The AAISI has been founded by well-known AI scientists and key decision-makers from industries in the frame of their collaborations in European funded research projects. The AAISI is the first choice of scientific and industrial communities to exploit the scientific AI to practical results in the industry. This has been mainly focused on a deep understanding of industry 4.0 and next-generation AI methods in AAISI activities and events.
AAISI
Association for AI in Science and Industry
Tara Javidi, Professor at University of California, San Diego
Black-box Optimization in Theory and in Practice
Title: Black-box Optimization in Theory and in Practice. Date & Time: 27 Apr. 2021, 16:00 CEST (10:00 EST).
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Schahram DustdarProfessor and Director, TU Vienna, Austria
Schahram Dustdar is a Professor of Computer Science (Informatics) with a focus on Internet Technologies heading the Distributed Systems Group at the Vienna University of Technology (TU Vienna). From 2004-2010 he was an Honorary Professor of Information Systems at the Department of
Computing Science at the University of Groningen (RuG), The Netherlands.
He is a member of the Academia Europaea: The Academy of Europe,
Informatics Section (since 2013), and an IEEE Senior Member (2009). He is the recipient of the ACM Distinguished Scientist award (2009), the IBM Faculty Award (2012), the IEEE TCSVC Outstanding Leadership Award
(June 2018), the IEEE TCSC Award for Excellence in Scalable Computing (June 2019). He is an Associate Editor of IEEE Transactions on Services
Computing, IEEE Transactions on Cloud Computing, ACM Computing Surveys, ACM Transactions on the Web, and ACM Transactions on Internet Technology and on the editorial board of IEEE Internet Computing and IEEE Computer.
He is Co-Editor-in-Chief of the ACM Transactions on Internet of Things and Editor-in-Chief of Computing (an SCI-ranked journal of Springer).
Schahram DustdarProfessor and Director, TU Vienna, Austria
Schahram Dustdar is a Professor of Computer Science (Informatics) with a focus on Internet Technologies heading the Distributed Systems Group at the Vienna University of Technology (TU Vienna). From 2004-2010 he was an Honorary Professor of Information Systems at the Department of
Computing Science at the University of Groningen (RuG), The Netherlands.
He is a member of the Academia Europaea: The Academy of Europe,
Informatics Section (since 2013), and an IEEE Senior Member (2009). He is the recipient of the ACM Distinguished Scientist award (2009), the IBM Faculty Award (2012), the IEEE TCSVC Outstanding Leadership Award
(June 2018), the IEEE TCSC Award for Excellence in Scalable Computing (June 2019). He is an Associate Editor of IEEE Transactions on Services
Computing, IEEE Transactions on Cloud Computing, ACM Computing Surveys, ACM Transactions on the Web, and ACM Transactions on Internet Technology and on the editorial board of IEEE Internet Computing and IEEE Computer.
He is Co-Editor-in-Chief of the ACM Transactions on Internet of Things and Editor-in-Chief of Computing (an SCI-ranked journal of Springer).
Sören AuerProfessor and Director, Leibnitz University Hannover and TIB Technical Library, Germany
Following stations at the universities of Dresden, Ekaterinburg, Leipzig, Pennsylvania, Bonn and the Fraunhofer Society, Prof. Auer was appointed Professor of Data Science and Digital Libraries at Leibniz Universität Hannover and Director of the TIB in 2017. Prof. Auer has made important contributions to semantic technologies, knowledge engineering and information systems. He is the author (resp. co-author) of over 100 peer-reviewed scientific publications. He has received several awards, including an ERC Consolidator Grant from the European Research Council, a SWSA ten-year award, the ESWC 7-year Best Paper Award, and the OpenCourseware Innovation Award. He has led several large collaborative research projects, such as the EU H2020 flagship project BigDataEurope. He is co-founder of high potential research and community projects such as the Wikipedia semantification project DBpedia, the OpenCourseWare authoring platform SlideWiki.org and the innovative technology start-up eccenca.com. Prof. Auer was founding director of the Big Data Value Association, led the semantic data representation in the Industrial/International Data Space, is an expert for industry, European Commission, W3C and member of the advisory board of the Open Knowledge Foundation.
