CV

Research Position

(Ongoing): Professor of Statistics, Département de mathématiques, Université du Québec à Montréal
2021-2022: CANSSI Distinguished Postdoctoral Fellow, Simon Fraser University & University of Victoria
- Supervisors : Farouk Nathou, Jiguo Cao and Mirza Faisal Beg

Education

2021: Ph.D. in Statistical Sciences, University of Toronto
- Thesis : Performance and accessibility of statistical learning algorithms for applied data analysis
- Supervisor : Dr. Jeffrey S. Rosenthal
2015: M.Sc. in Mathematics (Statistics), Université du Québec à Montréal
- Thesis : Narrow Artificial Intelligence for Real-Time Estimation of a Mobile Agent’s Location Using Hidden Markov Models
- Supervisor : Dr. Fabrice Larribe
2013: B.Sc. in Mathematics (Statistics), Université du Québec à Montréal

Research Operating Grants

2023-2028: Discovery Grant
- Natural Sciences and Engineering Research Council of Canada (NSERC)
2023-2025: Start-up Grant
- Université du Québec à Montréal

Awards

2021 : CRM StatLab Postdoctoral Fellowship - Declined
- Canadian Statistical Sciences Institute (CANSSI)
2021 : CANSSI Distinguished Postdoctoral Fellowship (DPF)
- Canadian Statistical Sciences Institute (CANSSI)
2020 : Doctoral Completion Award
- School of Graduate Studies, University of Toronto
2020 : Departmental Teaching Assistant Award
- Department of Statistical Sciences, University of Toronto
2019 : Ontario Graduate Scholarship (OGS)
2019 : Best Poster Award
- University of Toronto Statistics Graduate Student Research Day
2018 : Ontario Graduate Scholarship (OGS)
2015: Alexander Graham Bell Canada Graduate Scholarships-Doctoral (CGS D)
- Natural Sciences and Engineering Research Council of Canada (NSERC)
2015: Alma Mater Scholarship - Declined
- Université de Montréal
2014: Master’s research scholarship (B1)
- Fonds de Recherche du Québec sur la Nature et les Technologies (FRQNT)
2013: Alexander Graham Bell Canada Graduate Scholarships-Master (CGS M)
- Natural Sciences and Engineering Research Council of Canada (NSERC)
2013: Undergraduate student research award (USRA)
- Natural Sciences and Engineering Research Council of Canada (NSERC)
2013: Mathematics department excellence scholarship
- Université du Québec à Montréal
2012: Undergraduate student research award (USRA)
- Natural Sciences and Engineering Research Council of Canada (NSERC)
2011: Undergraduate student research award (USRA)
- Natural Sciences and Engineering Research Council of Canada (NSERC)

Publications

Functional Autoencoder for Smoothing and Representation Learning

Sidi Wu, Cédric Beaulac and Jiguo Cao

2024, Statistics and Computing

Constructing Ancestral Recombination Graphs through Reinforcement Learning

Neural Networks for Scalar Input and Functional Output

Sidi Wu, Cédric Beaulac and Jiguo Cao

2023, Statistics and Computing

Neuroimaging Feature Extraction using a Neural Network Classifier for Imaging Genetics

Cédric Beaulac, Sidi Wu, Erin Gibson, Michelle F. Miranda, Jiguo Cao, Leno Rocha, Mirza Faisal Beg and Farouk S. Nathoo

2023, BMC Bioinformatics

A moment-matching metric for latent variable generative models

Cédric Beaulac

2023, Machine Learning

Introducing a new high-resolution hand-written digits data set with writer characteristics

Cédric Beaulac and Jeffrey S. Rosenthal

2023, SN Computer Science

Predicting Time-to-conversion for Dementia of Alzheimer’s Type using Multi-modal Deep Survival Analysis

Ghazal Mirabnahrazam, Da Ma, Cédric Beaulac, Sieun Lee, Karteek Popuri, Hyunwoo Lee, Jiguo Cao, James E Galvin, Lei Wang and Mirza Faisal Beg

2023, Neurobiology of Aging

An evaluation of machine learning techniques to predict the outcome of children treated for Hodgkin-Lymphoma on the AHOD0031 trial

