Recent Invited Workshops and Tutorials

All workshops and tutorials listed below are organized by iSMART Lab.

3rd Workshop on Automated Spatial and Temporal Anomaly Detection (ASTAD) (AAAI 2026)

2nd Workshop on Automated Spatial and Temporal Anomaly Detection (ASTAD) (WACV 2025)

1st Workshop on Automated Spatial and Temporal Anomaly Detection (ASTAD) (WACV 2024)

Deep Learning Methods for Unsupervised Time Series Anomaly Detection (AAAI 2024)

Deep Learning Methods for Unsupervised Time Series Anomaly Detection (IJCAI 2023)

Recent Invited Talks

5th Edition of Mila’s Partner Symposium | Partner Symposium - 2025

  • Prof. Narges Armanfard as Invited Speaker
  • Website

Distinguished Research Lecture

  • “Anomaly Detection in Time Series Data”
  • Prof. Narges Armanfard as Invited Speaker
  • McMaster University, Hamilton, Canada
  • Link

Airbus AI Summit 2025

  • “AI‑Driven Monitoring of Systems and Crew for Aerospace Safety and Resilience”
  • Prof. Narges Armanfard as Invited Speaker
  • Mirabel, Quebec, Canada
  • Website

Espace Aéro — Quebec’s Aerospace Innovation Zone - 2025

  • Quebec, Canada
  • Prof. Narges Armanfard as Invited Speaker
  • Website

Reseach Talks

The 40th Annual AAAI Conference on Artificial Intelligence (AAAI 2026)

  • Singapore
  • Website
  • Research Talks:
    • MultiTab: A Scalable Foundation for Multitask Learning on Tabular Data
    • EngineAD: A Real-World Vehicle Engine Anomaly Detection Dataset
    • Unveiling the Flaws: A Critical Analysis of Initialization Effect on Time Series Anomaly Detection

The 41st Conference on Uncertainty in Artificial Intelligence (UAI 2025)

  • Rio de Janeiro, Brazil
  • Website
  • Topics:
    • Contaminated Multivariate Time-Series Anomaly Detection with Spatio-Temporal Graph Conditional Diffusion Models

IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2025)

  • Tucson, Arizona
  • Website
  • Topics:
    • Cross-Task Affinity Learning for Multitask Dense Scene Predictions
    • Graph-Jigsaw Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection

The 36th British Machine Vision Conference (BMVC 2025)

  • Sheffield, United Kingdom
  • Website
  • Topics:
    • Zero-Shot Anomaly Detection with Dual-Branch Prompt Selection
    • Language-Guided Reinforcement Learning for Hard Attention in Few-Shot Learning

27th European Conference on Artificial Intelligence (ECAI 2024)

  • Santiago de Compostela, Spain
  • Website
  • Topics:
    • Open-Set Multivariate Time-Series Anomaly Detection

34th British Machine Vision Conference (BMVC 2023)

  • Aberdeen, Scotland
  • Website
  • Topics:
    • C3: Cross-instance guided Contrastive Clustering

European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2023)

  • Turin, Italy
  • Website
  • Topics:
    • Multivariate Time-Series Anomaly Detection with Temporal Self-Supervision and Graphs: Application to Vehicle Failure Prediction

Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-2023)

  • Washington DC, USA
  • Website
  • Topics:
    • Self-Supervised Learning for Anomalous Channel Detection in EEG Graphs: Application to Seizure Analysis

26th International Conference on Pattern Recognition (ICPR 2022)

  • Montreal, Canada
  • Website
  • Topics:
    • Attentive Task Interaction Network for Multi-Task Learning

IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2022)

  • Singapore
  • Website
  • Topics:
    • Self-Supervised Acoustic Anomaly Detection Via Contrastive Learning

IEEE International Conference on Image Processing (ICIP 2021)

  • Anchorage, Alaska, USA
  • Website
  • Topics:
    • IDECF: Improved Deep Embedding Clustering With Deep Fuzzy Supervision

IEEE International Conference on Systems, Man, and Cybernetics (SMC 2021)

  • Melbourne, Australia
  • Website
  • Topics:
    • Joint Selection using Deep Reinforcement Learning for Skeleton-based Activity Recognition

International Joint Conference on Neural Networks (IJCNN 2021)

  • Virtual Conference
  • Website
  • Topics:
    • Deep Successive Subspace Learning for Data Clustering

Teaching Activities

1. ECSE 551 Machine Learning for Engineers (4 credits)

  • Instructor: Prof. Narges Armanfard
  • Winter 2025, Fall 2024, Winter 2024, Fall 2023, Winter 2023, Fall 2022, Winter 2022, Fall 2021, Winter 2021, Fall 2020, Winter 2020
  • Course Outline

2. ECSE 689 Generative AI (4 credits)

  • Instructor: Prof. Narges Armanfard
  • Winter 2027

3. ECSE 206 Introduction to Signals and Systems (3 credits)

  • Instructor: Prof. Narges Armanfard
  • Winter 2025, Winter 2024, Winter 2022, Fall 2021, Fall 2020, Fall 2019
  • Course Outline