Sören AuerProfessor and Director, Leibnitz University Hannover and TIB Technical Library, Germany
Following stations at the universities of Dresden, Ekaterinburg, Leipzig, Pennsylvania, Bonn and the Fraunhofer Society, Prof. Auer was appointed Professor of Data Science and Digital Libraries at Leibniz Universität Hannover and Director of the TIB in 2017. Prof. Auer has made important contributions to semantic technologies, knowledge engineering and information systems. He is the author (resp. co-author) of over 100 peer-reviewed scientific publications. He has received several awards, including an ERC Consolidator Grant from the European Research Council, a SWSA ten-year award, the ESWC 7-year Best Paper Award, and the OpenCourseware Innovation Award. He has led several large collaborative research projects, such as the EU H2020 flagship project BigDataEurope. He is co-founder of high potential research and community projects such as the Wikipedia semantification project DBpedia, the OpenCourseWare authoring platform SlideWiki.org and the innovative technology start-up eccenca.com. Prof. Auer was founding director of the Big Data Value Association, led the semantic data representation in the Industrial/International Data Space, is an expert for industry, European Commission, W3C and member of the advisory board of the Open Knowledge Foundation.
Mohammad Shokoohi YektaSenior Data Scientist, Microsoft
Mohammad is currently a Senior Applied Scientist at Microsoft, and Instructor at Stanford University. He is a former Data Scientist at Apple and previously worked for Samsung, Bosch, General Electric and UCLA Research Labs. He received a PhD in Computer Science from the University of California, Riverside and B.Sc. from University of Tehran. Mohammad is the author of the book, ‘Applications of Mining Massive Time Series Data’. He has also been a keynote speaker at more than 45 Data Summits/Conferences around the globe.
Mohammad Shokoohi YektaSenior Data Scientist, Microsoft
Mohammad is currently a Senior Applied Scientist at Microsoft, and Instructor at Stanford University. He is a former Data Scientist at Apple and previously worked for Samsung, Bosch, General Electric and UCLA Research Labs. He received a PhD in Computer Science from the University of California, Riverside and B.Sc. from University of Tehran. Mohammad is the author of the book, ‘Applications of Mining Massive Time Series Data’. He has also been a keynote speaker at more than 45 Data Summits/Conferences around the globe.
Rachel CummingsAssistant Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech.
Dr. Rachel Cummings is an Assistant Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. Her research interests lie primarily in data privacy, with connections to machine learning, algorithmic economics, optimization, statistics, and information theory. Her work has focused on problems such as strategic aspects of data generation, incentivizing truthful reporting of data, privacy-preserving algorithm design, impacts of privacy policy, and human decision-making.
Dr. Cummings received her Ph.D. in Computing and Mathematical Sciences from the California Institute of Technology, her M.S. in Computer Science from Northwestern University, and her B.A. in Mathematics and Economics from the University of Southern California.
She is the recipient of a Google Research Fellowship, a Simons-Berkeley Research Fellowship in Data Privacy, the ACM SIGecom Doctoral Dissertation Honorable Mention, the Amori Doctoral Prize in Computing and Mathematical Sciences, a Caltech Leadership Award, a Simons Award for Graduate Students in Theoretical Computer Science, and the Best Paper Award at the 2014 International Symposium on Distributed Computing. Dr. Cummings also serves on the ACM U.S. Public Policy Council's Privacy Committee.
Rachel CummingsAssistant Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech.
Dr. Rachel Cummings is an Assistant Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. Her research interests lie primarily in data privacy, with connections to machine learning, algorithmic economics, optimization, statistics, and information theory. Her work has focused on problems such as strategic aspects of data generation, incentivizing truthful reporting of data, privacy-preserving algorithm design, impacts of privacy policy, and human decision-making.
Dr. Cummings received her Ph.D. in Computing and Mathematical Sciences from the California Institute of Technology, her M.S. in Computer Science from Northwestern University, and her B.A. in Mathematics and Economics from the University of Southern California.
She is the recipient of a Google Research Fellowship, a Simons-Berkeley Research Fellowship in Data Privacy, the ACM SIGecom Doctoral Dissertation Honorable Mention, the Amori Doctoral Prize in Computing and Mathematical Sciences, a Caltech Leadership Award, a Simons Award for Graduate Students in Theoretical Computer Science, and the Best Paper Award at the 2014 International Symposium on Distributed Computing. Dr. Cummings also serves on the ACM U.S. Public Policy Council's Privacy Committee.
