Stanford University
Showing 14,141-14,150 of 34,423 Results
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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). -
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. Her work addresses a fundamental challenge in contemporary medicine: prevailing cohort-based diagnostic approaches are not always equipped to capture the biological mechanisms relevant to individual patients, particularly in long-pending, complex “outlier” cases.
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 not sufficient for the level of biological and clinical complexity being attempted, particularly for individual patients who lack relevant statistical cohorts. Her conclusion echoes the perspective of the mathematician Mikhail Gromov: “This area does not yet exist. It will have to be invented.” This gap has important clinical consequences: individual biological differences may be treated as “noise” or as "outliers" rather than as clinically meaningful information. As a result, many patients with complex or multi-system conditions remain undiagnosed or incorrectly diagnosed, sometimes for decades, delaying effective treatment and, in some cases, allowing disease processes to worsen.
Mathematical Medicine addresses these limitations by developing an intermediate translational layer between cohort-based statistical models and individualized multi-omic diagnosis and clinical decision-making. The approach reflects the data-first philosophy articulated by the late mathematician Jim Simons: “We don’t start with models. We start with data. We don’t have any preconceived notions.” By developing new mathematical frameworks for interpreting an individual’s genomic and multi-omic data, Mathematical Medicine seeks to seeks to let the data speak for itself while enabling quantitative, individualized diagnosis and clinical decision-making.
Sharada’s research has led to the diagnosis and identification of appropriate treatment pathways for patients with previously undiagnosed, complex conditions. These rare and atypical cases also reveal biological relationships not apparent in population-level analyses, leading to insights that can inform broader research, clinical applications, and drug development.
Further information on this field, including opportunities for early philanthropic partnerships, is available at: https://mathmed-2026.web.app -
Suman Kumar Kalavagunta
Graduate, Stanford Center for Professional Development
BioSuman is a technology and engineering leader with over 20 years of experience building and scaling large-scale platforms across commerce, payments, loyalty, and digital experiences. Most recently, he served as a Director of Engineering at Mastercard, leading engineering organizations responsible for platforms serving millions of users.
His interests include artificial intelligence, machine learning, distributed systems, platform architecture, and building technology that solves complex real-world problems. He is currently pursuing Stanford’s Artificial Intelligence Graduate Certificate to deepen his expertise in AI and its application to modern products and platforms.
Outside of technology, Suman is a lifelong chess player, former state champion in India, and co-founder of Chess Brains Academy, an initiative created from his passion for chess and education. -
Anusha Kalbasi, MD
Associate Professor of Radiation Oncology (Radiation Therapy)
BioDr. Kalbasi is a physician-scientist at the Stanford Cancer Institute. In the clinic, Dr. Kalbasi is a radiation oncologist specializing in the treatment of patients with sarcoma and other solid tumors, with expertise in early phase clinical trials related to immunotherapy, cellular therapy, and radiation therapy.
The Kalbasi laboratory studies cancer immunology, with a focus on understanding—and re-engineering—the molecular conversations that immune cells have with one another and with cancer cells, especially through cytokines. By mapping how these signals are sent, received, and interpreted within immune cells and cancer cells, the lab aims to design next-generation immunotherapies that deliver the right messages at the right time—making cancer-fighting cells more potent, more persistent, and more precise.
