Handover Engineering Professors and Supervisors

Martin Baumannمشاهده پروفایل

استاد

Ulm UniversityGermany

Prof. Dr. Martin Baumann is Chair of Human Factors at Ulm University, a position he has held since February 2014. His research is centered on cognitive and behavioral aspects of human interaction with advanced technological systems, particularly in automated transportation. He leads a research group focused on human-machine systems, with strong affiliations to transportation safety and driver assistance technologies. His research interests include: Cognitive Modeling and empirical studies of human behavior in human-machine systems Attention processes, situational awareness, and cognitive distraction Design and implementation of cooperative driver assistance and automation systems Multimodal interaction and transitions between automated and manual driving modes Diagnostic reasoning and decision-making under uncertainty His scholarly work, accessible via Google Scholar, demonstrates a consistent focus on understanding and enhancing human performance in automated environments. Key trends across his recent publications include modeling driver cognition, evaluating multimodal interfaces, and improving the safety of human-automation handovers in vehicles. His work integrates cognitive psychology with engineering design to develop human-centered automation. Scientific Contributions: Developed cognitive models of driver behavior and situational understanding Pioneered research on attentional tunneling and cognitive distraction in automated driving Advanced methodologies for usability evaluation of in-vehicle technologies Influenced design principles for cooperative human-machine interaction Prof. Baumann has supervised numerous research projects and mentored early-career researchers, though specific student names are not listed. His work has been supported by national and institutional research grants related to transportation safety and human factors engineering. He previously led research groups at the German Aerospace Center (DLR) and held postdoctoral positions at Chemnitz University of Technology and BASt, reflecting a deep engagement with applied cognitive science. He is associated with the Human Factors research lab at Ulm University, which conducts empirical studies on driver behavior, cognitive load, and interface design using driving simulators, eye-tracking, and cognitive task analysis. The team focuses on holistic evaluation methods for next-generation driver assistance systems.

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Mohammad Saquibمشاهده پروفایل

استاد

University of Texas at DallasUnited States

Mohammad Saquib is a Professor in the Department of Electrical Engineering at the Erik Jonsson School of Engineering and Computer Science, University of Texas at Dallas. He has been a faculty member at UT Dallas since 2000, progressing from Assistant to Associate and currently Professor. Prior to this, he held assistant professor positions at Louisiana State University. Education: Ph.D. in Electrical Engineering, Rutgers University, 1998 M.S. in Electrical Engineering, Rutgers University, 1995 B.S. in Electrical Engineering, Bangladesh University of Engineering & Technology, 1991 Mohammad Saquib's research focuses on wireless data transmission, emphasizing system modeling, performance evaluation, signal processing, and radio resource management. A significant portion of his work explores open-access spectrum sharing techniques and the development of low-cost signal processing solutions for radar and medical applications, particularly in microsurgery. His expertise bridges theoretical and applied domains in communications and signal processing. The 15 most recent articles (limited to 8 available) reflect a consistent focus on wireless systems, signal processing algorithms, and their applications in aerospace, medical, and mobile networks. Key themes include interference mitigation, handover optimization, adaptive modulation, and real-time physiological signal prediction. The publications appear in top-tier IEEE journals, demonstrating sustained scholarly impact. Scientific Awards and Recognitions: University of Texas System Regents’ Outstanding Teaching Award, 2014 Best paper award, International Test Synthesis Workshop (ITSW), 2007 Best student paper award, IEEE International Waveform Diversity and Design Conference, 2009 Best doctoral dissertation award (advised student), 2005 Donald Ceil & Elaune T. Delaune Endowed Professorship, 2000–2004 IEEE Senior Member (2009–present) Multiple best paper finalists and teaching recognitions Mohammad Saquib has successfully advised numerous graduate students, many of whom have received national awards for their research and theses. He has served as associate editor for IEEE Transactions on Wireless Communications and IEEE Communications Letters , contributing significantly to academic service. His work has been supported by institutional and professional recognition, though specific grant details are not listed in the text. He is deeply committed to teaching excellence, as reflected in multiple awards and student testimonials. He leads research in wireless and signal processing systems, likely supervising a lab or research group focused on communications and biomedical signal processing, though no formal lab name is provided.

