À vous de voter ! Qui remportera le Prix Hydro-Québec - Coup de cœur du public 2022 ? / It's your turn to vote! Who will win the Hydro-Quebec Public's Favourite Award 2022?

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Parmi les présentations orales d'aujourd'hui, laquelle a été votre coup de cœur ? / Which of today's student oral presentations was your favorite? *

Julien Pallage (Optimisation en temps-réel de réseaux électriques intelligents)

Arthur Chatton (La dialyse à l'ère digitale : prédiction et adaptation en temps réel)

Bill Xue (Analyse de modèles climatiques avec les VARIATIONAL AUTOENCODERS)

Istvan David (Inference of Simulators in Digital Twins by Reinforcement Learning)

Sacha Morin (StepMix : A Python package for Stepwise Estimation of Generalized Mixture Models)

Ève Campeau-Poirier (L'apprentissage automatique au service de la cosmologie en crise)

Moses Openja (An Empirical Study on the Usage of Automated Machine Learning Tools)

Alice Doucet Beaupré (Unsupervised niche discovery in the distribution of the tiger mosquito (Aedes albopictus))

Kellin Pelrine (Party Prediction on Twitter)

Raphael Zerbato (Optimal Audit with Scoring: an extension to machine learning models)

Maria Sadikov (Classifier les amas de galaxies avec des méthodes d'apprentissage automatique)

Firmin Ayivodji (Measuring Economic Activity using News-Based Sentiment Indices)

Patricia Gautrin (Les drones militaires peuvent-ils être vertueux?)

Tian Yue Ding (Prédiction des jours de crises d'épilepsie à partir du sommeil mesuré par un chandail connecté)

Clémentine Courdi (Understanding information about COVID-19: how reliability of favored sources and level of understanding influenced adherence to sanitary measures in Canada during the first year of the pandemic)

Bhargob Deka (Real-Time Uncertainty Modeling for Large-Scale Structural Health Monitoring)

Zichao Yan (Integrated pretraining with evolutionary information to improve RNA secondary structure prediction)

Esmaeil Ghorbani (Digital Twin for Damage Identification of Mechanical Systems Based on Physics-Informed Bayesian Inference)

Beheshteh T. Rakhshan (Tensor Networks for Machine Learning)

Xin Wang (Crowdkeeping in Last-mile Delivery)

Simon Faghel-Soubeyrand (Loss of face identification abilities affect visual and semantic brain computations)

Dmytro Humeniuk (Reinforcement learning assisted evolutionary search for autonomous systems testing)

Laurence Lachapelle-Bégin (L'autoformation professionnelle en intelligence numérique : quelles dynamiques entre les travailleur.euse.s et les organisations?)

Ammar Alsheghri (3D Deep learning for feature line extraction from surfaces of prepared teeth for crown reconstruction)

Myriam Cloutier (Tree species segmentation on multitemporal high-resolution UAV imagery using convolution neural networks)

Camille Rondeau Saint-Jean (Un réseau neuronal profond pour la reconnaissance individuelle d’oiseaux d’après leurs chants)

Mohammed Adba (Learning physics from equations and data)

Charlie Gauthier (By fear and by woe: fearful exploration for reliable robots)

Hamed Hojatian (Flexible Unsupervised Learning for Massive MIMO Subarray Hybrid Beamforming)

Michael Mayerhofer (Conception d'un réseau de neurones pour l'imagerie ultrasonore d'une sonde avec un relai ergodique)

Xiao Xia Liang (Auto-Detection Of Invalid Soil Spectra)

Rosnel Sessinou (When systemic risk meets post-selection inference)

Anne Imouza (The impact of social bots on public COVID-19 perceptions during the 2020 U.S. presidential election)

Anirudha Kemtur (AI-based modeling of brain and behavior: Combining neuroimaging, imitation learning and video games)

Alexis Leconte (Microscopie de localisation ultrasonore dynamique rapide in vivo à l'aide de la détection spatio-temporelle)

Mengying Lei (Bayesian Complementary Kernelized Learning for Multidimensional Spatiotemporal Data)

Nicolas Cabrera Malik (An exact method for the park-and-loop routing problem)

Jérôme St-Jean (Vêtements connectés et méthodes d'intelligence artificielle pour la détection de crises épileptiques)

Guillaume Gagné-Labelle (Généralisation en apprentissage semi-supervisé)

Steven Dahdah (Data-Driven Modeling and Control with the Koopman Operator)

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