Eirini NtoutsiProfessor, Leibnitz University Hannover, Germany
Eirini Ntoutsi is since March 2021 full Professor of Artificial Intelligence at the Free University (FU) Berlin. Prior to joining FU, she was an Associate Professor of Intelligent Systems at the Leibniz University of Hanover (LUH), Germany. Prior to that, she was a post-doctoral researcher at the Ludwig-Maximilians-University (LMU) in Munich, Germany in the group of Prof. H.-P. Kriegel. She joined the group as a post-doctoral fellow of the Alexander von Humboldt Foundation. She holds a PhD in Data Mining from the University of Piraeus, Greece and a master and diploma in Computer Engineering and Informatics from the University of Patras, Greece. Her research interests lie in the fields of Artificial Intelligence (AI) and Machine Learning (ML) and can be summarized as developing methods for i) learning over complex data and data streams, covering aspects such as adaptive learning, change detection and stability as well as ii) responsible AI, covering aspects such as fairness-aware learning, data quality and proper evaluation of AI/ML methods. Her research is supported by prestigious funding bodies, including the European Commission, the German Research Foundation (DFG), the Volkswagen Foundation etc. She serves on several boards and organizing committees including the ACM Intl Conference on Information and Knowledge Management (CIKM 2020) as demo and posters co-chair, the IEEE International Conference on Data Mining (ICDM 2017) as publicity co-chair and the German Machine Learning and Data Mining community meeting (KDML 2019) as program co-chair. She serves in the technical committee of many international conferences and she is a frequently reviewer for a number of international technical journals.
Eirini NtoutsiProfessor, Leibnitz University Hannover, Germany
Eirini Ntoutsi is since March 2021 full Professor of Artificial Intelligence at the Free University (FU) Berlin. Prior to joining FU, she was an Associate Professor of Intelligent Systems at the Leibniz University of Hanover (LUH), Germany. Prior to that, she was a post-doctoral researcher at the Ludwig-Maximilians-University (LMU) in Munich, Germany in the group of Prof. H.-P. Kriegel. She joined the group as a post-doctoral fellow of the Alexander von Humboldt Foundation. She holds a PhD in Data Mining from the University of Piraeus, Greece and a master and diploma in Computer Engineering and Informatics from the University of Patras, Greece. Her research interests lie in the fields of Artificial Intelligence (AI) and Machine Learning (ML) and can be summarized as developing methods for i) learning over complex data and data streams, covering aspects such as adaptive learning, change detection and stability as well as ii) responsible AI, covering aspects such as fairness-aware learning, data quality and proper evaluation of AI/ML methods. Her research is supported by prestigious funding bodies, including the European Commission, the German Research Foundation (DFG), the Volkswagen Foundation etc. She serves on several boards and organizing committees including the ACM Intl Conference on Information and Knowledge Management (CIKM 2020) as demo and posters co-chair, the IEEE International Conference on Data Mining (ICDM 2017) as publicity co-chair and the German Machine Learning and Data Mining community meeting (KDML 2019) as program co-chair. She serves in the technical committee of many international conferences and she is a frequently reviewer for a number of international technical journals.
Mahdi Tavakoli Professor in the Department of Electrical and Computer Engineering, University of Alberta
Mahdi Tavakoli is a Professor in the Department of Electrical and Computer Engineering, University of Alberta, Canada. He received his BSc and MSc degrees in Electrical Engineering from Ferdowsi University and K.N. Toosi University, Iran, in 1996 and 1999, respectively. He received his PhD degree in Electrical and Computer Engineering from the University of Western Ontario, Canada, in 2005. In 2006, he was a post-doctoral researcher at Canadian Surgical Technologies and Advanced Robotics (CSTAR), Canada. In 2007-2008, he was an NSERC Post-Doctoral Fellow at Harvard University, USA. Dr. Tavakoli’s research interests broadly involve the areas of robotics and systems control. Specifically, his research focuses on haptics and teleoperation control, medical robotics, and image-guided surgery. Dr. Tavakoli is the lead author of Haptics for Teleoperated Surgical Robotic Systems (World Scientific, 2008). He is a Senior Member of IEEE and an Associate Editor for IEEE/ASME Transactions on Mechatronics, Journal of Medical Robotics Research, IET Control Theory & Applications, and Mechatronics. Currently, Dr. Tavakoli acts as Scientific Co-Director for the University of Alberta’s SMART Network, Co-Lead for Healthy Communities Project of Autonomous Systems Initiative supported by the Government of Alberta, and Co-Chair for the IEEE RAS Technical Committee for Telerobotics.
