CHAIR Annual 2020

CHAIR Annual Workshop 2020

​The first CHAIR Annual was held as an online workshop on November 3rd, 2020.
Chalmers AI Research Centre (CHAIR) is now launching an annual workshop, highlighting AI and AI related research within Chalmers and with CHAIR core partners. 

We invite all AI interested researchers and others to join the workshop, listen in on the variety of projects that will be presented, and take part in the researcher speed dating sessions that we will run throughout the day. 

Presentations and videos from CHAIR Annual 2020 can be found here >

We are proud to present Professor Milind Tambe from Harvard University as keynote speaker on the subject Advancing AI for Social Impact.

Milind Tambe is Gordon McKay Professor of Computer Science, Director of Center for Research in Computation and Society at Harvard University. He is also Director "AI for Social Good" at Google Research in India.

Prof Milind Tambe is recipient of the IJCAI (International Joint Conference on AI) John McCarthy Award, ACM/SIGAI Autonomous Agents Research Award from AAMAS (Autonomous Agents and Multiagent Systems Conference), AAAI (Association for Advancement of Artificial Intelligence) Robert S Engelmore Memorial Lecture award, INFORMS (Institute for Operations Research and the Management Sciences) Wagner prize, the Rist Prize of the Military Operations Research Society, the Christopher Columbus Fellowship Foundation Homeland security award, International Foundation for Agents and Multiagent Systems influential paper award, best paper awards at conferences including AAMAS, IJCAI, IVA.

Due to the Covid19 situation this year’s event will be held online and the format will be a reporting workshop, where presentations are focused on those projects receiving funding from CHAIR. ​


​9:00 - 9:15 CHAIR 2020 and future plans - Ivica Crnkovic​

9:15 - 10:00 CHAIR Consortium 2020 & 2021 - CEVT, Volvo AB, Volvo Cars, Ericsson, Sahlgrenska Universitetssjukhuset 
Moderator Ivica Crnkovic

10:00 - 10:10 Speed dating I 

10:10 - 10:15 Break 

10:15 - 12:00 Session I - CHAIR senior researchers - overview of the projects  
Moderator Kolbjörn Tunström

  • ​​AI Engineering - Jan Bosch
  • AI Challenges in Industry 4.0 Applications - Knut Åkesson
  • CHAIR and Genie: a collaboration to improve gender equality at Chalmers - Mary Sheeran
  • Learning with feedback in multi agent systems - Devdatt Dubhashi
  • Understanding deep neural networks via information theory - Giuseppe Durisi
  • Flexible prediction and dimension reduction via regularized neural networks - Rebecka Jörnsten
  • 3D Perception and Geometric Deep Learning - Fredrik Kahl
  • Numerical Methods for Machine Learning in Data Starved Regimes - Ashkan Panay
  • Explanation-based learning to advance human-level AI - Karinne Ramirez Amaro
  • AI ethics at Chalmers - Olle Häggström
  • Data Science Research Engineers: Projects during 2020Vilhelm Verendel
12:00 - 13:00 Lunch break 

13:00 - 14:10 Session II - CHAIR PhD and PostDoc projects 
Moderators Ivica Crnkovic and Kolbjörn Tunström

  • Federated Learning: Model training on decentralized data - Hongyi Zhang, CSE
  • ViMCoR: Machine learning for motion prediction - Ze Zhang, E2
  • ViMCoR: Real-time planning of a Robot fleet - Sabino Francesco Roselli, E2
  • Vermillion: Verification of Machine Learning Algorithms  - Yinan Yu, CSE

  • Emergence of Efficient Communication in Multi-Agent Reinforcement Learning - Emil Carlsson, CSE
  • Studying generalization in machine learning using information theory - Fredrik Hellström, E2
  • Weight Correlation and Learning in Neural Networks - David Bosch, CSE
  • Learning & Understanding Human-Centered Robotic Manipulation Strategies - Maximilian Diehl, E2

  • Simulation-based approximate Bayesian inference and deep learning - Petar Jovanovski, MV
  • Stochastic continuous-depth neural networks - Oskar Eklund, MV
  • Contrastive hebbian learning in energy based models - Dorian Staudt Rasmus Kjær Høier, E2
  • Privacy Preserving Localization - Kunal Chelani, E2

