Holger Wittges is the Managing Director of the SAP University Competence Center (UCC) at the Technische Universität München (TUM) . His work focuses on Digital Transformation , Next Generation ERP , and Hybrid Cloud infrastructure. He is affiliated with the KrcmarLab and collaborates with IBM via the OpenPOWER@TUM initiative. Educational Background: 2004: Dr. rer. oec. (Promotion), Universität Hohenheim 1996: Diplom Wirtschaftsinformatiker, Universität Bamberg Research Interests include Digital Transformation, Cloud Computing, Enterprise Resource Planning (ERP), XaaS (Everything as a Service), and Service-Oriented Architecture (SOA). His work bridges academic innovation with industry needs through SAP UCC TUM, which provides 40+ educational service bundles like SAP HANA and S/4HANA for teaching and research. Recent Publications highlight advancements in machine learning for ERP support ticket systems, energy efficiency in SAP S/4HANA, and educational frameworks for cloud-based enterprise software. Articles emphasize collaboration with institutions across Europe and contributions to digital ecosystems like the SAP University Alliances. Key Projects include the OpenPOWER@TUM initiative with IBM, focusing on accessible AI/ML infrastructure for academia, and the SAP UCC TUM, which drives Education as a Service (EaaS) strategies for digital business ecosystems.
Byron Boots is the Amazon Professor of Machine Learning in the Paul G. Allen School of Computer Science and Engineering at the University of Washington, where he directs the UW Robot Learning Laboratory. He also serves as a Principal Research Scientist in the Seattle Robotics Lab at NVIDIA Research and co-chairs the IEEE Robotics and Automation Society Technical Committee on Robot Learning. Dr. Boots received his Ph.D. from the Machine Learning Department in the School of Computer Science at Carnegie Mellon University, where he was a member of the Sense, Learn, Act (SELECT) Lab co-directed by Carlos Guestrin and his advisor Geoff Gordon. Prior to joining the University of Washington faculty, he was an Assistant Professor in the School of Interactive Computing within the College of Computing at Georgia Tech, and before that, he completed a post-doc in the Robotics and State Estimation Lab directed by Dieter Fox at the University of Washington. Professor Boots' research focuses on the intersection of machine learning, artificial intelligence, and robotics, with particular emphasis on developing theory and systems that tightly integrate perception, learning, and control. His work spans computer vision, state estimation, localization and mapping, high-speed navigation, motion planning, and robotic manipulation. His group develops algorithms drawing from deep learning and neural networks, nonparametric statistics, graphical models, nonconvex optimization, quantum physics, online learning, reinforcement learning, and optimal control. The research demonstrates a strong theoretical foundation while maintaining practical relevance to real-world robotic systems. His recent publications reveal a clear trend toward integrating advanced machine learning techniques with robotics, particularly in model predictive control, motion planning, and learning-based approaches to robot control. His work shows increasing focus on developing theoretically grounded methods that can handle the complex, nonlinear dynamics of real-world robotic systems while maintaining computational efficiency. The publications span top venues including ICRA, CoRL, IROS, and NeurIPS, demonstrating broad impact across multiple subfields of robotics and AI. Finalist for Best Systems Paper at Conference on Robot Learning (CoRL-2021) Multiple papers selected for oral presentations at top robotics conferences Work recognized for theoretical contributions and practical applications in robot learning As director of the UW Robot Learning Laboratory, Boots leads a vibrant research group focused on fundamental and applied research in robot learning. The lab maintains strong collaborations with NVIDIA Research and has produced numerous high-impact publications that bridge theory and practice. Professor Boots teaches courses in autonomous robotics, machine learning, and reinforcement learning, contributing to both undergraduate and graduate education at the University of Washington.
