Stanford University
Showing 41-60 of 1,893 Results
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Thomas Kailath
Hitachi America Professor in the School of Engineering, Emeritus
BioThomas Kailath obtained a B.E.(Telecom) degree from the College of Engineering in Pune, India, in !956 and M.S. (1959) and Sc.D. (1961) degrees in Electrical Engineering from the Massachusetts Institute of Technology.
After a year at the Jet Propulsion Laboratories, he joined Stanford University in 1963 as an Associate Professor of Electrical Engineering, was promoted to Professor in 1968, and named to the Hitachi America Chair in 1988. He assumed Emeritus status in June 2001. His research has spanned a large number of engineering and mathematical disciplines, and he has mentored over a hundred doctoral and postdoctoral students. Their joint efforts have led to over 300 journal papers, several of which have received outstanding paper prizes; they have also led to a dozen patents and to several books and monographs. He has also co-founded and served as a director of several private and public high-technology companies. and has been
He is a fellow of the IEEE and a member of the US National Academy of Engineering, the US National Academy of Sciences, the American Academy of Arts and Sciences, the Indian National Academy of Engineering, the Academy of Sciences of the Developing World and the Royal Spanish Academy of Engineering. In 2006, he was inducted into the Silicon Valley Engineering Hall of Fame.
Other major honors include several IEEE medals and prizes, including the 2007 Medal of Honor in 2007, Guggenheim and Churchill Fellowships, and honorary degrees from universities in Sweden, Scotland, Spain and France. -
A Dale Kaiser
Member, Bio-X
Current Research and Scholarly InterestsHow are genes regulated to construct a developmental program? How do signals received from other cells change the program and coordinate it for multicellular development? The approach taken by our laboratory group to answer these questions utilizes biochemistry and genetics; genetics to isolate mutants that have particular defects in development and biochemistry to determine the molecular basis of the defects. We study swarming in Myxococcus xanthus that builds fruiting bodies.
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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). -
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
