Events: Informations- och kommunikationsteknik events at Chalmers University of TechnologyFri, 30 Oct 2020 23:40:55 +0100 to CHAIR Annual Workshop 2020<p>Online, Zoom</p><p>​The first CHAIR Annual is held as an online workshop on November 3, 2020.</p><div>​​</div> <div>Chalmers AI Research Centre (CHAIR) is now launching an annual workshop, highlighting AI and AI related research within Chalmers and with CHAIR core partners. <div><br /></div> <div> 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. </div> <div><br /></div> <div>We are proud to present <strong>Professor Milind Tambe from Harvard University as keynote speaker</strong> on the subject Advancing AI for Social Impact.</div> <div><br /></div> <div><span><img src="/SiteCollectionImages/Centrum/CHAIR/events/milind_tambe_180px.jpg" class="chalmersPosition-FloatLeft" alt="" style="margin:5px 15px" /><strong><span style="display:inline-block"></span></strong></span>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 &quot;AI for Social Good&quot; at Google Research in India. <p>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. <br /></p> <br /></div> <div>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. ​<br /></div> <div><br /></div> </div> <a href="" target="_blank"><div><h3 class="chalmersElement-H3">Register for CHAIR Annual &gt;</h3></div> ​</a><div> </div> <h2 class="chalmersElement-H2">Programme</h2> <div> </div> <div><br /></div> <div> <strong>​9:00 - 9:15</strong> CHAIR 2020 and future plans - Ivica Crnkovic​</div> <div><br /><div><strong>9:15 - 10:00</strong> CHAIR Consortium 2020 &amp; 2021 - CEVT, Volvo AB, Volvo Cars, Ericsson, Sahlgrenska Universitetssjukhuset</div> <div><br /><strong>10:00 - 10:10 </strong>Speed dating I </div> <div><br /></div> <div><strong>10:10 - 10:15</strong> Break </div> <div><br /></div> <div><strong>10:15 - 12:00</strong> Session I - CHAIR senior researchers - overview of the projects <br /><br /></div> </div> <div><ul><li><strong>​​AI Engineering</strong> - Jan Bosch</li> <li> <strong>AI Challenges in Industry 4.0 Applications</strong> - Knut Åkesson<br /></li> <li><strong>CHAIR and Genie: a collaboration to improve gender equality at Chalmers</strong> - Mary Sheeran<br /></li> <li><strong>Learning with feedback in multi agent systems</strong> - Devdatt Dubhashi<br /></li> <li><strong>Understanding deep neural networks via information theory</strong> - Giuseppe Durisi<br /></li> <li><strong>Flexible prediction and dimension reduction via regularized neural networks</strong> - Rebecka Jörnsten<br /></li> <li><strong>3D Perception and Geometric Deep Learning</strong> - Fredrik Kahl<br /></li> <li><strong>Numerical Methods for Machine Learning in Data Starved Regimes</strong> - Ashkan Panay<br /></li> <li><strong>Explanation</strong><span><strong><span style="display:inline-block">-based learning to advance human-level AI </span></strong></span><span style="font-family:-webkit-standard;font-size:medium;font-style:normal;font-weight:normal;letter-spacing:normal;text-align:left;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration:none;display:inline !important;float:none"> - </span>Karinne Ramirez Amaro<br /></li> <li><strong>AI ethics at Chalmers</strong> - Olle Häggström<br /></li> <li>Vilhelm Verendel<br /></li></ul></div> <div> <div><strong>12:00 - 13:00</strong> Lunch break </div> <div><br /></div> <div><strong>13:00 - 14:00</strong> Session II - CHAIR PhD and PostDoc projects <br /><br /></div> <div><ul> <li>Hongyi Zhang, CSE</li> <li>Ze Zhang, E2</li> <li>Sabino Francesco Roselli, E2</li> <li>Yinan Yu, CSE</li> <br /> <li>Emil Carlsson, CSE</li> <li>Fredrik Hellström, E2</li> <li>David Bosch, CSE</li> <li>Maximilian Diehl, E2</li> <br /> <li>Petar Jovanovski, MV</li> <li>Oskar Eklund, MV</li> <li>Dorian Staudt, E2</li> <li>Kunal Chelani, E2</li> <br /> <li>Mike Pereira, MV</li> <li>Shiliang Zhang, CSE</li> <li>Liang Dai, CSE</li> <li>Che-Tsung Lin, E2</li> </ul></div> <div><br /></div> <div><strong>14:00 - 14:10</strong> Speed dating II </div> <div><br /></div> <div><strong>14:10  -  14:15</strong> Break </div> <div><br /></div> <div><strong>14:15 - 