Nathan van de Wouw is a Full Professor at the Mechanical Engineering Department of Eindhoven University of Technology (TU/e), affiliated with ICMS, EAISI Mobility, EAISI High Tech Systems, EAISI Foundational, and EIRES. He also holds an adjunct Full Professor position at the University of Minnesota and a part-time Full Professorship at Delft University of Technology. His research focuses on dynamics and control of mechanical systems, including mechatronics, robotics, smart manufacturing, energy systems, and networked control. He has supervised over 150 students and led numerous projects funded by industry partners like ASML, Philips, and Shell. Education: M.Sc. (with Honors) in Mechanical Engineering, TU/e (1994) Ph.D. in Mechanical Engineering, TU/e (1999) Research Interests: Nonlinear systems and control Model reduction and complexity analysis Data-driven and networked control strategies Applications in high-tech systems, autonomous vehicles, and energy systems Awards: IEEE Control Systems Technology Award (2015) for variable-gain control in motion systems Grants & Projects: Lead projects on mechatronic design, lithography systems, and thermodynamic optimization Collaborations with TNO, ASML, and industrial partners Labs & Teams: Member of TU/e’s Dynamics and Control group Affiliated with EAISI (Eindhoven AI Systems Institute)
Mendel Rosenblum is the Cheriton Family Professor and holds dual appointments as Professor in the Departments of Computer Science and Electrical Engineering at Stanford University. He is a co-founder of VMware Inc. and served as its Chief Scientist for its first decade, playing a pivotal role in designing foundational virtualization technologies. Rosenblum's research focuses on system software, distributed systems, and computer architecture, with notable contributions to virtualization, data center networks, and operating systems. He leads the Platform Lab at Stanford, exploring next-generation data center technologies and high-performance computing systems. Administrative Role: Faculty Director of Stanford Computer Forum (2012–present) Education: PhD (UC Berkeley, 1992), MS (UC Berkeley, 1989), BA (University of Virginia, 1984) His research interests span disk storage management, computer simulation, scalable operating systems, and security. Recent work emphasizes deployable consensus algorithms, programmable smartNICs, and self-programming networks. Rosenblum has authored over 80 publications and holds multiple patents in virtualization and system software. Awards & Recognition: ACM System Software Award (2009) IEEE Computer Entrepreneur Award (2011) ACM Thacker Breakthrough in Computing Award (2018) Member, National Academy of Engineering (2013) He advises PhD and Master's students, including current advisees Sina Jandaghi Semnani and Zixi Liu. Rosenblum teaches advanced courses on web applications, distributed systems, and independent research projects.
Massimo Canale is a Tenured Associate Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino , and a member of the CARS@PoliTO Interdepartmental Center for Automotive Research and Sustainable Mobility. His academic career spans over two decades, focusing on control systems engineering with applications in automotive technology. Scientific Branch: Systems and Control Engineering (IINF-04/A) ERC Sectors: Automotive Engineering, Control Engineering, Control Theory Dr. Canale's research bridges theoretical advancements in Model Predictive Control (MPC) with practical applications in autonomous vehicles , hybrid/electric propulsion , and active suspension systems . His work integrates reinforcement learning and dynamic programming for optimizing vehicle performance and energy efficiency. Recent publications demonstrate trends in autonomous driving architectures (2024), sliding mode control for highway scenarios (2024), and energy management for sustainable mobility (2023-2024). He has developed patented solutions for semi-active suspension control and autonomous vehicle guidance. Award: IEEE Transactions on Control Systems Technology Outstanding Paper Award (2011) Editorial Roles: Associate Editor, IEEE Open Journal of Control Systems (2022–present) Dr. Canale supervises PhD students like Francesco Cerrito and teaches courses on digital control technologies , automatic control , and reinforcement learning at Politecnico di Torino. His research is funded through competitive grants (e.g., MPC4AVP 2021-2022) and commercial contracts (AD Shuttle 2024).
Benjamin J. Delaware is an Assistant Professor of Computer Science at Purdue University. His research focuses on programming languages, formal verification, and tools for ensuring software correctness using mechanized theorem provers. He holds a Ph.D. from The University of Texas at Austin (2013), an MSc from Washington University in St. Louis (2007), and a B.S. from Truman State University (2005). His work emphasizes practical formal methods, including static enforcement of privacy policies, compiler design for oblivious computation, and automated verification techniques. Key contributions include tools like Taypsi, KestRel, and HACCLE. His research bridges theory and practice, addressing challenges in software security, correctness, and efficiency. Publications span top venues like POPL, PLDI, and OOPSLA, reflecting a strong focus on foundational programming language concepts. Collaborations with researchers like Suresh Jagannathan and Qianchuan Ye drive advancements in automated reasoning and secure computation.