Cédric Beaulac, Jeffrey S. Rosenthal, Qinglin Pei, Debra Friedman, Suzanne Wolden and David Hodgson

2020, Applied Artificial Intelligence

BEST : A decision tree algorithm that handles missing values

Cédric Beaulac and Jeffrey S. Rosenthal

2020, Computational Statistics

Predicting University Students’ Academic Success and Major using Random Forests

Cédric Beaulac and Jeffrey S. Rosenthal

2019, Research in Higher Education

A Deep Latent-Variable Model Application to Select Treatment Intensity in Survival Analysis

Cédric Beaulac, Jeffrey S. Rosenthal and David Hodgson

2018, Proceedings of the Machine Learning for Health (ML4H) Workshop at NeurIPS 2018

Narrow Artificial Intelligence with Machine Learning for Real-Time Estimation of a Mobile Agents Location Using Hidden Markov Models

Cédric Beaulac and Fabrice Larribe

2017, International Journal of Computer Games Technology

Talks

Images, pixels, statistique et formes
May 25, 2024
XXVIe Colloque panquébécois de l'ISM, Université du Québec à Montréal, Montréal, Québec, Canada

Functional machine learning and applications
December 16, 2023
CMStatistics 2023 Conference, HTW Berlin University of Applied Sciences, Berlin, Germany

Neural network architectures for functional data analysis
October 20, 2023
McGill Statistics Seminar, McGill University, Montréal, Ontario, Canada

Integrating Deep Learning into Functional Data Analysis
July 13, 2023
ISBIS 2023 Conference, Brock University, Saint-Catherine, Ontario, Canada

Developing neural network architectures for functional data analysis
May 29, 2023
SSC 2023 Annual Meeting, Careleton University, Ottawa, Ontario, Canada

Neural Network Disease Classification Based Feature Extraction for Imaging Genetics.
June 03, 2022
SSC 2022 Annual Meeting, Simon Fraser University, Vancouver, British Columbia, Canada (Online)

Variational Autoencoders: an introduction to new applications and a new regularization approach.
October 13, 2021
University of Victoria Statistics Seminar, University of Victoria Statistics, Victoria, British Columbia, Canada

Démystifier les réseaux de neurones
May 05, 2021
Cégep Lionel-Groulx, Sainte-Thérèse, Québec, Canada

Performance and accessibility of statistical learning algorithms for applied data analysis.
December 18, 2020
PhD Defense, Toronto, Ontario, Canada

Auto-encodeur variationnel: vers de nouvelles applications et une mise à jour de la théorie.
November 05, 2020
Séminaire de STATQAM, Université du Québec à Montréal, Montréal, Québec, Canada

Génération d’images : Une application de l’apprentissage automatique.
March 15, 2019
SÉSÀM 2019, Université du Québec à Montréal, Montréal, Québec, Canada

Handling Missing Values with BEST
June 06, 2018
SSC 2018 Annual Meeting, McGill Universtiy, Montréal, Québec, Canada

Utilisation des chaînes de Markov cachés pour estimer la position d’un agent mobile.
January 14, 2017
SUMM 2017, McGill University, Montréal, Québec, Canada

Estimation de la position d’un agent mobile dans un environnement bornée grâce aux modèles de Markov cachés.
July 02, 2015
EMoSta Seminar, Montréal, Québec, Canada

Posters

Predicting Alzheimer’s disease progression in healthy and MCI subjects using multi-modal deep learning approach
August 01, 2022
AAIC 2022, San Diego, USA

Deep-Learning-Based Multi-modal Survival Analysis for Alzheimer’s Disease
June 20, 2022
OHBM 2022 Annual Meeting, Glasgow, UK

Neural Networks with Functional Responses (Poster Presentation Award)
May 30, 2022
SSC 2022 Annual Meeting, Online

A Linear State-Space Model to Predict Hourly Electricity Demand
June 01, 2020
SSC 2020 Annual Meeting, Online

Controllable content generator (Best Poster Award)
April 25, 2019
Statistics Graduate Student Research Day 2019, Toronto, Ontario, Canada