Mahdi Tavakoli Professor in the Department of Electrical and Computer Engineering, University of Alberta
Mahdi Tavakoli is a Professor in the Department of Electrical and Computer Engineering, University of Alberta, Canada. He received his BSc and MSc degrees in Electrical Engineering from Ferdowsi University and K.N. Toosi University, Iran, in 1996 and 1999, respectively. He received his PhD degree in Electrical and Computer Engineering from the University of Western Ontario, Canada, in 2005. In 2006, he was a post-doctoral researcher at Canadian Surgical Technologies and Advanced Robotics (CSTAR), Canada. In 2007-2008, he was an NSERC Post-Doctoral Fellow at Harvard University, USA. Dr. Tavakoli’s research interests broadly involve the areas of robotics and systems control. Specifically, his research focuses on haptics and teleoperation control, medical robotics, and image-guided surgery. Dr. Tavakoli is the lead author of Haptics for Teleoperated Surgical Robotic Systems (World Scientific, 2008). He is a Senior Member of IEEE and an Associate Editor for IEEE/ASME Transactions on Mechatronics, Journal of Medical Robotics Research, IET Control Theory & Applications, and Mechatronics. Currently, Dr. Tavakoli acts as Scientific Co-Director for the University of Alberta’s SMART Network, Co-Lead for Healthy Communities Project of Autonomous Systems Initiative supported by the Government of Alberta, and Co-Chair for the IEEE RAS Technical Committee for Telerobotics.
Vincenzo PiuriProffesor at Universita’ degli Studi di Milano
Vincenzo Piuri has received his Ph.D. in computer engineering at Polytechnic of Milan, Italy (1989). He is a Full Professor in computer engineering at the University of Milan, Italy (since 2000). He has been an Associate Professor at Polytechnic of Milan, Italy and Visiting Professor at the University of Texas at Austin, USA, and visiting researcher at George Mason University, USA.His main research interests are artificial intelligence, computational intelligence, intelligent systems, machine learning, pattern analysis and recognition, signal and image processing, biometrics, intelligent measurement systems, industrial applications, digital processing architectures, fault tolerance, cloud computing infrastructures, and internet-of-things. Original results have been published in 400+ papers in international journals, proceedings of international conferences, books, and book chapters. He is a Fellow of the IEEE, Distinguished Scientist of ACM, and Senior Member of INNS. He is President of the IEEE Systems Council (2020-21) and IEEE Region 8 Director-elect (2021-22) and has been IEEE Vice President for Technical Activities (2015), IEEE Director, President of the IEEE Computational Intelligence Society, Vice President for Education of the IEEE Biometrics Council, Vice President for Publications of the IEEE Instrumentation and Measurement Society and the IEEE Systems Council, and Vice President for Membership of the IEEE Computational Intelligence Society. He has been Editor-in-Chief of the IEEE Systems Journal (2013-19). He is Associate Editor of the IEEE Transactions on Cloud Computing and has been Associate Editor of the IEEE Transactions on Computers, the IEEE Transactions on Neural Networks, the IEEE Transactions on Instrumentation and Measurement, and IEEE Access. He received the IEEE Instrumentation and Measurement Society Technical Award (2002) and the IEEE TAB Hall of Honor (2019). He is an Honorary Professor at Obuda University, Hungary; Guangdong University of Petrochemical Technology, China; Northeastern University, China; Muroran Institute of Technology, Japan; Amity University, India; and Galgotias University, India.
