Stanford University
Showing 821-840 of 1,659 Results
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Tracey Riesen
Student Services Officer, Language Ctr
BioTracey is the Student Services Officer for the Stanford Language Center. She is responsible for all undergraduate and graduate student-related activities in the Language Center; this includes language advising, certification of the Language Requirement, academic records for the 6000 students who take foreign language courses each year, language credit transfers, and administration of the Advanced Proficiency Notation. She is the primary contact person for students, as well as for language program coordinators within the Language Center. She also manages the English for Foreign Students (EFS) summer intensive English program for incoming international graduate students and visiting scholars. She greatly enjoys being of service to Stanford students and values working in such a diverse and dynamic community.
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Mouhssine Rifaki
Graduate Visiting Researcher Student, Electrical Engineering
Current Research and Scholarly InterestsI work on sample complexity reduction in reinforcement learning by exploiting latent structure in Markov decision processes such as low-rank Q-functions, spectral gaps, and manifold geometry. My broader interests lie at the intersection of reinforcement learning, control theory, and multi-agent systems, with applications to autonomous driving and adaptive sensing.
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Fran Riley
Clinical Assistant Professor, Emergency Medicine
BioDr. Fran Riley is a physician engineer and Clinical Assistant Professor at Stanford University. She obtained an undergraduate degree in electrical engineering and robotics, she obtained her undergraduate degree from the University of Waterloo where she focused on robotics. Driven by her passion for merging medicine and technology, she pursued a Master's degree in Computer Science at The Johns Hopkins University, where she developed a motor controller for an early prototypes of the Da Vinci robot for ENT surgical applications. Dr. Riley's research also focused on utilizing real-time monitoring data to enhance the treatment of traumatic brain injuries in the pediatric intensive care unit.
Following her work in robotics and computer science, Dr. Riley transitioned to the healthcare industry, where she served as a product manager at Microsoft. In this role, she lead multidisciplinary teams to develop multiple features for an electronic medical record dedicated to data analytics. The product was then acquired by GE Healthcare.
Dr. Riley then pursued a medical degree at the University of Vermont, followed by a residency and chief residency at Maimonides Medical Center. She then completed a fellowship in emergency ultrasound at Columbia University Medical Center.
At Stanford, Dr. Riley is an integral part of the Stanford Emergency Medicine Partnership Program (STEPP), utilizing her technical expertise to identify industry partners for research collaborations and product development. She also actively contributes to a hospital-wide committee dedicated to evaluating the use of informatics for clinical care, prioritizing patient safety and high-quality care.
Dr. Riley's clinical research focuses on leveraging artificial intelligence in image recognition for regional wall motion abnormalities, specifically utilizing point-of-care ultrasound to diagnose acute coronary syndrome. -
Geoffrey Riley
Clinical Professor, Radiology
Current Research and Scholarly InterestsMSK tumors, sarcomas, bone tumors, soft tissue tumors.
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Reiko Riley
Director of Education and Program Development, Psychiatry and Behavioral Sciences
Current Role at StanfordSr. Education Program Manager
Member of the Diversity, Equity, and Inclusion Advisory Committee (Psychiatry and Behavioral Sciences) -
Ellen Youngsoo Rim
Assistant Professor of Chemical Engineering
BioPlants are increasingly vulnerable to environmental stressors—such as pathogen infection, drought, and heat—from climate change. These challenges threaten global food security and limit the carbon sequestration potential of plants. Our research goal is to sustainably enhance plant productivity and resilience through protein engineering. We engineer proteins involved in plant immune and hormone signaling pathways using directed evolution in high-throughput single cell systems. Directed evolution is a synthetic biology approach that enables rapid development of proteins with novel or improved functions. We combine this approach with machine learning, which allows us to learn from large datasets generated during the directed evolution process. Engineered proteins are then introduced into plants to enhance crop yields and climate resilience.
