Mona Singh
Professor of Computer Science and the Lewis Sigler Institute for Integrative Genomics
Office:
420
Computer Science Building
Princeton,
NJ
08544
Phone: 609-258-2087
Interdisciplinary Research Area: Applied Math, Bioengineering, Data Science
Research Area: Computational biology and bioinformatics; computational science
Areas of Impact
Bioengineering and Health
Bioengineers at Princeton bring together fundamental questions about how living systems work with an engineering approach to solving problems. While much work in bioengineering aims to improve human health, advances in the field also help address other global challenges, such as sustainable food, energy, water, and materials.
Data Science
Data science accelerates discovery across nearly all areas of science, engineering, and social science. Students and faculty in this area create new data-analysis techniques and harness advanced computing and storage systems to solve problems in biology, the environment, materials science, communications, security, transportation, and many other areas.
Primary affiliation
Computer Science
Princeton has been at the forefront of computing since Alan Turing, Alonzo Church, and John von Neumann were among its residents. The department, now in a period of major growth, has strong groups in artificial intelligence and machine learning, theory, programming languages, graphics and vision, systems and networking, computer architecture, computational biology and neuroscience, security, privacy, and information technology policy.
Lewis-Sigler Institute for Integrative Genomics
The Lewis-Sigler Institute for Integrative Genomics creates innovative research and teaching programs at the interface of modern biology and the more quantitative sciences. Institute researchers find ways to understand and harness the explosion of information based on the genomic sequences of the human and experimental organisms. The institute also is founded on the realization that the most interesting and difficult problems in the quantitative disciplines, especially physics, chemistry and computer science, frequently lie in biological phenomena and applications.
