Machine Intelligence Lab


The Machine Intelligence Laboratory (MIL)  in the Computer Engineering Department specializes in deep learning research.  From pattern recognition, to smart device control, to video understanding, to natural language processing, the MIL works on core architectures and algorithms to teach next generation devices how to recognize objects, interact with people, navigate complex environments, and make temporal extrapolations. With seven state-of-the-art GPU servers, the MIL is able to process huge datasets and learn models with hundreds of millions of parameters.  In addition to software, students interface with hardware, developing both an effective access wheelchair and an autonomous golf cart. The MIL hosts deep learning seminars, online classes, reading groups, and will lead a graduate class entitled “Deep Learning” in the Spring of 2017.



  • Jan 30th-Feb 2nd: EI paper presentations on visual odometry/localization, distracted driver recognition, Milpet
  • Sun, Jan 29th: EI tutorial on deep learning
  • Dec 5th-8th: ICPR paper presentations on hierarchical, neural style, and key frame activity recognition (Cancun, Mexico)
  • Dec 1st: Visit Qualcomm, San Diego
  • Mon, Nov 28: Dr. Chienchung Chang, head of Qualcomm Multimedia R&D and Standards Team
  • Fri, Nov 18th: WNYISPW (NVIDIA, Mathworks visit)
  • Wed, Nov 16th, 4-4:30pm: partner university Kanazawa Institute of Technology (KIT)
  • Thurs, Nov 10th, 2:30-3:15: Honda Strategy Leader Carl Sommerville
  • Wed, Oct 19th: 10-11am: TI visit
  • Tues, Oct 18th, 2-3pm: Tesla visit
  • Fri, Sept 30th: CE graduate seminar
  • Thurs, Sept 29th: 2-2:30pm, Magic Leap visit
  • Wed, Sept 28th: ICIP paper presentation on LSTM fusion (Phoenix, AZ)
  • Wed, Sept 28th: ICIP “Deep Learning for Detection and Classification II” Session Chair
  • Mon, Sept 26th: Huawei Smart Device Summit (in Shenzhen, China)
  • Thurs, Sept 8th: Caitlin Esch, Marketplace, public radio show from LA.
  • Washington Post “Machines Evolve to Help, but not Replace, Humans”, Oct 26, 2015.  Includes quotes by Ptucha on behalf of lab

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