CHAIR Spotlight on Research
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CHAIR Spotlight on Research

Chalmers AI Research Center, CHAIR Spotlight on Research is a series of short talks hosting researchers from Chalmers and other organisations working on AI/machine learning/data science and their applications to different domains. The seminars are targeted towards everyone who has interest in AI/machine learning/data science, particularly from the Chair Consortium core partners and Chalmers.

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. 
 
The seminars are open t​o all and are free of charge. CHAIR Spotlight Research talks are taking place on Fridays 14.00-14.45.

Upcoming seminars ​




Previous seminars

Aleksej Zelezniak

Aleksej Zelezniak is an ​​Associate Professor in the divison for Systems and Synthetic Biology in the Department of Biology and Biological Engineering.
 

Raquel Mini

Raquel Mini and Per Skarin

Date: 25 March 2022, at 14.00​​​
​​​Changing the Industry Landscape using 5G and AI
Raquel Mini is a researcher at Ericsson working in the Cloud Systems and Platforms area. She got her BSc, MSc, and PhD in Computer Science from Federal University of Minas Gerais (UFMG), Brazil. Before joining Ericsson in 2021, Raquel worked for more than 20 years as a Professor of Computer Science in Brazil. Her research addresses the area of sensor networks, IoT, ubiquitous computing, and cloud computing. 
 
Per Skarin is a researcher at Ericsson working in the Cloud Systems and Platforms area. He got his MSc in Computer Science and his PhD in Automatic Control from Lund University. Per went into research in 2015 where his latest endeavor is a thesis on Control Over the Cloud within the Wallenberg AI, Autonomous Systems and Software Program. He has also recently done work within the WASP strategic research arenas WARA Public Safety and WARA Collaborative Autonomous Transports. His focus is on the use of cloud technology in the automation of critical cyber-physical systems. Before going into research, Per has over a decade of experience from development organizations in and outside of Ericsson.

Adel Daoud

​​​Observatory of Poverty: combining satellite images and deep-learning algorithms to estimate health and living conditions in Africa
Adel Daoud is an Associate Professor at Institute for Analytical Sociology, Linköping University, and Affiliated Associate Professor in Data Science and Artificial Intelligence for the Social Sciences, Department of Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden. Previously he held positions at Harvard University, University of Cambridge, Max Planck Institute for the Studies of Societies, and the Alan Turing Institute. His researh has both a social-scientific and methodologically orientation. For the social sciences, he researchers the effect of international development interventions (e.g., anti-poverty policies) on global poverty, but also the impact of sudden shocks (e.g., economic, political, and natural disasters). Daoud implements novel methodologies in machine learning and causal inference to analyze the causes and consequences of poverty. He has published in journals such as PNAS, Science Advances, World Development, International J of Epidemiology, and Ecological Economics, and machine-learning conferences as AAAI.
Date: 24 February 2022, at 14.00​​​

Tommy Svensson

Challenges and opportunities in 6G mobile communications
Tommy Svensson is Full Professor in Communication Systems at Chalmers University of Technology in Gothenburg, Sweden, where he is leading the Wireless Systems research on air interface and wireless backhaul networking technologies for future wireless systems. Tommy's research interests include design and analysis of physical layer algorithms, multiple access, resource allocation, cooperative systems, moving networks, and satellite networks. He has co-authored 5 books, 100 journal papers, 132 conference papers and 60 public EU projects deliverables.
Date: 26 November 2021, at 13.00​​​

Palle Dahlstedt

Musicking with Algorithms: Thoughts on Artificial Intelligence, Creativity, and Agency​
Palle Dahlstedt is  an artist, composer and researcher from Sweden. He has studied piano, composition and electronic music, and has a PhD in evolutionary computation for artistic creativity from Chalmers (2004). Dahlstedt studies the deep entanglement of art and advanced technology, particularly in relation to creative and aesthetic implications.
Date: 12 November 2021, at 13.00​​​

Xiaobo Qu

AI and Transportation Engineering: Case Studies, trends and some thoughts​ Xiaobo Qu  is a Full Professor with a Chair in the Department of Architecture and Civil Engineering, Chalmers University of Technology in Sweden. His research is focused on improving large, complex and interrelated urban mobility systems by integrating with emerging technologies. More specifically, his research has been applied to the improvement of emergency services, and operations of electric vehicles and connected automated vehicles.
Date: 29 October 2021, at 13.00​​​

Victor Botev

Processing scientific content with Artificial Intelligence​ Victor Botev is the CTO and Co-Founder of Iris.ai. As the head of both the research and development team at Iris.ai, Victor has had to put his unique experience from a combination of AI research, software development, and technology leadership skills to the ultimate test in building and operating an international startup with a very ambitious vision and goal.

Date: 15 October 2021, at 13.00​​​

Esben Bjerrum 

Creative computer algorithms in drug discovery suggests what to make, and how to make it.​ Esben Bjerrum completed his PhD in COmputational Chemistry at Copenhagen University in 2008. He has then worked both in academia as a post.doc, in industry as an IT specialist as well as an self-employed IT consultant. In 2017 his independent research resulted in several contributions to the chemistry deep learning renaissance. He joined Astrazeneca in 2018 where he currently works with development of de novi design algorithms and deep learning assisted retrosynthetic planning. 

