School of Medicine
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Alexander D. Kaiser
Instructor, Cardiothoracic Surgery
BioAlexander Kaiser, PhD, is an applied mathematician and computational scientist who researches modeling and simulation of heart valves, focused on congenital heart valve disease and its surgical treatment. His recent research explores simulation-guided design of aortic valve repair of complex congenital heart defects. He has developed novel, nearly first-principles modeling methods for heart valves called elasticity-based design. These methods produce robust and realistic flows in fluid-structure interaction simulations. Dr. Kaiser is an Instructor in Cardiothoracic Surgery at Stanford University working with Michael Ma and Alison Marsden. He completed his PhD in Mathematics with Charles Peskin at the Courant Institute of Mathematical Sciences at New York University, where he was awarded the Kurt O. Friedrichs Prize for Outstanding Dissertation in Mathematics.
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Pooja Kakar
Member, Maternal & Child Health Research Institute (MCHRI)
Current Research and Scholarly InterestsAs a breastfeeding medicine physician, I am passionate about advocating for mother-infant dyads and supporting their breastfeeding journeys. Additionally, I am interested studying and addressing disparities in initiation and duration of breastfeeding, particularly in lower-resourced populations, by building and advancing community partnerships.
I am also interested in the use of digital health tools to advance upstream determinants of health in community-based settings. My current funded research projects include: 1) Providing a telehealth-based, weight control program to children with obesity from lower-income, racial and ethnic minority families (Gardner GOALS) and 2) Assessing and addressing disparities in healthy behaviors in families from under-resourced settings through the use of a secure, multilingual mobile neighborhood app (Our Voice: Beyond Clinic Walls). -
Anusha Murali Kakolu, PhD
Clinical Assistant Professor, Psychiatry and Behavioral Sciences - Child & Adolescent Psychiatry and Child Development
BioAnusha Murali Kakolu, PhD (she/her) received her PhD in clinical psychology from Palo Alto University and completed her predoctoral pediatric psychology residency at the Cleveland Clinic, followed by a postdoctoral residency at Kaiser Permanente Santa Clara Medical Center. She also holds a master’s degree in mental health counseling and behavioral medicine from Boston University School of Medicine.
Anusha’s research and clinical work focus particularly on pediatric health psychology and anxiety. She has a strong commitment to supporting diverse youth and their families, especially those with complex medical conditions. Her training spans multiple specialties, including solid organ transplant, nephrology, endocrinology, genetic conditions, hematology, and oncology.
Anusha is also a passionate educator, serving as adjunct faculty in the doctoral and master’s programs at various universities. She is deeply dedicated to teaching, mentorship, and the supervision of students and trainees and is actively involved in several mentorship programs with the APA. She is an avid baker and yogi and enjoys reading and traveling -
Sharada Kalanidhi
Director of Data Science, Biochemistry - Genome Center
Current Role at StanfordParaphrasing the mathematician Alexander Grothendieck: the essential thing is to pose problems in the right framework.
Sharada is developing a new field, Mathematical Medicine, which applies pure mathematical frameworks to genomic and multi-omic data for quantitative, personalized diagnosis. This approach explores alternatives to prevailing cohort-based statistical paradigms, particularly in complex clinical cases that have resisted standard methods.
After more than a decade of research and close collaboration with biochemists at the Stanford Genome Technology Center (Dept. of Biochemistry), Sharada concluded that the mathematics currently used for multi-omic diagnosis is inadequate for the level of biological and clinical complexity being attempted. Her conclusion echoes the perspective of the mathematician Mikhail Gromov: “This area does not yet exist. It will have to be invented.” Mathematical Medicine represents one possible construction of such an area.
This field is focused on the development of an intermediate translation layer between cohort-based statistical models and individualized multi-omic diagnosis and clinical decision-making. Without this mathematical layer, the clinical adoption of multi-omic data- particularly for complex cases- has been limited. As a result, many complex, multi-system conditions remain undiagnosed or misdiagnosed for long periods, delaying effective treatment and, in some cases, allowing disease processes to worsen. Additionally, what is learned from rare and extreme cases proves highly informative for the rest of the population.
Further information on this field, including opportunities for early philanthropic partnerships, is available at: https://mathmed-2026.web.app/