15:00</strong> Session III - CHAIR Consortium Seed grant projects </div> <div><br /><ul><li><strong>​Yata – Intelligent systems to improve and support education</strong> - Simon Petterson Fors, F<br /></li> <li><strong>AI and the Competitiveness of Swedish Industry (AISI)</strong> - Vilhelm Verendel, CSE</li> <li><strong>AI, Big Data, Machine Learning and Metal-Organic Framework synthesis, analysis and design. A proof of concept study (MOF-CADS)</strong> - Lars Öhrström, K</li> <li><strong>AI and Missingness in Diagnostics for Alzheimer’s Disease</strong> - Fredrik Johansson, CSE</li> <li><strong>eHRV - Using EEG to label HRV data for detection of Delayed Cerebral Ischema in Stroke Patients</strong> - Miroslaw Staron, CSE</li> <li><strong>Robust Federated Learning against Low-quality and Corrupted Data</strong> - Jun Li, E2</li> <li><strong>Enhanced Security and Privacy for Wireless Federated Learning</strong> - Sina Rezaei Aghdam, E2</li> <li><strong>Online Lithium-ion Battery State of Health Prognostics</strong> - Kun Gao, ACE</li> <li><strong>Automatic data validation in data-streams for machine learning</strong> - Lucy Ellen Lwakatare, CSE</li> <li><strong>DegradeFX - Explicating and Measuring Data Degradation Effects on ML</strong> - Christian Berger, CSE</li> <li><strong>Learning to Solve Robust Visual Odometry</strong> - Huu Le, E2</li></ul></div> <div><br /></div> <div><strong>15:00 - 15:10</strong> Speed dating III </div> <div><br /></div> <div><strong>15:10 - 15:15</strong> Break </div></div> <div> </div> <div><br /></div> <div> </div> <div><strong>15:15-16:15 Advancing AI for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline</strong> Keynote talk by Professor Milind Tambe, Director Center for Research in Computation and Society (CRCS) at Harvard University<br /></div> <div> </div> <div><br /></div> <div> </div> <div><br /></div> ​​​​​ 2020 – Virtual Worlds for Artificial Intelligence<p>Online</p><p>Wallenberg AI, Autonomous Systems and Sofware Program, WASP yearly conference.</p>​​<div>The flagship conference WASP4ALL this year presents high-profile international speakers, and researchers from WASP and Swedish industry on the topic “Virtual Worlds for Artificial Intelligence”.<div><br /><div>Explore how simulation and artificially generated environments can facilitate machine learning and other AI-development. If you are interested in technology, methods, challenges and problems – this is a conference you don’t want to miss! The conference is an open, virtual conference, not limited to the WASP community. The number of participants is limited – first come-first serve <br /></div> <div><br /></div> <div><a href="" target="_blank">Register and read more at &gt;​</a></div> <div><br /></div></div></div> on Research with Ashkan Panahi<p>Online, Zoom</p><p>Dynamics of Machine Learning: Toward Demystifying Neural Networks</p><div><br /></div> 6 November 2020, 13.00 (Swedish time)<br />Online, Zoom​​<div><br /></div> <div><h3 class="chalmersElement-H3">Title: Dynamics of Machine Learning: Toward Demystifying Neural Networks</h3> <div><br /><div><strong>Abstract: </strong>We review a recent trend in analyzing machine leaning techniques that unlike the traditional studies, incorporates the role of numerical methods such as optimization algorithms. We will refer to this approach by the term “Dynamics of Machine Leaning”. We discuss how the study of the dynamics of machine learning has provided promising answers to some of the fundamental questions about the learning behavior of artificial neural networks. In this regard, we present potential ideas and relevant observations. Further, we present the application of the dynamics of machine learning in understanding information distillation in neural networks.