Vincenzo PiuriProffesor at Universita’ degli Studi di Milano
Vincenzo Piuri has received his Ph.D. in computer engineering at Polytechnic of Milan, Italy (1989). He is a Full Professor in computer engineering at the University of Milan, Italy (since 2000). He has been an Associate Professor at Polytechnic of Milan, Italy and Visiting Professor at the University of Texas at Austin, USA, and visiting researcher at George Mason University, USA.His main research interests are artificial intelligence, computational intelligence, intelligent systems, machine learning, pattern analysis and recognition, signal and image processing, biometrics, intelligent measurement systems, industrial applications, digital processing architectures, fault tolerance, cloud computing infrastructures, and internet-of-things. Original results have been published in 400+ papers in international journals, proceedings of international conferences, books, and book chapters. He is a Fellow of the IEEE, Distinguished Scientist of ACM, and Senior Member of INNS. He is President of the IEEE Systems Council (2020-21) and IEEE Region 8 Director-elect (2021-22) and has been IEEE Vice President for Technical Activities (2015), IEEE Director, President of the IEEE Computational Intelligence Society, Vice President for Education of the IEEE Biometrics Council, Vice President for Publications of the IEEE Instrumentation and Measurement Society and the IEEE Systems Council, and Vice President for Membership of the IEEE Computational Intelligence Society. He has been Editor-in-Chief of the IEEE Systems Journal (2013-19). He is Associate Editor of the IEEE Transactions on Cloud Computing and has been Associate Editor of the IEEE Transactions on Computers, the IEEE Transactions on Neural Networks, the IEEE Transactions on Instrumentation and Measurement, and IEEE Access. He received the IEEE Instrumentation and Measurement Society Technical Award (2002) and the IEEE TAB Hall of Honor (2019). He is an Honorary Professor at Obuda University, Hungary; Guangdong University of Petrochemical Technology, China; Northeastern University, China; Muroran Institute of Technology, Japan; Amity University, India; and Galgotias University, India.
Rolf FindeisenProfessor at University Magdeburg
Prof Rolf Findeisen received an MSc degree from the University of Wisconsin–Madison, Madison, WI, USA, a Diploma degree from the University in Stuttgart in Engineering Cybernetics, and a Dr. degree from the University of Stuttgart, Stuttgart, Germany, in 2005. He was a Research Assistant with the Automatic Control Laboratory, ETH Zurich, Switzerland, and a Researcher with the Institute for Systems Theory and Automatic Control, University of Stuttgart. Rolf heads the Systems Theory and Automatic Control Laboratory at the Otto-von-Guericke University Magdeburg, Germany. He had research stays and guest professorships at the Massachusetts Institute of Technology Cambridge, EPF Lausanne, the University of California at Santa Barbara, Imperial College London, NTNU Trondheim, Norway. Rolf's current research activities focus on the control and monitoring of autonomous and cyber-physical systems, predictive control, and the fusion of machine learning and control with guarantees. Fields of applications span from mechatronics, aerospace systems to chemical and biotechnological processes, robotics, energy systems, and systems medicine.
Rolf FindeisenProfessor at University Magdeburg
Prof Rolf Findeisen received an MSc degree from the University of Wisconsin–Madison, Madison, WI, USA, a Diploma degree from the University in Stuttgart in Engineering Cybernetics, and a Dr. degree from the University of Stuttgart, Stuttgart, Germany, in 2005. He was a Research Assistant with the Automatic Control Laboratory, ETH Zurich, Switzerland, and a Researcher with the Institute for Systems Theory and Automatic Control, University of Stuttgart. Rolf heads the Systems Theory and Automatic Control Laboratory at the Otto-von-Guericke University Magdeburg, Germany. He had research stays and guest professorships at the Massachusetts Institute of Technology Cambridge, EPF Lausanne, the University of California at Santa Barbara, Imperial College London, NTNU Trondheim, Norway. Rolf's current research activities focus on the control and monitoring of autonomous and cyber-physical systems, predictive control, and the fusion of machine learning and control with guarantees. Fields of applications span from mechatronics, aerospace systems to chemical and biotechnological processes, robotics, energy systems, and systems medicine.
