Texas Data Analytics is based out of Austin, TX. Our expertise lies in developing state of the art data analytic methods and applying them to today's most challenging problems. We regularly publish, present and contribute to many of the top data mining, machine learning and applied statistics conferences and have applied our expertise in many industrial settings, including Google, IBM, and Sabre Holdings.

Jason Davis

Jason Davis is currently finishing his PhD at the University of Texas at Austin. Jason brings expertise in both research and applied industrial research, along with a strong programming background.  He is a program committee member of the Knowledge Discovery in Data mining (KDD) conference, and recently won a best paper award at the International Conference on Machine Learning (ICML) for his work on learning distance functions for nearest neighbor searches.  He has applied his research to a broad set of domains, including web search, text mining, and statistical program debugging. More information about his research can be found on his academic home page. Jason is an entrepreneur and excels in fast-paced work environments, having worked with several early-stage startups and recently spending time at Google developing their next generation search technology. He received his B.S. from Cornell University.

Inderjit Dhillon, Ph.D.

Inderjit Dhillon is an associate professor at the University of Texas at Austin and a leading researching in the field of data mining, machine learning, and numerical algorithms. He has successfully applied his research to many real-world problems, having worked with Sabre, IBM and Syncata. He is best known for his work on computational algorithms in these areas, in particular on eigenvalue computations, clustering, co-clustering and matrix approximations. Software based on his research on eigenvalue computations is now part of all state-of-the-art numerical software libraries. Inderjit received the best paper award at the SIAM data mining conference in 2003. He received his B.Tech. degree from the Indian Institute of Technology at Bombay, and Ph.D. from the University of California at Berkeley. He is a member of the Association for Computing Machinery, the Institute of Electrical and Electronics Engineers, and the Society for Industrial and Applied Mathematics. More information about Inderjit can be found at his academic home page at the University of Texas at Austin.