​</div></div></div> <div><br /></div> <h3 class="chalmersElement-H3"><a href="">Register for Spotlight on Research with Ashkan Panahi &gt;​</a></h3> <div><br /></div> <div><strong><img src="/SiteCollectionImages/Centrum/CHAIR/events/Ashkan_Panahi_180px.jpg" class="chalmersPosition-FloatLeft" alt="" style="margin:5px 10px" />About the sepaker:</strong> Ashkan Panahi is an assistant professor at the Computer Science and Engineering Department at Chalmers University of Technology, Sweden. He received his BSc and MSc degrees in electrical and communication systems engineering from Iran University of Science and Technology (IUST) (2008) and Chalmers University (2010). He also received his PhD degree in Signal Processing from the Electrical Engineering Department at Chalmers (2015). </div> <div><br /></div> <div>He has held multiple other research positions such as visiting research student at California Institute of Technology (Caltech 2014), U.S. National Research Council Research Associate (2016-2018) and Postdoctoral Researcher at North Carolina State University (2018-2019). His research interest spans a broad range of topics in machine learning and data science, including optimization algorithms, statistical analysis and probabilistic methods, compressed sensing, and statistical detection and estimation theory. </div> ​ Talks with Aravind Srinivasan<p>Zoom</p><p>​Fairness in AI and in Algorithms</p>November 12, 2020, 3:00-4:00 pm, Swedish time<div>Onlinne, Zoom​​</div> <div><br /></div> <div><h3 class="chalmersElement-H3">Title: ​Fairness in AI and in Algorithms</h3> <div><br /><div><strong>Abstract: </strong>With the increasing role played by AI and algorithms in our lives, it is well-recognized now that fairness should be a key aspect of such AI systems, to avoid automated decision-making that may (inadvertently) be biased. After surveying some of the approaches considered in this general area, we will discuss some of our work on fairness -- particularly in unsupervised learning. </div> <div><br /></div> <h3 class="chalmersElement-H3"><a href="" target="_blank">Register for AI Talks with Aravind Srinivasan &gt;​</a></h3> <h3 class="chalmersElement-H3"><br /><img src="/SiteCollectionImages/Centrum/CHAIR/events/srinivasan_180px.jpg" class="chalmersPosition-FloatLeft" alt="" style="margin:5px 10px" />About the speaker</h3> <div> Aravind Srinivasan is a Distinguished University Professor and a Professor with the Department of Computer Science and the Institute for Advanced Computer Studies at the University of Maryland, College Park, USA. He received his undergraduate degree from the Indian Institute of Technology, Madras, and his Ph.D. from Cornell University. His research interests include randomized algorithms, algorithms and models in AI, E-commerce, public health, digital health, networking, social networks, and combinatorial optimization. </div> <div><br /></div> <div> He is Editor-in-Chief of the ACM Transactions on Algorithms, and an Editor for Theory of Computing (Managing Editor, 2006-2019) as well as for the Journal of the IISc. He is an elected Fellow of six professional societies: ACM, AAAS, IEEE, AMS, EATCS, and SIAM. He was elected a Member of Academia Europaea, the Academy of Europe, in 2018. He received a Distinguished Alumnus Award from his alma mater IIT Madras. He also received the Distinguished Faculty Award from the Board of Visitors of the College of Computing, Mathematical, and Natural Sciences (University of Maryland). He is a recipient of the Dijkstra Prize and the Danny Lewin Award. </div></div></div> Matchmaking workshop - Volvo Cars, Volvo Group, CEVT<p>Online</p><p></p>​​The Chalmers Artificial Intelligence Research Centre (CHAIR) is organizing a joint online workshop with Volvo Cars, Volvo Group, CEVT to facilitate future collaboration in the area of artificial intelligence and machine learning. General attendance is open to all Chalmers researchers, as well as GU researchers from joint GU/Chalmers departments. This workshop also serves as a matchmaking event for the upcoming <a href="/en/centres/chair/news/Pages/Call-for-CHAIR-Consortium-Projects-2021.aspx">Call for CHAIR Consortium 1- and 2-year Projects 2021</a>. <div><br /></div> <h3 class="chalmersElement-H3"> Program</h3> <div>13:00 – 13:05 Short introduction to CHAIR and the call (5 minutes) </div> <div>13:05 – 13:20 Short introduction on AI at Volvo Cars, Volvo Group, and CEVT (5 min. for each partner) </div> <div>1<span style="background-color:initial">3:20 – 14:20 Pitch presentations from Chalmers/GU researchers (3 mins each) for up to 1 hour </span></div> <div><span style="background-color:initial">14:20     5 to 10 min. break</span></div> <div><span style="background-color:initial">14:30 – 15.30 Presentations from Volvo Cars, Volvo Group, and CEVT for up to 1 hour </span></div> <div><span style="background-color:initial">15:30 – 15:55 Short small-group meetings</span></div> <div><span style="background-color:initial">15:55 – 16.00 Wrap and next steps </span></div> <div><span style="background-color:initial"><br /></span></div> <div><span style="background-color:initial"> <a href="" target="_blank">To register for this event, please fill in this form &gt;​</a></span></div> <div><span style="background-color:initial">The deadline is November 6th, 2020, 17:00. </span></div> <div><span style="background-color:initial"><br /></span></div> <div><span style="background-color:initial"> If want to present your work, please fill in the relevant sections in the registration form. You will be contacted to submit your slides by November 6th, 2020. Due to time constraints, a limited number of attendees will be able to present their work in 3 to 4 minutes. Priority is given to those researchers who have an identified partner from Volvo Cars, Volvo Group, and CEVT for the upcoming call. </span></div> <div><span style="background-color:initial"><br /></span></div> <h3 class="chalmersElement-H3"><span>Organizers</span></h3> <div><span style="background-color:initial">Department of Computer Science and Engineering: Morteza Haghir Chehreghani and Elad Michael Schiller </span></div> <div><span style="background-color:initial"><br /></span></div> <div><span style="background-color:initial">Contact person: <br /><a href=""></a></span></div> Talks with Bill Dally<p>Online, Zoom</p><p>November 19, 2020 4.00-5.00 pm, Swedish time</p><p><br /></p> <h2 class="chalmersElement-H2">A​bout the speaker</h2> <p><img src="/SiteCollectionImages/Centrum/CHAIR/events/AI_Talks_BillDally_180px.jpg" class="chalmersPosition-FloatRight" alt="" style="margin:5px 10px" />Dally develops efficient hardware for demanding information processing problems and sustainable energy systems. His current projects include domain-specific accelerators for deep learning, bioinformatics, and SAT solving; redesigning memory systems for the data center; developing efficient methods for video perception; and developing efficient sustainable energy systems. His research involves demonstrating novel concepts with working systems. Previous systems include the MARS Hardware Accelerator, the Torus Routing Chip, the J-Machine, M-Machine, the Reliable Router, the Imagine signal and image processor, the Merrimac supercomputer, and the ELM embedded processor. His work on stream processing led to GPU computing. His group has pioneered techniques including fast capability-based addressing, processor coupling, virtual channel flow control, wormhole routing, link-level retry, message-driven processing, deadlock-free routing, pruning neural networks, and quantizing neural networks.</p> <p>Bio from: <a href=""></a><br /></p> on Research with Yasemin Bekiroglu<p>Online, Zoom</p><p>In this Spotlight on Research talk Yasemin Bekiroglu will handle the subject Learning from vision and touch for robotic grasping and manipulation.</p><div><br /></div> 20 Nov 2020, 13.00 (Swedish time)<br />Online, Zoom <h3 class="chalmersElement-H3">Title: ​​Learning from vision and touch for robotic grasping and manipulation </h3> <div><strong><br /></strong></div> <div> </div> <div><strong>Abstract:</strong> Robots are envisioned as capable machines who easily navigate and interact in a world built for humans. However, looking around us we see robots mainly confined to factories only performing repetitive tasks in environments built such as to circumvent their limitations. The central question of my research is how we can create robots that are capable of adapting such that they can co-inhabit our world. This means designing systems that are capable of functioning in unstructured environments that are continuously