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Andreas Sondereggerمشاهده پروفایل

مدرس

University of FribourgSwitzerland

Andreas Sonderegger is a Lecturer at the Department of Psychology , University of Fribourg , and group leader of the Human Factors Lab . His research focuses on Human-Computer Interaction , Usability Engineering , and User Experience (UX) , with particular emphasis on: Web accessibility for diverse user groups Neurofeedback systems for cognitive enhancement Human factors in automated driving Cross-cultural usability testing Physiological computing for user state assessment His recent publications analyze: Neurofeedback applications for tinnitus treatment Human-AI decision-making comparisons Physiological indicators in automated driving Usability of no-code robotics programming He has contributed to journals such as: Computers in Human Behavior Scientific Reports Ergonomics International Journal of Human Computer Studies

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Henrik Ebelمشاهده پروفایل

استادیار

Lappeenranta-Lahti University of Technology LUTFinland

Henrik Ebel is an Assistant Professor (Tenure Track) in Mechanical Engineering at Lappeenranta-Lahti University of Technology (LUT), specifically within the LUT School of Energy Systems. He joined LUT in 2024 after previously working at the University of Stuttgart's Institute of Engineering and Computational Mechanics from 2016 to 2024. Dr. Ebel's research focuses on the intersection of artificial intelligence, machine learning, and mechanical engineering, with particular emphasis on: Distributed cooperative robotics Model predictive control systems Non-holonomic robot control Data-driven approaches to mechanical engineering problems Automation systems development His research aims to bring cooperative robotics from laboratory settings to real-world applications in Finland, focusing on using multiple simple and cost-efficient robots that collaborate to solve problems rather than relying on single complex machines. He believes automation promotes sustainability through better energy conservation, generation, and storage compared to manual processes. His recent publications demonstrate consistent advancement in cooperative robotics, control systems, and machine learning applications in mechanical engineering. As an educator, Dr. Ebel supervises doctoral students and finds fulfillment in seeing them grow and succeed in their research. He values the human aspect of academia and enjoys teaching as a complement to his research work, noting that honing teaching skills helps him explain research better and pass on important future-oriented knowledge.

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Karl Norrmanمشاهده پروفایل

پژوهشگر

KTH Royal Institute of TechnologySweden

Karl Norrman is an Industry doctoral student and Researcher at the Department of Theoretical Computer Science (TCS) at KTH Royal Institute of Technology, concurrently working as a Security Researcher at Ericsson Research since 2001. His academic appointment at KTH is part-time (20% time allocation), while he spends the majority of his time (80%) at Ericsson, where he holds the formal title of Expert Mobile Network Security. He is supervised by Professor Mads Dam for his doctoral studies and receives partial research funding from the Wallenberg AI, Autonomous Systems and Software Program (WASP). His educational background includes: PhD candidate in Computer Science at KTH Royal Institute of Technology, Department of Theoretical Computer Science (ongoing). Research focuses on formal modeling and proofs for cryptographic protocols using pen-and-paper proofs and mechanized proof-support tools such as Tamarin and EasyCrypt. Master's degree in Computer Science from Stockholm University, Department of Mathematics (2001). Thesis: "RTP Security in 3G Networks." During this work, he contributed to the development of the Secure Real-time Transport Protocol (SRTP), standardized in IETF as RFC 3711. Norrman's research centers on formal methods for security protocol verification , with particular expertise in cryptographic protocol analysis, modeling, and mechanized proof techniques. His work bridges theoretical computer science and practical security applications, focusing on making formal verification tools accessible for industrial adoption. Key research areas include 5G/6G security architectures, privacy-preserving mechanisms for mobile networks, authentication and key agreement protocols, and software security. He advocates for "goal oriented and motivated security designs" that balance theoretical rigor with practical implementation constraints while specializing in translating complex security requirements into implementable solutions for telecommunications infrastructure. Analysis of Norrman's publication history reveals a consistent evolution from foundational work on SRTP (2002-2007) through LTE security analysis (2014-2015) to pioneering 5G security research (2016-2020) and now 6G security exploration (2024). His work demonstrates methodological progression from analyzing existing protocols to designing novel security mechanisms and developing verification frameworks like OpenSAW. A distinctive pattern is his focus on industrial applicability —ensuring theoretical security models translate to real-world implementations, particularly evident in his work on USIM-compatible protocols and error-correcting authentication for noisy wireless channels. Recent publications increasingly address cross-domain challenges like secure federated learning in mobile networks, reflecting the expanding scope of telecommunications security. Professional engagement: Reviewer for ACM CCS 2023, EURO S&P 2023, ACM CCS 2022, NordSec 2022, Vietcrypt 2006, IEEE Telecommunications Journal Active contributor to 3GPP security standardization processes Co-author on multiple Ericsson whitepapers shaping industry security practices Norrman maintains a unique dual affiliation that enables direct translation of academic research into industrial security solutions. At KTH, he contributes to the Theoretical Computer Science group's formal methods research, while at Ericsson he applies these techniques to real-world security challenges in mobile network development. His work on OpenSAW exemplifies this bridge between academia and industry, creating practical tools for automated security testing of component-based software systems. This position allows him to identify emerging security challenges in next-generation networks while maintaining theoretical rigor in his approach.