Date: 1 October 2021, at 13.00​​

Richard Johansson

Interpreting and Grounding Pre-trained Representations for Natural Language Processing Richard Johansson a senior lecturer at the Division of Data Science and Artificial Intelligence at the Department of Computer Science and Engineering, Chalmers Technical University and University of Gothenburg. He earned his PhD in 2008 at Lund University and then spent some years as a postdoctoral researcher at the University of Trento, Italy, before returning to Sweden in 2011. His research interests are at the intersection of natural language processing and machine learning (ML), and most of his research focuses on the interplay between structured knowledge and ML-based language processing.

Date: 17 September 2021, at 13.00​​

Johanna Björklund

Reinventing Hollywood: Automated and Distributed​ Johanna Björklund is an Associate Professor at the Department of Computing Science at Umeå University. Her research is on semantic, or human-like, analysis of multimodal data, incorporating, e.g., images, audio, video, and text. She is also a co-founder of the media tech companies Codemill, Adlede, and Accurate Player, which deliver products and services for the media supply chain and count ITV, BBC, and ProSieben among their customers. 

Date: 3 September 2021, at 13.00​

Anders Broo

Applied machine learning to support chemistry and formulation at AstraZeneca Anders Broo has a PhD in theoretical and physical chemistry from University of Gothenburg, Sweden (1991). After post-doc’s in Uppsala and Florida he returned to Sweden for an assistant and associate professor position at Chalmers University of Technology, Gothenburg, Sweden. Anders has published 48 peer reviewed articles and is co-inventor on 3 patents.  

Date: 18 June 2021, at 13.00

Irene Yu-Hua Gu

Irene Yu-Hua Gu received Ph.D. degree in electrical engineering from Eindhoven University of Technology (The Netherlands), in 1992. From 1992 to 1996, she was Research Fellow at Philips Research Institute IPO, (The Netherlands), post dr. at Staffordshire University (U.K), and Lecturer at the University of Birmingham (U.K).
Since 1996, she has been with the Department of Electrical Engineering (former name: Department of Signals and Systems), Chalmers University of Technology, Sweden, where she became a professor (
bitr. professor) in 2004, and a full professor since 2008. 
Date: 4 June 2021, at 13.00

Yasemin Bekiroglu

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.
Date: 20 November 2020, at 13.00


CHAIR Spotlight on Research seminars 2020

Ashkan Panahi

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).

Date: 6th November 2020, at 13.00


Simon Olsson

Simon Olsson is Assistant Professor for Applied Artificial Intelligence at the Data Science and AI section of Computer Science and Engineering, Chalmers.
In 2013 the University of Copenhagen awarded Simon Olsson a Ph.D. in Bioinformatics for his work in probabilistic modeling of protein ensembles from averaged data under Thomas Hamelryck. Following his Ph.D., he was award several postdoctoral fellowships to spend time, first in Switzerland at the ETH Zürich and IRB Bellinzona, and later in Germany at the Freie Universität Berlin. Simons research focuses on the interface between machine learning and experimental, theoretical, and computational aspects of the natural sciences.
Date: 9th October 2020, at 13.00

Morteza Haghir Chehreghani

Adaptive Information Acquisition and Sequential Decision Making in AI​​ Morteza Haghir Chehreghani is Associate Professor of AI and Machine Learning at Chalmers University of Technology, Department of Computer Science and Engineering, Data Science and AI division. He holds a Ph.D. in Computer Science (AI/Machine Learning group) from ETH Zurich (2014). After the Ph.D., he joined Xerox Research as a Staff Research Scientist I and then Staff Research Scientist II. After about four years and in 2018, he joined Chalmers University of Technology.
Date: 25th September 2020, at 13.00


Karinne Ramirez-Amaro

Dr. Karinne Ramirez Amaro is an Assistant professor at Chalmers University of Technology since September 2019. Previously, she was a post-doctoral researcher at the Chair for Cognitive Systems (ICS) at the Technical University of Munich (TUM). She completed her Ph.D. (summa cum laude) at the Department of Electrical and Computer Engineering at the Technical University of Munich (TUM), Germany in 2015. 
Date: 28th August 2020, at 13.00

Marija Furdek 

Dr. Furdek is an assistant professor at the Department of Electrical Engineering at Chalmers. She received her Docent degree in Optical Networking from KTH Royal Institute of Technology in 2017. Her research focuses on the design of high-performance networks supporting next generation services, encompassing issues related to the optical network architecture and control.
Date: 21st August 2020, at 13.00

Ross King

Ross D. King obtained a B.Sc. Hons. in Microbiology from the University of Aberdeen, an M.Sc. in computer science from the University of Newcastle upon Tyne, and a Ph.D. in Machine Learning from the Turing Institute. He is one of the most experienced machine learning researchers in Europe. His main research interest is the interface between computer science and science.
Date: 12th June 2020, at 13.00
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Page manager Published: Wed 27 Apr 2022.