Invited Speakers 

Frank Hutter is a Full Professor for Machine Learning at the Computer Science Department of the University of Freiburg 

(Germany), as well as Chief Expert AutoML at the Bosch Center for Artificial Intelligence. Frank holds a PhD from the 

University of British Columbia (UBC, 2009) and a Diplom (eq. MSc) from TU Darmstadt (2004). He received the 2010 CAIAC 

doctoral dissertation award for the best thesis in AI in Canada, and with his coauthors, several best paper awards and prizes 

in international competitions on machine learning, SAT solving, and AI planning. He is the recipient of a 2013 Emmy Noether 

Fellowship, a 2016 ERC Starting Grant, a 2018 Google Faculty Research Award, a 2020 ERC PoC Award, and he is a Fellow of 

ELLIS. Frank‘s recent research focuses on automated machine learning (AutoML), where he co-organized the ICML workshop 

series on AutoML every year since its inception in 2014, co-authored the prominent AutoML tools Auto-WEKA, Auto-sklearn, 

and Auto-PyTorch, won the first two AutoML challenges with his team, co-authored the first book on AutoML, worked 

extensively on efficient hyperparameter optimization and neural architecture search, and gave a NeurIPS 2018 tutorial

 with over 3000 attendees.                                                                        

        

       

Baopu Li obtained his Ph.D degree in the field of computer vision and robotics from the Chinese University of Hong Kong 

in 2008. After that, he was in the academic field for another 8 years. Since 2016, he changed his career path to industry in 

the USA, and now he is a director at Oracle Cloud. His major research and development interests include Auto machine 

learning (ML), low-level image processing, video understanding and so on together with their applications on cloud and 

edge devices.                                                                        

        

                                                                    

        

                                                                   

        

       

Radu Marculescu is a Professor and the Laura Jennings Turner Chair in Engineering in the Department of Electrical and Computer 

Engineering at The University of Texas at Austin. Between 2000-2019, he was a Professor in the Electrical and Computer Engineering 

department at Carnegie Mellon University. His current research focuses on developing ML/AI algorithms and tools for system design 

and optimization for computer vision, bioimaging, and IoT applications. He has received the 2019 IEEE Computer Society Edward 

J. McCluskey Technical Achievement Award, for seminal contributions to the science of network on chip design, analysis, and 

optimization. Most recently, he received the 2020 ESWEEK Test-of-Time Award from The International Conference on Hardware/ 

Software Co-Design and System Synthesis (CODES). He is an IEEE Fellow and an ACM Fellow.