Supervision

Issam Moindjié

Ongoing, Postdoctoral fellow at Université du Québec à Montréal

Louis-Pierre Ménard

Ongoing, Research Intern at Université du Québec à Montréal

Valentin Larchevêque

2023, Research Intern at Université du Québec à Montréal

Sabrina Nunes

Ongoing, MS.c at Université du Québec à Montréal

Hélène Fourniotis

Ongoing, MS.c at Université du Québec à Montréal

Mélanie Raymond

Ongoing, MS.c at Université du Québec à Montréal

Ghazal Mirabnahrazam

2022, MS.c at Simon Fraser University

Yasaman Shahhosseini

Ongoing, Ph.D at University of Victoria

Sidi Wu

Ongoing, Ph.D at Simon Fraser University

Review and judging

2024 : Reviewer for Bioinformatics
2024 : External Reviewer for NSERC Discovery Programm - Committee 1508
2023 : Reviewer for a MITACS Accelerate proposal
2023 : Reviewer for the Journal of Machine Learning Research
2022 : Reviewer for the Journal of Agricultural, Biological, and Environmental Statistics
2022 : Judge for the 2022 CSSC presentation competition
2022 : Reviewer for Research in Higher Education
2021 : Reviewer for AERA Open
2017 : Reviewer for Studies in Higher Education

Teaching

Course Instructor
- (Ongoing) UQAM STT3030: Apprentissage Statistique
- (Ongoing) UQAM STT8330: Théorie de l’Apprentissage Statistique
- 2023 UQAM MAT2720: Processus Stochastique
- 2019 UofT STA302 : Methods of Data Analysis I
Statistical Consulting Mentor
- 2018-2020 UofT STA490: Statistical Consultation, Communication and Collaboration
Teaching Assistant
- 2019 STA414: Statistical Methods for Machine Learning II
- 2014 STT200: Statistics II
- 2012-2014 MAT2070: Stochastic Processes
- 2011-2013 MAT1085: Probability and Statistics

Statistical Consulting

2021 : Machine Learning Associate at Burkett Statistical Consulting

Language

Computer
- R, Python, C++, Matlab, Excel, Java, SAS
Human
- French, English, Spanish (intermediate)

Cédric Beaulac, Ph.D.

CV

Research Position

Education

Research Operating Grants

Awards

Publications

Talks

Images, pixels, statistique et formes May 25, 2024XXVIe Colloque panquébécois de l'ISM, Université du Québec à Montréal, Montréal, Québec, Canada

Functional machine learning and applications December 16, 2023CMStatistics 2023 Conference, HTW Berlin University of Applied Sciences, Berlin, Germany

Neural network architectures for functional data analysis October 20, 2023McGill Statistics Seminar, McGill University, Montréal, Ontario, Canada

Integrating Deep Learning into Functional Data Analysis July 13, 2023ISBIS 2023 Conference, Brock University, Saint-Catherine, Ontario, Canada

Developing neural network architectures for functional data analysis May 29, 2023SSC 2023 Annual Meeting, Careleton University, Ottawa, Ontario, Canada

Neural Network Disease Classification Based Feature Extraction for Imaging Genetics. June 03, 2022SSC 2022 Annual Meeting, Simon Fraser University, Vancouver, British Columbia, Canada (Online)

Variational Autoencoders: an introduction to new applications and a new regularization approach. October 13, 2021University of Victoria Statistics Seminar, University of Victoria Statistics, Victoria, British Columbia, Canada

Démystifier les réseaux de neurones May 05, 2021Cégep Lionel-Groulx, Sainte-Thérèse, Québec, Canada

Performance and accessibility of statistical learning algorithms for applied data analysis. December 18, 2020PhD Defense, Toronto, Ontario, Canada

Auto-encodeur variationnel: vers de nouvelles applications et une mise à jour de la théorie. November 05, 2020Séminaire de STATQAM, Université du Québec à Montréal, Montréal, Québec, Canada

Génération d’images : Une application de l’apprentissage automatique. March 15, 2019SÉSÀM 2019, Université du Québec à Montréal, Montréal, Québec, Canada

Handling Missing Values with BEST June 06, 2018SSC 2018 Annual Meeting, McGill Universtiy, Montréal, Québec, Canada