changing with unlimited combination of shapes, sizes, appearance, and positions of objects, able to understand, adapt and learn from humans, and importantly do so from small amounts of data. <div><br /></div> <div>In specific my work focuses on grasping and manipulation, fundamental aspects to enable a robot to interact with humans in our environment, along with dexterity (e.g. to use objects/tools successfully) and high-level reasoning (e.g. to decide about which object/tool to use). Despite decades of research, robust autonomous grasping and manipulation approaching human skills remains an elusive goal. One main difficulty lies in dealing with the inevitable uncertainties in how a robot perceives the world. Our environment is dynamic, has a complex structure and sensory measurements are noisy and associated with a large degree of uncertainty which poses challenges to avoid failures. </div> <div><br /></div> <div> In my research I have developed methodologies that enable a robot to interact with natural objects and learn about object properties and relations between tasks and sensory streams. I have developed tools that allow a robot to use multiple streams of sensory data in a complementary fashion. In this talk I will specifically address how a robot can use vision and touch to address grasp related questions e.g. estimating unknown object properties such as shape, grasp planning, analysis and adaptation. </div> <div><br /></div> <h2 class="chalmersElement-H2">Registration for this event will open in November</h2> <div><br /></div> <div> <strong><img src="/SiteCollectionImages/Centrum/CHAIR/events/yasemin_bekiroglu_180px.jpg" class="chalmersPosition-FloatLeft" alt="" style="margin:5px 10px" />About the speaker: </strong>Yasemin Bekiroglu is an Assistant Professor in the Automatic Control research group. She completed her Ph.D. at the Royal Institute of Technology (KTH) in 2012. Her research is focused on data-efficient learning from multisensory data for robotics applications. She received the Best Paper Award at IEEE International Conference on Robotics and Automation for Humanitarian Applications (RAHA) in 2016 and the Best Manipulation Paper Award at IEEE International Conference on Robotics and Automation (ICRA) in 2013, and was IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) CoTeSys Cognitive Robotics Best Paper Award Finalist in 2013. She serves as a reviewer for robotics conferences and journals.</div></div> <div><br /></div> <div><div><h3 class="chalmersElement-H3">About CHAIR Spotlight on Research</h3> <div>Chalmers AI Research Centre, CHAIR Spotlight on Research is a series of AI short talks hosting researchers from Chalmers. The seminars are targeted towards experts from the Chair Consortium core partners as well as other Chalmers researchers.</div> <div><br /></div> <div>Our aim is to increase awareness of AI at Chalmers between Chalmers researchers and AI experts in industry. In the seminars, speakers present an overview of their current research and thoughts for new research, ideas, challenges – anything they believe to be of interest for other researchers. The seminar is taking place online and is scheduled to contain 30 minutes of presentation and 15 minutes of discussion. </div> <div><div><br />The first series of CHAIR Spotlight Research talks have the theme “New Chalmers researchers on the spot!”, meaning that researchers that came to Chalmers in the last three years are giving these talks. ​​​</div> <div><br /></div></div> <div> <span style="background-color:initial">The seminars are open to all and are free of charge. CHAIR Spotlight Research talks are taking place on Fridays 13:00-13:45.​​</span></div></div> ​<br /></div> <div> ​</div> ​ Ethics online: Ethics guidelines as a tool for AI governance - EU and its member states<p>Online, Zoom</p><p>​AI Ethics seminar with lawyer and Professor Stefan Larsson from Lund University.