Ute SchmidProfessor of Applied Computer Science/Cognitive Systems, University of Bamberg
Ute Schmid is professor of Applied Computer Science/Cognitive Systems at the University of Bamberg. She has university diplomas in computer science as well as psychology, and a doctor degree and a habilitation in computer science from TU Berlin. She is member of the board of directors of the Bavarian Institute of Digital Transformation (bidt) and member of the Bavarian AI Council. Furthermore, Ute Schmid is head of the Fraunhofer IIS project group Explainable AI. Research interests of Ute Schmid are in the domain of comprehensible machine learning, explainable AI, and high-level learning on relational data, especially inductive programming. Research topics are generation of visual, verbal and example-based explanations, cognitive tutor systems, and cooperative and interactive learning. Ute Schmid dedicates a significant amount of her time to measures supporting women in computer science and in 2018 won the Minerva Gender Equality Award of Informatics Europe for her university. Since many years she offers and organises computer science workshops, including AI for children and is speaker of the working group AI in Schools of the SIG AI of the German Computer Science Society (GI e.V.).
The foto copyright is J. Schabel.
Ute SchmidProfessor of Applied Computer Science/Cognitive Systems, University of Bamberg
Ute Schmid is professor of Applied Computer Science/Cognitive Systems at the University of Bamberg. She has university diplomas in computer science as well as psychology, and a doctor degree and a habilitation in computer science from TU Berlin. She is member of the board of directors of the Bavarian Institute of Digital Transformation (bidt) and member of the Bavarian AI Council. Furthermore, Ute Schmid is head of the Fraunhofer IIS project group Explainable AI. Research interests of Ute Schmid are in the domain of comprehensible machine learning, explainable AI, and high-level learning on relational data, especially inductive programming. Research topics are generation of visual, verbal and example-based explanations, cognitive tutor systems, and cooperative and interactive learning. Ute Schmid dedicates a significant amount of her time to measures supporting women in computer science and in 2018 won the Minerva Gender Equality Award of Informatics Europe for her university. Since many years she offers and organises computer science workshops, including AI for children and is speaker of the working group AI in Schools of the SIG AI of the German Computer Science Society (GI e.V.).
The foto copyright is J. Schabel.
Tara Javidi Professor at University of California, San Diego
Dr. Javidi is a professor of electrical and computer engineering at University of California, San Diego. She received her MS and PhD degrees in Electrical Engineering and Computer Science as well as her MS in Applied Mathematics from the University of Michigan, Ann Arbor. Before joining UCSD, she was on the faculty of Electrical Engineering Department at the University of Washington, Seattle; In 2013-2014, she spent her sabbatical at Stanford University as a visiting faculty. Her area of research is at the intersection of stochastic control, information theory, and data science with notable contributions to the theory of information acquisition and active learning. At the University of California, San Diego, Tara is a founding co-director of the Center for Machine-Integrated Computing and Security, the principal investigator of Detect Drone Project as well as a faculty member of the member of the Centers of Information Theory and Applications (ITA), Halıcıoğlu Data Science Institute, Wireless Communications (CWC), Contextual Robotics Institute (CRI) and Networked Systems (CNS).
Tara Javidi Professor at University of California, San Diego
Dr. Javidi is a professor of electrical and computer engineering at University of California, San Diego. She received her MS and PhD degrees in Electrical Engineering and Computer Science as well as her MS in Applied Mathematics from the University of Michigan, Ann Arbor. Before joining UCSD, she was on the faculty of Electrical Engineering Department at the University of Washington, Seattle; In 2013-2014, she spent her sabbatical at Stanford University as a visiting faculty. Her area of research is at the intersection of stochastic control, information theory, and data science with notable contributions to the theory of information acquisition and active learning. At the University of California, San Diego, Tara is a founding co-director of the Center for Machine-Integrated Computing and Security, the principal investigator of Detect Drone Project as well as a faculty member of the member of the Centers of Information Theory and Applications (ITA), Halıcıoğlu Data Science Institute, Wireless Communications (CWC), Contextual Robotics Institute (CRI) and Networked Systems (CNS).
Gustau Camps-VallsProffessor at Universitat de València
Gustau Camps-Valls (IEEE Fellow'18, IEEE Distinguished lecturer, PhD in Physics) is currently a Full professor in Electrical Engineering and head of the Image and Signal Processing (ISP) group, http://isp.uv.es. He is interested in the development of machine learning algorithms for geosciences and remote sensing data analysis, and in particular the intersection between physics, statistical learning and causal inference. He is an author of around 250 journal papers, more than 300 conference papers, 20 international book chapters, and editor of 6 books on kernel methods and deep learning. He holds a Hirsch's index h=75 (Google Scholar), entered the ISI list of Highly Cited Researchers in 2011, and Thomson Reuters ScienceWatch identified one of his papers on kernel-based analysis of hyperspectral images as a Fast Moving Front research. He received two European Research Council (ERC) grants: an ERC Consolidator grant on "Statistical learning for Earth observation data analysis" (2015) and an ERC Synergy grant on "Understanding and Modelling the Earth system with machine learning" (2019). In 2016 he was included in the prestigious IEEE Distinguished Lecturer program of the GRSS.