Utilisation des chaînes de Markov cachés pour estimer la position d’un agent mobile. January 14, 2017SUMM 2017, McGill University, Montréal, Québec, Canada

Estimation de la position d’un agent mobile dans un environnement bornée grâce aux modèles de Markov cachés. July 02, 2015EMoSta Seminar, Montréal, Québec, Canada

Posters

Predicting Alzheimer’s disease progression in healthy and MCI subjects using multi-modal deep learning approach August 01, 2022AAIC 2022, San Diego, USA

Deep-Learning-Based Multi-modal Survival Analysis for Alzheimer’s Disease June 20, 2022OHBM 2022 Annual Meeting, Glasgow, UK

Neural Networks with Functional Responses (Poster Presentation Award) May 30, 2022SSC 2022 Annual Meeting, Online

A Linear State-Space Model to Predict Hourly Electricity Demand June 01, 2020SSC 2020 Annual Meeting, Online

Controllable content generator (Best Poster Award) April 25, 2019Statistics Graduate Student Research Day 2019, Toronto, Ontario, Canada

Supervision

Review and judging

Teaching

Statistical Consulting

Language

Images, pixels, statistique et formes
May 25, 2024
XXVIe Colloque panquébécois de l'ISM, Université du Québec à Montréal, Montréal, Québec, Canada

Functional machine learning and applications
December 16, 2023
CMStatistics 2023 Conference, HTW Berlin University of Applied Sciences, Berlin, Germany

Neural network architectures for functional data analysis
October 20, 2023
McGill Statistics Seminar, McGill University, Montréal, Ontario, Canada

Integrating Deep Learning into Functional Data Analysis
July 13, 2023
ISBIS 2023 Conference, Brock University, Saint-Catherine, Ontario, Canada

Developing neural network architectures for functional data analysis
May 29, 2023
SSC 2023 Annual Meeting, Careleton University, Ottawa, Ontario, Canada

Neural Network Disease Classification Based Feature Extraction for Imaging Genetics.
June 03, 2022
SSC 2022 Annual Meeting, Simon Fraser University, Vancouver, British Columbia, Canada (Online)

Variational Autoencoders: an introduction to new applications and a new regularization approach.
October 13, 2021
University of Victoria Statistics Seminar, University of Victoria Statistics, Victoria, British Columbia, Canada

Démystifier les réseaux de neurones
May 05, 2021
Cégep Lionel-Groulx, Sainte-Thérèse, Québec, Canada

Performance and accessibility of statistical learning algorithms for applied data analysis.
December 18, 2020
PhD Defense, Toronto, Ontario, Canada

Auto-encodeur variationnel: vers de nouvelles applications et une mise à jour de la théorie.
November 05, 2020
Séminaire de STATQAM, Université du Québec à Montréal, Montréal, Québec, Canada

Génération d’images : Une application de l’apprentissage automatique.
March 15, 2019
SÉSÀM 2019, Université du Québec à Montréal, Montréal, Québec, Canada

Handling Missing Values with BEST
June 06, 2018
SSC 2018 Annual Meeting, McGill Universtiy, Montréal, Québec, Canada

Utilisation des chaînes de Markov cachés pour estimer la position d’un agent mobile.
January 14, 2017
SUMM 2017, McGill University, Montréal, Québec, Canada

Estimation de la position d’un agent mobile dans un environnement bornée grâce aux modèles de Markov cachés.
July 02, 2015
EMoSta Seminar, Montréal, Québec, Canada

Predicting Alzheimer’s disease progression in healthy and MCI subjects using multi-modal deep learning approach
August 01, 2022
AAIC 2022, San Diego, USA

Deep-Learning-Based Multi-modal Survival Analysis for Alzheimer’s Disease
June 20, 2022
OHBM 2022 Annual Meeting, Glasgow, UK

Neural Networks with Functional Responses (Poster Presentation Award)
May 30, 2022
SSC 2022 Annual Meeting, Online

A Linear State-Space Model to Predict Hourly Electricity Demand
June 01, 2020
SSC 2020 Annual Meeting, Online

Controllable content generator (Best Poster Award)
April 25, 2019
Statistics Graduate Student Research Day 2019, Toronto, Ontario, Canada