  • Parameter estimation for road traffic models - Mike Pereira, MV
  • Towards Privacy-Protected Learning in Automotives - Shiliang Zhang, CSE
  • Real-Time Robust and AdaptIve Learning in ElecTric VEhicles - Liang Dai, CSE
  • Driver's Posture Recognition - Che-Tsung Lin, E2
  • DORA - Dexterous robot assistant for physical object manipulation - Yasemin Bekiroglu, E2

14:10  -  14:15 Break 

14:15 - 15:00 Session III - CHAIR Consortium Seed grant projects 
Moderators Giuseppe Durisi and Fredrik Kahl
Session  runs in parallel in two groups
Group A: health, education, DataStream security&privacy:
(Moderator Giuseppe Durisi)
  • ​Yata – Intelligent systems to improve and support education - Simon Petterson Fors, F
  • AI and Missingness in Diagnostics for Alzheimer’s Disease - Fredrik Johansson, CSE
  • eHRV - Using EEG to label HRV data for detection of Delayed Cerebral Ischema in Stroke Patients - Miroslaw Staron, CSE
  • Enhanced Security and Privacy for Wireless Federated Learning - Sina Rezaei Aghdam, E2
  • Automatic data validation in data-streams for machine learning - Lucy Ellen Lwakatare, CSE
Group B: industrial applications, chemistry, corrupted and degraded data, visual odometry
(Moderator Fredrik Kahl)

  • AI and the Competitiveness of Swedish Industry (AISI) - Vilhelm Verendel, CSE
  • AI, Big Data, Machine Learning and Metal-Organic Framework synthesis, analysis and design. A proof of concept study (MOF-CADS) - Lars Öhrström, K
  • Robust Federated Learning against Low-quality and Corrupted Data - Jun Li, E2
  • DegradeFX - Explicating and Measuring Data Degradation Effects on ML - Christian Berger, CSE
  • Online Lithium-ion Battery State of Health Prognostics - Kun Gao, ACE
  • Learning to Solve Robust Visual Odometry - Huu Le, E2

15:00 - 15:10 Speed dating II

15:10 - 15:15 Break

15:15-16:15  Keynote Speaker of CHAIR Annual 2020
Moderator Devdatt Dubhashi

Advancing AI for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline. Professor Milind Tambe, Director Center for Research in Computation and Society (CRCS) at Harvard University


Milind Tambe - Keynote Speaker of CHAIR Annual 2020 

Advancing AI for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline

Abstract: With the maturing of AI and multiagent systems research, we have a tremendous opportunity to direct these advances towards addressing complex societal problems. I focus on the problems of public health and wildlife conservation, and address one key cross-cutting challenge: how to effectively deploy our limited intervention resources in these problem domains. I present our deployments from around the world as well as lessons learned that I hope are of use to researchers who are interested in AI for Social Impact. Achieving social impact in these domains often requires methodological advances. I will highlight key research advances in topics such as computational game theory, multi-armed bandits and influence maximization in social networks as well as in integrating machine learning with such advances in the data to deployment pipeline. In pushing this research agenda, our ultimate goal is to facilitate local communities and non-profits to directly benefit from advances in AI tools and techniques.

About the speaker: Milind Tambe is Gordon McKay Professor of Computer Science and Director of Center for Research in Computation and Society at Harvard University; concurrently, he is also Director "AI for Social Good" at Google Research India. He is a recipient of the IJCAI John McCarthy Award, ACM/SIGAI Autonomous Agents Research Award from AAMAS, AAAI Robert S Engelmore Memorial Lecture award, INFORMS Wagner prize, Rist Prize of the Military Operations Research Society, Columbus Fellowship Foundation Homeland security award, AAMAS influential paper award, best paper awards at conferences such as AAMAS, IJCAI, IVA, and meritorious commendations from agencies such as the US Coast Guard and the Los Angeles Airport. Prof. Tambe is a fellow of AAAI and ACM.
Category Seminar
Location: Online, Zoom
Starts: 03 November, 2020, 09:00
Ends: 03 November, 2020, 16:15

Published: Mon 16 Nov 2020.