Graduate Students Supervised by David Poole

Sanjana, Mehran, Matt, Mehrdad, Anuj, William, Charles, David, Anupam, David, July 2013.

Ph.D.

• Bahare Fatemi, Representation learning with explicit and implicit graph structures, 2023.
• Matthew Dirks, ongoing.
• Sayed Mehran Kazemi, Representing and learning relations and properties under uncertainty, 2018
• Mark Crowley, 2011, Equilibrium policy gradients for spatiotemporal planning
• Michael Chiang, 2011, Learning latent theories of relations and individuals
• Jacek Kisynski, 2010, Aggregation and Constraint Processing in Lifted Probabilistic Inference
• Rita Sharma, 2006, Probabilistic Inference with Large Discrete Domains.
• Rubén Morales-Menéndez, 2003, Real-time Monitoring and Diagnosis in Dynamic Systems Using Particle Filtering Methods, (Ph.D. from ITESM) co-supervised with Nando de Freitas.
• Carl Alphonce, 2000, A parsing explanation of linear movement asymmetry in natural language. Co-supervised with Henry Davis.
• Michael Horsch, 1998, Flexible Policy Construction by Information Refinement.
  
• Andrew Csinger, 1995, User Models for Intent-based Authoring,  co-supervised with Kelly Booth.
  
• Runping Qi, 1994, Decision Graphs: Algorithms and Applications to Influence Diagram Evaluation and High-Level Path Planning Under Uncertainty.
  
• Nevin Lianwen Zhang, 1994, A Computational Theory of Decision Networks
  
• Julian Craddock, 1993, Making Predictions Directly from Past Experiences
  
• Yang Xiang, 1992, Miltiply Sectioned Bayesian Belief Networks for Large Knowledge-Based Systems: An Application to Neuromuscular Diagnosis, co-supervised with Michael Beddoes.
  
• Pierre Gaboury, 1990, VLSI Architecture Design Using Predicate Logic, co-supervised with M.I. Elmasry
  
• Paul Van Arragon, 1990, Nested Default Reasoning for User Modelling
  
• Eric Neufeld, 1988, Construction of a Sound Nonnumeric Probabilistic Reasoner, co-supervised with Romas Aleliunas.
  

M.Sc.

• Melika Farahani, Transporting and Evaluating Predictive Models in Different Environments., 2022
• Wan Shing Martin Wang, Hierarchical structure and ordinal features in class-based linear models, 2021
• Ali Mohammad Mehr, Prediction and anomaly detection in water quality with explainable hierarchical learning through parameter sharing, 2020
• Ainaz Hajimoradlou, Predicting landslides using contour aligning convolutional neural networks, 2019
• Mohammad Amin Aghaee Rad, Machine learning of lineaments from magnetic, gravity and elevation maps, 2018
• Adnan Reza, essay, 2019
• Bahare Fatemi, 2017, Finding a Record in a Database
• Anupam Srivastava, Modeling ordinal data for recommendation system, 2014.
• Seyed Mehran Kazemi, 2014, Relational logistic regression
• Matthew Dirks, 2014, Sensing and sorting ore using a relational influence diagrams
• Sanjana Bajracharya, 2014, Interactive visualization for group decision-making. Cosupervised with Gunilla Öberg
• Anupam Srivastava, 2014, Modeling ordinal data for recommendation systems
• Chia-Li (Charles) Kuo, 2013, Probabilistic reasoning with undefined properties in ontologically-based belief networks
• Disha Al Baqui, 2007, Value-focused GAI network structure elicitation given a domain Ontology, co-supervised with Giuseppe Carenini.
• James Cook, 2007, Mechanism Design and Veto Mechanisms for Sequential Meeting Scheduling (essay).
• Mark Crowley, 2005, Shielding against conditioning side effects in graphical models.
• Oxana Chakoula, 2002, Predicting Users' Next Access to the Web Server
  
• Leslie Tung, 2002, A Clique Tree Algorithm Exploiting Context Specific Independence
  
• Rita Sharma, 2001, Symmetric Collaborative Filtering using the Noisy Sensor Model
  
• Peter Gorniak, 2000, Keyhole State Space Construction with Applications to User Modelling
  
• Carl Alphonce, 1992, Towards and Explanatory Division of Competence and Performance: A Language-Independent Parsing Scheme, co-supervised with Henry Davis.
  
• Michael Horsch, 1990, A dynamic approach to probabilistic inference using Bayesian networks
• Andrew Csinger, 1990, Implementing a Normative Theory of Communication in a Framework for Default Reasoning..