Maurice Heemels is a Full Professor at Eindhoven University of Technology (TU/e), leading the Control Systems Technology group. He holds additional professorships in EAISI Mobility, EAISI Foundational, EAISI Health, and EAISI High Tech Systems. His research focuses on hybrid and networked systems, emphasizing resource-aware control, event-triggered strategies, and cyber-physical systems integration. He is an IEEE Fellow and chairs the IFAC Technical Committee on Networked Systems. Academic Background: MSc and PhD in Mathematics (TU/e, 1995 and 1999, both summa cum laude ) Visiting Professorships: ETH Zurich (2001), UC Santa Barbara (2008) Industry Experience: Research & Development at Océ NV Research Interests: Hybrid Systems, Networked Control, Event-Triggered Control Model Predictive Control (MPC) in healthcare and high-tech systems Cyber-Physical Systems for applications like lithography and precision agriculture Key Contributions: Developed Hybrid Integrator-Gain (HIGS) systems and Projection-Based Control methodologies Recipient of a VICI Grant for wireless control systems research Oversaw over €7M in research funding from NWO, EU, and industry Awards & Recognition: Automatica Outstanding Service Award (2014) Best Paper Awards (EBCCSP 2017, etc.) Invited Keynote Speaker at ECC, CDC, and others Grants & Projects: Current Projects: COMEDI (Cost-effective Mechatronics), PROACTHIS (Projection-based Control) Past Projects: Fault Detection in Wafer Scanners, Drone-based Farming Labs & Teams: Active in TU/e’s Cyber-Physical Systems and Systems Engineering research groups, collaborating globally on nonsmooth dynamics and hybrid systems.
Chris Freeman is a Professor of Robotics and Control at the University of Southampton's Electronics and Computer Science (ECS) school. His research focuses on iterative learning control theory, biomedical engineering, and robotics with applications in industrial automation and healthcare. As Deputy Head of School (Equity, Diversity and Inclusion) and Chair of the ECS Belonging, Inclusion, Diversity and Equity (BIDE) Committee, he drives initiatives promoting inclusive academic environments. Freeman leads multidisciplinary research projects such as "Towards intelligent, pervasive, high performance control system architectures" "Elder Athletes: building incidental interaction at home" "Low-cost personalised instrumented clothing with integrated FES electrodes" . His work combines robotics, functional electrical stimulation (FES), and wearable technologies to develop rehabilitation systems for stroke patients and industrial automation solutions. His recent publications demonstrate expertise in iterative learning control (ILC), model predictive control, and biomedical applications. Research groups include: Digital Health and Biomedical Engineering Institute for Life Sciences Centre for Health Technologies Centre for Robotics
Dr. Keivan Ahmadi is an Associate Professor in the Department of Mechanical Engineering at the University of Victoria (UVic), serving as Graduate Program Director. He holds a PhD from the University of Waterloo (2012), followed by postdoctoral positions at UBC and Pratt & Whitney Canada. His research focuses on dynamics and vibrations in machining processes, robotic manufacturing, and advanced manufacturing systems. Education: BSc (Tehran Polytechnic), MSc (IUST), PhD (Waterloo) Affiliations: Dynamics and Digital Manufacturing Lab (DDML), UVic Mechanical Engineering Research interests include vibration suppression in machining, chatter prediction, robotic milling dynamics, and high-speed manufacturing systems. His work combines experimental modal analysis, Bayesian modeling, and data-driven approaches to enhance manufacturing precision and sustainability. Key projects include vibration compensation in 3D printing, dynamic modeling of robotic arms for milling, and optimization of thin-walled structure machining. Over 20 peer-reviewed articles showcase his contributions to machining stability, FRF estimation, and additive manufacturing. Advised 19 graduate students (9 alumni, 10 current) Collaborations with industries like GM, Linamar, and CanEV Labs/Teams: Leads the Dynamics and Digital Manufacturing Lab (DDML), focused on sustainable manufacturing through dynamic systems innovation. Hosts a diverse team prioritizing underrepresented groups in engineering.
