Carl Kesselman, PhD

EIT Member
Dean’s Professor, USC Viterbi School of Engineering, Daniel J. Epstein Department of Industrial and Systems Engineering
Professor of Computer Science and Preventative Medicine, Keck School of Medicine
Director, Informatics Division, USC Information Sciences Institute

EIT Member

Carl Kesselman is an EIT Member and Dean’s Professor in the USC Viterbi School of Engineering Daniel J. Epstein Department of Industrial and Systems Engineering and a professor of Computer Science and Preventative Medicine at Keck School of Medicine. He is a USC Information Sciences Institute Fellow, where he directs the Informatics Systems Research Division, and the Director of the Center of Excellence for Discovery Informatics in the Michelson Center for Convergent Biosciences. Kesselman leads ISI’s Informatics Systems Research division. Created to understand how to build informatics systems that can help tackle the hardest problems of great societal impact, the work of the division spans grid computing, information security, service-oriented architectures, and sociotechnical systems and reproducibility. Kesselman is an ISI Fellow, the Institute’s highest honor. One of the fathers of grid computing and the GLOBUS open-source toolbox, now the de facto grid computing standard, he has received numerous honors for his pioneering research including the Lovelace Medal from the British Computing Society and the Goode Memorial Award from the IEEE Computing Society. He is a Fellow of the British Computing Society and the Association for Computing Machinary. Kesselman joined ISI in 1997 as a USC Computer Science Department research associate professor.

Kesselman earned his PhD in Computer Science from the University of California at Los Angeles, a master’s degree in Electrical Engineering from the University of Southern California and a bachelor’s degree in Electrical Engineering from the State University of New York at Buffalo.

Research Focus

Convergent Bioscience
Discovery Informatics
Computer Science



Electrical Engineering, University of Southern California


Computer Science, University of California- Los Angeles


  • 2020 IEEE Computer Society Goode Memorial Award
  • 2018 Association for Computing Machinary Fellow
  • 2009 Viterbi School of Engineering Viterbi: Use Inspired Research Award
  • 2007 ComputerWorld Horizon Award
  • 2007 Internet2 Idea Award
  • 2006 Best Paper
  • 2006 University of Amsterdam Honorary Doctorate
  • 2003 The Federal Laboratory Consortium (FLC) Award for Excellence in Technology Transfer
  • 2003 USC Information Sciences Institute Fellow
  • 2003 World Technology Award for Information Technology Software Finalist
  • 2003 InfoWorld Top 10 Innovators
  • 2002 MIT Technology Review Award: Ten Technologies that Will Change the World
  • 2002 British Computing Society Lady Ada Lovelace Medal
  • 2002 R&D Magazine Most Promising New Technology Award (best of the R&D100)
  • 2002 R&D Magazine R&D 100 Award
  • 1998 Global Information Infrastructure Award in the Next Generation Infrastructure category


  • Director, Informatics Systems Research Division, USC Information Sciences Institute
  • Dean’s Professor of Industrial and Systems Engineering and Professor of Industrial and Systems Engineering, Computer Science, and Preventive Medicine, University of Southern California
  • Director, Center of Excellence for Discovery Informatics, USC Michelson Center for Convergent Biosciences
  • Professor, Preventive Medicine, Keck School of Medicine of USC
  • Professor, Computer Science, USC Viterbi School of Engineering
  • Professor, Herman Ostrow School of Dentistry of USC

Selected Publications

Madduri, R., Chard, K., D’arcy, M., Jung, S.C., Rodriguez, A., Sulakhe, D., Deutsch, E., Funk, C., Heavner, B., Richards, M., Shannon, P., Glusman, G., Price, N., Kesselman, C., & Foster, I. (2019) Reproducible big data science: A case study in continuous FAIRness. PLoS ONE 14(4): e0213013.  

