About Us

We are pleased to announce the “Fifth IPM Advanced School on Computing: Artificial Intelligence”, which will be held by the Institute for Research in Fundamental Sciences (IPM) school of Computer Sciences, scheduled from 5-8 September 2021.

What is Our Goal?

This Summer School provides a set of invited lectures conducted by renowned experts from both academia and industry, to address the current challenges in Artificial Intelligence (AI) and Machine Learning (ML), with the motivation to educate the participants on the significances and potentials of AI applications in engineering. Participants have the chance to learn more about the latest machine learning and deep learning approaches, including relevant applications, particularly computer vision. All the invited speakers are leading experts in their fields of research.

  • Machine learning
  • Deep learning
  • Future Artificial Intelligence

2021
5-8, Sep

Virtual Online Event
IRAN

850
Tickets

16
Speakers

Speakers

Stephen Grossberg

Boston University

Ehsan Adeli

Stanford University

Ali Borji

Primer AI

Ali Eslami

Google DeepMind

Hamid Eghbal zadeh

JKU Institute of Computational Perception

Ali Ghadirzadeh

Stanford University

Kristen Grauman

Facebook AI

Sara Hooker

Google Brain

Hadis Karimipour

University of Calgary

Maryam Kouzehgar

SUTD-MIT International Design Center

Hossein Mobahi

Google AI

Neda Nategh

University of UTAH

Mohammad Taher Pilehvar

TeIAS

Hamed Pirsiavash

UC Davis

Cees Snoek

University of Amsterdam

Carl Vondrick

Columbia University

Nasrin Mostafazadeh

Verneek

Sahand Sharifzadeh

DeepMind/LMU

News

  • 2021-08-16 We are pleased to announce that the school registration link has been activated. Registration capacity is limited. The registration fee with a fifty percent discount is 200,000 100,000 Tomans.

  • 2021-08-12 Good news! Registration will start soon. School registration is from August 16 to 27. Get in touch with us via email asc@ipm.ir.

  • 2021-08-08 website is under construction ...

Event Schedule

Timing Title Lecturer
First day - 5.sep
15:30 -16:30 Prompting in Natural Language Processing Taher Pilevar
>16:30-17:00 See-mode technologies Startup talk
17:00-17:30 Deeplite Startup talk
18:00-19:00 Predicting Unpredictability Carl Vondrick
19:00-20:00 A tutorial on evaluating generative models Ali Borji
20:00-21:00 Self-supervised learning for visual recognition Hamed Pirsiavash
2nd day - 6.sep
15:30 -16:30 Deep Multi-Agent Reinforcement Learning for Multi-Target Pursuit-Evasion among a Swarm of Decentralized UAVs Maryam Kouzehgar
16:30-17:30 Representation Learning Without Labels Ali Eslami
18:00-19:00 From noisy spikes to robust perception Neda Nategh
19:00-20:00 Anticipating motion and dynamics in multiple levels of abstraction Ehsan Adeli
20:00-21:00 Self-Distillation Amplifies Regularization in Hilbert Space Hossein Mobahi
3rd day - 7.sep
15:30 -16:30 Learning Context Variables in Contextual Reinforcement Learning Hamid Eghbal-zadeh
17:00-17:30 How far have we come in giving our NLU systems common sense? Nasrin Mostafazadeh
18:00-19:00 Towards data-efficient deep reinforcement learning for robotics Ali Ghadirzadeh
19:00-20:00 Explainable and Reliable AI:
Comparing Deep Learning with Adaptive Resonance
Stephen Grossberg
20:00-21:00 Real- World Video AI Cees Snoek
4th day - 8.sep
15:30 -16:30 Poster Session ...
16:30-17:30 Poster Session ...
18:00-19:00 Classification by Attention: Scene Graph Classification with Prior Knowledge Sahand Sharifzadeh
19:00-20:00 Intelligent Cyber Security Analysis in IoT-enabled Critical Infrastructure Hadis Karimipour
20:00-21:00 Sights, sounds, and space: Audio-visual learning in 3D environments Kristen Grauman
21:00-22:00 What can compression teach us about deep learning generalization? Sara Hooker

Poster session schedule

Timing Room # / link Poster title Publisher Presenter Affiliation
Part 01 (15:30 - 16:30)
15:30 - 16:30 Enter the Room 1 The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks - Rahim Entezari TU Graz
15:30 - 16:30 Enter the Room 2 Classification by Attention: Scene Graph Classification with Prior Knowledge AAAI 2021 Sahand Sharifzadeh LMU Munich
15:30 - 16:30 Enter the Room 3 Multiresolution Knowledge Distillation for Anomaly Detection CVPR 2021 Mohammadreza Salehi University of Amsterdam
15:30 - 16:30 Enter the Room 4 Kernel Continual Learning ICML 2021 Mohammad Mahdi Derakhshani University of Amsterdam
15:30 - 16:30 Enter the Room 5 A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics IEEE Internet of Things Journal 2020 Ali Osia Sharif University of Technology
15:30 - 16:30 Enter the Room 6 Neural Response Interpretation Through the Lens of Critical Pathways CVPR 2021 Ashkan Khakzar Technical University of Munich
Part 02 (16:30 - 17:30)
16:30 - 17:30 Enter the Room 1 Representations in 3D Deep Learning ECCV 2020 Omid Poursaeed Facebook AI
16:30 - 17:30 Enter the Room 2 Image Manipulation using Scene Graphs and Scene Graph Generation ICCV 2021 Azade Farshad Technical University of Munich
16:30 - 17:30 Enter the Room 3 3D CNNs with Adaptive Temporal Feature Resolutions CVPR 2021 Mohsen Fayyaz University of Bonn
16:30 - 17:30 Enter the Room 4 Mean Shift for Self-Supervised Learning ICCV 2021 Soroush Abbasi Koohpayegani UMBC
16:30 - 17:30 Enter the Room 5 Asymtotics of Learning in Generalized Linear Models and Recurrent Neural Networks ICML 2021 Melika Emami ECE, UCLA
16:30 - 17:30 Enter the Room 6 FarsTail: A Persian Natural Language Inference Dataset ... Soroush Faridan University of Qom

Organizers

Mohammad
Sabokrou

IPM

Mohsen
Fayyaz

Bonn

Mohammad
Khalooei

AUT

Rahim
Entezari

TU Graz

Zahra
Rezvani

IPM

Sarah
Rastegar

UVA

Previously

Event videos and images from previous years is a great way to show people what to expect at the conference and entice them to join. (http://cs.ipm.ac.ir/asoc2020).

Event FAQs

Due to the COVID-19 situation, this event will be an online virtual event.

Yes, a signed certificate will be emailed to all participants after the event. Please do not email us about this.

Event Location

Due to the COVID-19 situation, this event will be an online virtual event.

Event Partner