Gabor Orosz is a Professor at the University of Michigan in both the Department of Mechanical Engineering and Department of Civil and Environmental Engineering . His work bridges nonlinear dynamics and control , time delay systems , and connected automated vehicles , with a focus on traffic flow optimization and vehicle safety . Education: PhD in Engineering Mathematics, University of Bristol, UK (2006) MSc in Engineering Physics, Budapest University of Technology and Economics, Hungary (2002) Research Focus : Orosz's research explores the intersection of vehicle automation , connectivity , and nonlinear dynamics . He investigates time delay effects in teleoperation , intent-sharing protocols for cooperative maneuvering , and control barrier functions for safety-critical systems . His work spans theoretical analysis, numerical validation, and real-world experimentation. Article Trends : Recent publications highlight advancements in latency mitigation for remote driving , nonholonomic vehicle control , intent-sharing frameworks , and energy-efficient strategies for connected vehicle systems . Themes include delayed feedback , stochastic communication , and safety-guaranteed control . Awards & Appointments : NSF CAREER Award (2014) Fulbright Scholar at Budapest University of Technology (2023-2024) Editorial roles in Vehicle System Dynamics (2020) and Time Delay Systems (2017) Student Mentorship : Orosz has advised numerous PhD students, including Anil Alan (2024, TU Delft), Chaozhe He (2018, University at Buffalo), and Tamás Molnár (2020, Wichita State University). His alumni work at institutions like Toyota Research Institute , Ford Motor Co. , and Zoox . Labs & Teams : He leads research at the University of Michigan's Mechanical Engineering Department and collaborates with international institutions such as Caltech and Budapest University of Technology . His team focuses on experimental validation of connected vehicle systems and delay-tolerant control .
Professor Matthew Jonathan Rosseinsky holds the Chair of Inorganic Chemistry at the University of Liverpool, a position he has occupied since October 1999. His career includes significant appointments at the University of Oxford (1992-1999) and Bell Laboratories in New Jersey (1990-1992), following his DPhil at Merton College, Oxford. As a Fellow of the Royal Society and recipient of numerous prestigious awards, Professor Rosseinsky maintains an active research program and leadership roles in the international chemistry community. Professor Rosseinsky's educational background includes a First Class Honours degree in Chemistry with Quantum Chemistry from the University of Oxford (1987) and a DPhil in "Physical Properties of Superconducting Oxides and Radical Cation Salts" completed in 1990 under Professor P. Day FRS. His research focuses on the synthesis of new materials with applications in energy storage and generation, communications, separation, and catalysis. The Rosseinsky Group employs a broad range of synthesis and characterization techniques, including neutron and synchrotron X-ray diffraction, combined with computational methods in collaboration with Dr. George Darling. Current research areas include Dynapore, CO2 fuels, SOLBAT, and CATMAT projects that target specific material challenges. Professor Rosseinsky's publication record is exceptional, with 304 papers including 11 in Nature, 6 in Science, and 3 in Nature Materials, accumulating over 15,000 citations and an h-index of 56 as of 2012. His work demonstrates consistent excellence across materials chemistry, with particular emphasis on porous frameworks, electronic materials, and solid-state chemistry. Among his numerous accolades are the Harrison Memorial Prize (1991), Corday-Morgan Medal (2000), Royal Society Wolfson Research Merit Award (2002), De Gennes Prize (2009), and the prestigious Hughes Medal from the Royal Society (2011). He also holds an ERC Advanced Investigator Grant and has delivered distinguished lectures worldwide. Professor Rosseinsky has served in numerous editorial and advisory capacities, including as Associate Editor for Chemical Sciences, membership on the Royal Society Conference and Travel Grant Committee since 2007, and as a member of the International Advisory Board for the Max Planck Institut for Solid State Research since 2011. His professional activities extend to international review committees for research institutions in France, South Korea, and Saudi Arabia. The Rosseinsky Group operates within the Department of Chemistry at the University of Liverpool, collaborating extensively with researchers including Dr. John Claridge, Professor Andrew Cooper, and Professor Paul Chalker. The group maintains strong international partnerships and utilizes advanced facilities for materials synthesis and characterization to drive innovation in functional materials development.
Dr. Ghazal Bargshady is a Lecturer at the University of Canberra , with expertise in Affective Computing , Artificial Intelligence , and Healthcare Technology . Her roles include teaching units such as Computer Vision, Data Analytics, and Soft Computing, as well as supervising PhD and Master by Research students in AI-driven projects for healthcare and road safety. Education: She earned her PhD in Artificial Intelligence and Computer Vision from the University of Southern Queensland in 2020. Research Interests: Dr. Bargshady specializes in Computer Vision Deep Learning Biosignal Processing Facial Expression Analysis Human Factors in AI Wearable Sensors Multimodal Data Fusion Brain–Computer Interfaces Her work addresses real-world challenges in pain assessment, depression recognition, and driver safety using cutting-edge AI models. Article Trends: Her recent publications focus on Transformer architectures , fNIRS signal analysis , multimodal pain detection , and depression severity estimation via facial video data. These studies highlight her contributions to AI in healthcare , transportation safety , and biomedical signal processing . Teaching Activities: Dr. Bargshady has lectured units including Programming for Data Science , Computer Vision , and Soft Computing , emphasizing practical AI applications.