</p>​​1 Dec 2020<br />13.15 - 14.15 (Swedish time)<br />Online<div><br /></div> <div><h3 class="chalmersElement-H3">Title: Ethics guidelines as a tool for AI governance - EU and its member states</h3> <div><br /></div> <div> </div> <div><strong>Abstract:</strong> Many companies, NGOs and governmental bodies have recently formulated ethical principles as a way to govern development and applications of artificial intelligence (AI). This includes the EU, particularly indicated by the Ethics Guidelines for Trustworthy AI published by the High-Level Expert Group on AI in april 2019. This presentation offers (a) findings from a recent paper on the overall topic of ethics guidelines as a tool for AI governance <span style="background-color:initial">[</span><span style="background-color:initial">1</span><span style="background-color:initial">], and (b) </span><span style="background-color:initial">a recent anthology on how 9 different member states' strategies relate to the EU-level notions of human-centric and trustworthy AI [2]. </span></div> <div> </div> <div><span style="background-color:initial"><br /></span></div> <div> </div> <div><span style="background-color:initial"> [1] Larsson, S. (2020). On the Governance of Artificial Intelligence through Ethics Guidelines. Asian Journal of Law and Society, 1-15. doi:10.1017/als.2020.19 </span></div> <div> </div> <div><span style="background-color:initial"> [2] Larsson, Ingram Bogusz &amp; Andersson Schwarz, eds. (2020) Human Centric AI in the EU: Towards a trustworthy development of artificial intelligence in the European Member States, Brussels/Stockholm: ELF/Fores. </span></div> <div><span style="background-color:initial"><br /></span></div> <h3 class="chalmersElement-H3"><span>Registration will open in November.</span></h3> <div> </div> <div><span style="background-color:initial"><br /></span></div> <div> </div> <div><span style="background-color:initial"> <strong><img src="/SiteCollectionImages/Centrum/CHAIR/events/stefan_larsson_180px.jpg" class="chalmersPosition-FloatRight" alt="" style="margin:5px 10px" />Ab</strong></span><span style="background-color:initial"><strong>out the speaker</strong></span></div> <div> </div> <div><span style="background-color:initial"><strong></strong>Stefan Larsson is a senior lecturer and Associate Professor in Technology and Social Change at Lund University, Sweden. He is a lawyer (LLM) and socio-legal researcher who holds a PhD in Sociology of Law as well as a PhD in Spatial Planning. His multidisciplinary research focuses on issues of trust and transparency on digital, data-driven markets, and the socio-legal impact of autonomous and AI-driven technologies. </span></div> <div> </div> <div><span style="background-color:initial"><br /></span></div> <div> </div> <div><span style="background-color:initial"><br /></span></div> <div> </div> <div><span style="background-color:initial"><br /></span></div></div> ​ Ethics online: A conversation on AI governance and AI risk<p>Online, Zoom</p><p>​AI Ethics seminar with Seán Ó hÉigeartaigh and Olle Häggström.</p>​​15 Dec, 2020<div>13.15 - 14.15 (Swedish time)<br />Online</div> <div><br /></div> <h3 class="chalmersElement-H3">Title: A conversation on AI governance and AI risk</h3> <div><br /></div> <div><strong>About the speakers</strong><br /></div> <div><br /></div> Seán Ó hÉigeartaigh serves as co-director of the Centre for the Study of Existential Risk at University of Cambridge. His research focuses on technological trajectories and impacts of artificial intelligence (AI) and other emerging technologies. <div><br /></div> <div> Olle Häggström is a professor of mathematical statistics at Chalmers, where he also serves as chairman of CHAIR's AI ethics committee. </div> <div><br /></div> <div> Seán and Olle will discuss a range of topics in AI ethics, AI governance and AI risk. ​</div> <div><br /></div> <div><span class="text-normal"><h2>About AI ETHICS at Chalmers</h2></span>A  series of seminars highlighting ethical perspectives of artificial intelligence. The series will feature invited speakers and Chalmers researchers with the aim of cultivating an informed discussion on ethical issues. The seminars are organised by the <a href="" style="background-color:rgb(255, 255, 255)">AI Ethics Committee</a> , within Chalmers AI Research Centre (CHAIR). <br /></div> ​​