Gustau Camps-VallsProffessor at Universitat de València
Gustau Camps-Valls (IEEE Fellow'18, IEEE Distinguished lecturer, PhD in Physics) is currently a Full professor in Electrical Engineering and head of the Image and Signal Processing (ISP) group, http://isp.uv.es. He is interested in the development of machine learning algorithms for geosciences and remote sensing data analysis, and in particular the intersection between physics, statistical learning and causal inference. He is an author of around 250 journal papers, more than 300 conference papers, 20 international book chapters, and editor of 6 books on kernel methods and deep learning. He holds a Hirsch's index h=75 (Google Scholar), entered the ISI list of Highly Cited Researchers in 2011, and Thomson Reuters ScienceWatch identified one of his papers on kernel-based analysis of hyperspectral images as a Fast Moving Front research. He received two European Research Council (ERC) grants: an ERC Consolidator grant on "Statistical learning for Earth observation data analysis" (2015) and an ERC Synergy grant on "Understanding and Modelling the Earth system with machine learning" (2019). In 2016 he was included in the prestigious IEEE Distinguished Lecturer program of the GRSS.
Maria-Esther VidalProf. Dr. at Universidad Simón Bolívar
Prof. Dr. (Univ. Simon Bolivar) Maria-Esther Vidal is the head of the Scientific Data Management Research Group at TIB and a member of the L3S Research Centre at the University of Hannover; she is also a full professor (on-leave) at Universidad Simón Bolívar (USB) Venezuela. Her interests include Big data and knowledge management, knowledge representation, and semantic web. She has published more than 170 peer-reviewed papers in Semantic Web, Databases, Bioinformatics, and Artificial Intelligence. She has co-authored one monograph, and co-edited books and journal special issues. She is part of various editorial boards (e.g., JWS, JDIQ), and has been the general chair, co-chair, senior member, and reviewer of several scientific events and journals (e.g., ESWC, AAAI, AMW, WWW, KDE). She is leading data management tasks in the EU H2020 projects iASiS, BigMedylitics, and QualiChain, and has participated in BigDataEurope, BigDataOcean; she is a supervisor of MSCA-ETN projects WDAqua and NoBIAS. She has been a visiting professor in different universities (e.g., Uni Maryland, UPM Madrid, UPC, KIT Karlsruhe, Uni Nantes). In the past, she has participated in international projects (e.g., FP7, NSF, AECI), and led industrial data integration projects for more than 10 years (e.g., Bell South, Telefonica).
Maria-Esther VidalProf. Dr. at Universidad Simón Bolívar
Prof. Dr. (Univ. Simon Bolivar) Maria-Esther Vidal is the head of the Scientific Data Management Research Group at TIB and a member of the L3S Research Centre at the University of Hannover; she is also a full professor (on-leave) at Universidad Simón Bolívar (USB) Venezuela. Her interests include Big data and knowledge management, knowledge representation, and semantic web. She has published more than 170 peer-reviewed papers in Semantic Web, Databases, Bioinformatics, and Artificial Intelligence. She has co-authored one monograph, and co-edited books and journal special issues. She is part of various editorial boards (e.g., JWS, JDIQ), and has been the general chair, co-chair, senior member, and reviewer of several scientific events and journals (e.g., ESWC, AAAI, AMW, WWW, KDE). She is leading data management tasks in the EU H2020 projects iASiS, BigMedylitics, and QualiChain, and has participated in BigDataEurope, BigDataOcean; she is a supervisor of MSCA-ETN projects WDAqua and NoBIAS. She has been a visiting professor in different universities (e.g., Uni Maryland, UPM Madrid, UPC, KIT Karlsruhe, Uni Nantes). In the past, she has participated in international projects (e.g., FP7, NSF, AECI), and led industrial data integration projects for more than 10 years (e.g., Bell South, Telefonica).