Wenchao Li is an Assistant Professor in the Department of Electrical and Computer Engineering at Boston University, directing the Dependable Computing Laboratory. He holds a B.S., M.S., and Ph.D. in Electrical Engineering and Computer Sciences, along with a B.A. in Economics from UC Berkeley. His research focuses on dependable computing, applying formal verification, machine learning, and control theory to cyber-physical systems, electronic design automation, and AI safety. Key research interests include neural network verification, safe reinforcement learning, autonomous systems security, and resilient control strategies for connected vehicles. His work emphasizes provable safety guarantees and defense against adversarial attacks in critical infrastructure systems. Notable awards include the ACM Outstanding Ph.D. Dissertation Award and the Leon O. Chua Award. His lab investigates topics such as neural network repair, secure multi-robot coordination, and formal methods for autonomous systems. He advises students like Jiameng Fan and collaborates on projects funded by grants in AI safety and cyber-physical systems. Labs/Teams: Dependable Computing Laboratory Grants: Focus on formal verification, AI safety, and autonomous systems resilience
Professor Bruce N. Walker holds a joint appointment in the School of Psychology and School of Interactive Computing at Georgia Institute of Technology, within the College of Sciences. His research focuses on human-centered technology design, emphasizing accessibility, auditory displays, and human-AI interaction. He leads the Sonification Lab, pioneering multimodal interfaces and inclusive technology solutions. He earned his Ph.D. in Human Factors and Human-Computer Interaction from Rice University in 2001. Research Interests: Trust in technology, accessible interfaces, sonification, AI-human collaboration, and HCI in non-traditional environments. Current projects include the AccessCORPS VIP initiative to enhance course accessibility and studies on automated vehicle interaction. Awards: Best Paper Award at AudioMostly 2014 for auditory weather reports research. Active in professional organizations like the International Community for Auditory Display and Human Factors and Ergonomics Society. Teaching: Courses include Research Methods for Human Factors, Sensation and Perception, and HCI Foundations. Supervises interdisciplinary teams in the Sonification Lab R&D Studio and AccessCORPS VIP. Labs/Teams: Sonification Lab (multimodal data exploration) and AccessCORPS (disability-inclusive course design). Collaborates on international projects like the Mwangaza initiative for learners with vision impairment in Kenya.
Hollis Cline, PhD, is the Hahn Professor of Neuroscience and Director of the Dorris Neuroscience Center at The Scripps Research Institute (TSRI). She holds adjunct positions at the University of California San Diego and the Salk Institute. Her research focuses on understanding how sensory experience shapes visual circuit development, plasticity, and function, with a focus on neurodevelopmental disorders. Cline earned her PhD in Neurobiology from UC Berkeley (1985) and conducted postdoctoral work at Yale and Stanford. She has served in leadership roles including Co-Chair of TSRI’s Department of Neuroscience and President of the Society for Neuroscience (2015–2016). Her research integrates molecular genetics, electrophysiology, and imaging to study structural dynamics in neural circuits, neurogenesis regulation, and excitation/inhibition balance. Key projects include the Dynamic Connectome (3D connectomics in the optic tectum), neurogenesis control, and the role of inhibition in visual circuit function. Her work revealed activity-dependent mechanisms driving synaptic maturation and topographic map formation, and identified molecular pathways linking visual experience to brain development. Education : PhD (UC Berkeley), B.A. (Bryn Mawr College) Awards : NIH Pioneer Award, AAAS Fellow, TSRI Mentor Award Labs/Teams : Cline Lab at TSRI, Dorris Neuroscience Center Grants : Not explicitly listed but implied via NIH advisory roles and research infrastructure Professional Service : NINDS Board, NIH Advisory Council, Society for Neuroscience leadership Her recent work bridges neurodevelopmental mechanisms with translational insights, using Xenopus models to study exosome-mediated intercellular communication and regeneration responses to injury. Collaborative efforts include the BigNeuron project for neuronal morphology analysis and AI-driven behavior recognition studies.
