Welcome to the Data-Driven Decision Making Lab (D3M)


Our lab reenvisions urban and consumer informatics from a data-driven decision-making perspective to forge sustainable, smarter cities and more efficient, consumer-responsive businesses.

Research Areas:

Machine Learning and Large-scale Data Analysis, Artificial Intelligence (AI), Information Retrieval, Social Media, Recommender Systems, Sequential Decision Optimization, Operations Research, Smart Cities Applications.

Lab News:

  • July 5, 2017: Professor Scott Sanner and D3M Post-doc Dusan Sovilj have just been awarded an OCE VIP I + NSERC Engage to investigate sequential and explainable deep learning models for anomaly detection in cybersecurity with Rank, Inc.
  • June 28, 2017: Professors Scott Sanner and William O’Brien (Carleton) and D3M PhD Student Brent Huchuk have just been awarded an NSERC CRD to pursue research on machine learning for residential HVAC with Ecobee, Inc.
  • April 24, 2017: Check out our IJCAI-17 paper on Planning in Deep Learned Models and a highly retweeted Arxiv paper on Hybrid Planning with Tensorflow by D3M PhD students Buser Say and Ga Wu and undergraduate researcher Yu Qing (Ivan) Zhou.
  • Dec 29, 2016: Iain Guilliard has won the 2016 Kikuchi-Karlaftis Best Paper Award at the 95th Annual Meeting of the Transport Research Board for his paper A Non-homogeneous Time Mixed Integer LP Formulation for Traffic Signal Control (video).
  • Dec 9, 2016: A paper on Deep Learning and Sequential Recommender Systems for personalized adaptive user interfaces has been accepted to Intelligent User Interfaces (IUI-17)!