Lindstrom, N.O., McMahon, J.A., Guo, J., Tran, T., Guo, Q., Rutledge, E., Parvez, R.K., Saribekyan, G., Schuler, R.E., Liao, C., Kim, A.D., Abdelhalim, A., Ruffins, S.W., Thornton, M.E., Basking, L., Grubbs, B., Kesselman, C., & McMahon, A.P. (2018). Conserved and divergent features of human and mouse kidney organogenesis. Journal of the American Society of Nephrology, 29(3), 785-805.  

Sepehrband, F., Lynch, K. M., Cabeen, R. P., Gonzalez-Zacarias, C., Zhao, L., D’Arcy, M., Kesselman, C., Herting, M. M., Dinov, I. D., Toga, A. W., & Clark, K. A. (2018). Neuroanatomical morphometric characterization of sex differences in youth using statistical learning. NeuroImage, 172, 217–227.     

Oxburgh, L., Carroll, T. J., Cleaver, O., Gossett, D. R., Hoshizaki, D. K., Hubbell, J. A., Humphreys, B.D., Jain, S., Jensen, J., Kaplan, D.L., Kesselman, C., Ketchum, C.J., Little, M.H., McMahon, A.P., Shankland, S.J., Spence, J.R., Valerius, M.T., Wertheim, J.A., Wessely, O., Zheng, Y. & Drummond, I.A. (2017). (Re) Building a kidney. Journal of the American Society of Nephrology, 28(5), 1370-1378.     

Dinov, I.; Heavner, B., Tang, M., Glusman, G., Chard, K., Darcy, M., Madduri, R., Pa, J., Spino, C., Kesselman, C., Foster, I., Deutsch, E., Price, N., Van Horn, J., Ames, J., Clark, K., Hood, L., Hampstead, B., Dauer, W. & Toga, A. (2016). Predictive big data analytics: a study of Parkinson’s disease using large, complex, heterogeneous, incongruent, multi-source and incomplete observations. PloS one, 11(8), e0157077.    

Brinkley, J., Fisher, S., Harris, M., Holmes, G., Hooper, J., Jabs, E., Jones, K., Kesselman, C., Klein, O., Maas, R., Marazita, M., Selleri, L., Spritz, R., van Bakel, H., Visel, A., Williams, T., Wysocka, J., Chai, Y., Aho, R., Alkuraya, F., Barozzi, I., Chard, K., Cox, T., Cunningham, M., Detwiler, L., Donovan, M., Feingold, E., Fitzpatrick, D., Green, J., Grimaldi, A., Grishina, I., Hallgrimsson, B., Harris, M., Ho, T.-V., Hochheiser, H., Leslie, E., Li, H., Liao, E., Mejino, J., Mio, W., Nowak, C., Parada, C., Park, P., Pennacchio, L., Potter, S., Rubin, E., Ruffins, S., Samuels, B., Sanchez-Lara, P., Schuler, R., Shapiro, L., Spurrell, C., Stoler, J., Sunyaev, S., Thomas, P., Welsh, I., Williams, C. & Fukuda-Yuzawa, Y. The facebase consortium: A comprehensive resource for craniofacial researchers. Development (Cambridge), 2016, 143, 2677-2688      

Toga, A. W., Foster, I., Kesselman, C., Madduri, R., Chard, K., Deutsch, E. W., Price, N.D., Glusman, G., Heavner, B.D., Dinov, I.D., Ames, J., Van Horn, J., Kramer, R. & Hood L. (2015). Big biomedical data as the key resource for discovery science. Journal of the American Medical Informatics Association, 22(6), 1126-1131.  

Foster, I., & Kesselman, C. (2003). The Grid 2: Blueprint for a New Computing Infrastructure, 2nd Edition. Morgan Kauffman.  

Foster, I., Kesselman, C., Nick, J. M., & Tuecke, S. (2002). Grid services for distributed system integration. Computer, 35(6), 37-46.  Foster, I., Kesselman, C., & Tuecke, S. (2001). The anatomy of the grid: Enabling scalable virtual organizations. The International Journal of High Performance Computing Applications, 15(3), 200-222.