biostatistics from Paris Cité University. In 2016/2017, he worked as a research fellow in the Department of Health Research Methods, Evidence, and Impact at McMaster University, Canada (Profs Yannick Le Manach and Gordon Guyatt). During his doctorate with Prof. Raphaël Porcher, he utilized causal inference, personalized medicine methods, and statistical reinforcement learning for medical applications in the ICU. -
Zepeng Huo
Postdoctoral Scholar, Biomedical Informatics
BioConducting research on Foundation Models for medicine
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Tushar Mungle
Postdoctoral Scholar, Biomedical Informatics
Current Research and Scholarly InterestsUse electronic health records (EHRs) to identify and classify common ocular diseases such as glaucoma, diabetic retinopathy, and macular degeneration. We aim to develop an approach to accurately identify these conditions using EHRs. This will be followed by cluster analysis to identify novel subtypes of these conditions that have not been recognized before. Finally, we will develop an approach to extract outcome data from EHRs for patients with these conditions in the primary care setting.
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Fateme Nateghi Haredasht
Postdoctoral Scholar, Biomedical Informatics
BioAs a postdoctoral scholar at the Stanford Center for Biomedical Informatics Research, I find myself at the exciting intersection of machine learning and healthcare. My journey began with a PhD in Biomedical Sciences from KU Leuven in Belgium, where I delved into the complexities of machine learning algorithms and their transformative potential in healthcare settings. My research, particularly focused on adapting these algorithms for time-to-event data (a method used for predicting specific events in a patient’s future), has not only been a challenging endeavor but also a deeply fulfilling one.
Now at Stanford, my role involves not just advancing machine learning integration in healthcare, but also collaborating with a diverse team of experts. Together, we're striving to unravel complex healthcare challenges and improve patient outcomes. -
Madelena Ng
Postdoctoral Scholar, Biomedical Informatics
BioDr. Ng is a postdoctoral fellow at the Stanford Center for Biomedical Informatics Research, mentored by Dr. Tina Hernandez Boussard. Her research aims to illuminate the evolving ethical and practical challenges with emerging technologies used for health purposes. Prior to joining Stanford, Dr. Ng facilitated mobile- and internet-based health research initiatives with the Health eHeart Study and the Eureka Digital Research Platform and developed research study prototypes that used blockchain technology for health data exchange. Her current work focuses on discerning key challenges that exist at each stage of the AI life cycle and generating informed guidance to drive the responsible and equitable use of AI for patient care.
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Malvika Pillai
Postdoctoral Scholar, Biomedical Informatics
BioMalvika Pillai is a postdoctoral research fellow in the VA Big Data Scientist Training Enhancement Program (BD-STEP), jointly in Stanford University in Medicine (Biomedical Informatics) in the Boussard Lab and VA Palo Alto. She received her BS in Quantitative Biology and PhD in Health Informatics from the University of North Carolina at Chapel Hill. Her current work focuses on developing, evaluating, and implementing fair artificial intelligence/machine learning (AI/ML) models that can lead to high-quality, patient-centered care.
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Xianghao Zhan
Postdoctoral Scholar, Biomedical Informatics
BioXianghao Zhan is a postdoctoral researcher at Stanford Department of Biomedical Data Science, mentored by Prof. Olivier Gevaert. Previously, he obtained his Ph.D. from Stanford Bioengineering with a Ph.D. minor in Biomeidcal Data Science in June 2024. During his Ph.D. at Stanford, he also obtained his M.S in Bioengineering in 2021 and his M.S in Statistics in 2023 both at Stanford. Before that he got B. Eng. in Control Science and Engineering (Automation) and his B. Art in English Language and Literature with Summa Cum Laude at Chu Kochen Honors College, Zhejiang University, China, in 2019.
Under the guidance of Prof. Oliver Gevaert and Prof. David B. Camarillo, his PhD research mainly focuses on the optimization of computational modeling of traumatic brain injury with machine learning and animal modeling based on biomechanical and radiological data. His research interests and projects also extend to the data mining of free-text clinical notes with natural language processing, biomedical data fusion for COVID-19 patient outcome prediction, machine learning reliability quantification with conformal prediction, reliability-based semi-supervised learning, and domain adaptation for biomedical sensory systems (with artificial olfaction systems and surface electromyography systems). He has published 20 peer-reviewed articles as a first/co-first author (IF 140.6) in such journals as NPJ Digital Medicine, IEEE Transactions on Biomedical and Health Informatics, IEEE Transactions on Biomedical Engineering, Journal of Sport and Health Science, Journal of Biomechanics, with 4 first-author journal articles under review. He has been a peer reviewer for 17 journals including Annals of Biomedical Engineering, Journal of Neurotrauma, Computer methods in biomechanics and biomedical engineering.
In addition to his research, he has two master degrees while pursuing his Ph.D. degree: BIOE 2021 and STATS 2023. He has taken more than 10 data science and machine learning courses at Stanford with course project experiences and technical background with UNet-based image segmentation, BERT, Transformer-XL, DeepSEA, BPNet, VAE/SSVAE, flow model, energy-based model cycle-GAN, CNN-based image classification, LSTM-based clinical event prediction, Bi-LSTM-based neural machine translation, BERT, DCT/DWT/STFT, PCA, DRCA, NFL, convex optimization.
His research is recognized by the field and he was awarded with IET Postgraduate Research Award for an Outstanding Researcher (one awardee across the globe, first Chinese), Siebel Scholar Class of 2024, IET Healthcare Technology William James Award (one awardee across the globe), Stanford Interdisciplinary Graduate Fellowship (highest honor for interdisciplinary Stanford graduates), Pfeiffer Research Foundation Fellow, AMIA Trainee Award (six awardees, the only Chinese), American Society of Neurotrauma Trainee Award (20 awardees, the only Chinese), Chu Kochen Scholarship (12/23,000), Ten most Preeminent Students of Zhejiang University (10/36,000), Chinese National Scholarship (Top 0.2%).
He is dedicated to support underrepresented minorities. He has been a program leader for Stanford Summer Research Program and mentored 3 undergrads from the underrepresented minorities. He has been a research mentor at Foothill College for two years and mentored latino students from local community college. Additionally, he is a sports fan with 15 Stanford Intramural champions (12 volleyball, 3 tennis) and two medals from regional volleyball tournaments. He enjoys the sport passion and team spirits as a captain.