IDEAL > Projects


Current/ Recent Projects at IDEAL

Post-Doc Openings

Candidates should have strong machine learning/computation/optimization/coding skills. Domain knowledge and track record in solving real-world problems is a plus. If you think you are well qualified, please send an email to jghosh at utexas.edu, with subject: IDEAL-POSTDOC.

  • High-throughput Phenotyping on Electronic Health Records using Multi-Tensor Factorization (NSF)
  • Monotonic Retargeting: A Scalable Learning Framework for Determining Order (NSF)
  • CAR-STOP: Communications and Radar-Supported Transportation Operations and Planning (TxDOT).

    This project involves distributed machine learning algorithms for collision detection/avoidance, trajectory and uncertainty modeling, smart transport infrastructure, etc.

  • Joint Topic and Network Modeling in Complex Environments (ARL/ONR)
  • Privacy-Aware Analysis of Healthcare Data (ORNL)
  • Simultaneous Decomposition and Predictive Modeling on Large Multi-Modal Data (NSF)
  • Analysis of usage and demographic data in very large wireless networks (SKT)
  • Inter-Agency “Co-opetition” via Hidden Web Databases (NHARP)
  • Mining of large-scale transactional data for informing better health-care policy

  • Some Older Projects