Mudita Singhal is a Senior Research Scientist in the Bioinformatics Group. With more than eight years' experience working in interdisciplinary teams facilitating large data visualization and analysis, her expertise is in the areas of user interfaces, visual analytics, and applied machine learning. Her current research focuses on developing algorithms and visual paradigms for motif analysis.
Mudita has contributed significantly to several publicly available tools, including the Complex Pathway Simulator (COPASI), Bioinformatics Resource Manager (BRM), the Peptide Permutation and Protein Prediction (PQuad), and the Collective Analysis of Biological Interaction Networks (CABIN) softwares, as well as prediction algorithms such as DomainGA , domainSVM, and imPredict.
Dr. Singhal received her Ph.D. in Computer Science from Washington State University, a Masters in Computer Science and Bioinformatics from Virginia Tech, and a B.E. in Computer Science from Kurukshetra University. She has authored and co-authored more than 28 peer-reviewed journal and conference publications.