Data-Driven Decision Making Lab | Department of Mechanical and Industrial EngineeringData-Driven Decision Making Lab

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

Mission:

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:

Jan 9, 2023: Check out an outstanding summary overview of our IPM 2023 article on Unintended Bias in Language Model-driven Conversational Recommendation written by D3M MASc graduate Tianshu (Tina) Shen.
Oct 9, 2022: D3M is running the ICAPS 2023 Probabilistic Planning and Reinforcement Learning Competition. Please contact Dr. Ayal Taitler if you have any questions, suggestions, or are interested in participating.
June 17, 2020: Congratulations to D3M MASc student Zheda (Marco) Mai who won 1st place in the CVPR 2020 CLVISION Challenge with his entry Batch-level Experience Replay with Review.
Feb 28, 2020: Professor Sanner has received a Google Faculty Research Award in Machine Learning and Data Mining to pursue research on Deep Conversational Recommender Systems.
Aug 17, 2019: We’re co-organizing the AAAI-20 Workshop on Interactive and Conversational Recommendation Systems (WICRS) with colleagues from Google and U. of Michigan.
May 25, 2018: Zhijiang (Tony) Ye’s paper with Buser Say entitled Symbolic Bucket Elimination for Piecewise Continuous Constrained Optimization has received the Student Paper Award at CPAIOR-18.
June 28, 2017: Professors Scott Sanner and William O’Brien (Carleton) and D3M student Brent Huchuk have been awarded an NSERC CRD to pursue research on machine learning for residential HVAC with Ecobee, Inc.
Dec 29, 2016: Iain Guilliard has won the 2016 Kikuchi-Karlaftis Best Paper Award of the Transport Research Board for his paper A Non-homogeneous Time Mixed Integer LP Formulation for Traffic Signal Control (video).