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Jeroen J.L. Schepersمشاهده پروفایل

دانشیار

Eindhoven University of TechnologyNetherlands

Jeroen J.L. Schepers is an Associate Professor at Eindhoven University of Technology, affiliated with the Department of Industrial Engineering and Innovation Sciences and the Innovation Technology Entrepreneurship & Marketing group. He also holds a position within the EAISI Foundational research institute. His current educational activities include teaching courses on Marketing Perspectives on Product Innovation, Servitization and Customer Experience, and Multivariate Statistics. Dr. Schepers specializes in the digitalization and robotization of frontline services, with particular focus on the psychological responses of both customers and employees to service technologies. His research examines how AI and robotics transform service encounters, exploring questions about customer adoption of service innovations, the impact of technology on service value, and the optimal collaboration between humans and technology in service delivery. His work spans service marketing, human-robot interaction, consumer psychology, and digital service transformation, with particular emphasis on service robotics, customer experience design, and the psychological mechanisms underlying technology adoption in service contexts. His recent publications reveal a strong focus on human-AI collaboration in service contexts, with recurring themes around service robot design, customer perception of technology, and the psychological mechanisms that determine service success or failure. His research demonstrates how service robots impact customer experience, how frontline employees interact with AI systems, and how service encounters can be optimized through intelligent technology integration. The work spans both theoretical development and practical applications across various service industries. Dr. Schepers has received numerous prestigious awards including the Robert Johnston Outstanding Reviewer Award (2024), multiple highly cited papers in the top 1% of Economics & Business, the Insights Scientist of the Year award (2023), and several Industria Education Awards. His research has been recognized with Best Paper Awards from leading service marketing journals and conferences. HybridLabs - €10.4M grant accelerating Dutch innovations in offshore renewables D-SIDE: Decision Support for Intelligent Damage Estimation and Control (€1.1M) 3TU.CEE research project Grant from DAAD for visiting scholarship at University of Mannheim Dr. Schepers leads research within the Innovation Technology Entrepreneurship & Marketing group, focusing on how digital technologies transform service encounters and employee-customer interactions. His work examines both customer-facing service technologies and employee-facing intelligent systems, investigating how these technologies reshape service delivery, customer experience, and employee work practices in the digital age.

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Lauri Lovénمشاهده پروفایل

استادیار

University of OuluFinland

Lauri Lovén is a tenure-tracked Assistant Professor at the University of Oulu's Faculty of Information Technology and Electrical Engineering. As vice-director of the Center for Ubiquitous Computing (UBICOMP) and leader of the Future Computing Group (20+ researchers), he coordinates the Distributed Intelligence strategic research area within Finland's 6G Flagship program. Education: D.Sc.(Tech.) 2021, Docent (Edge Intelligence) 2025, University of Oulu Prior Affiliations: TU Wien (2022), ETH Zürich (2023) Research Focus: Specializing in edge intelligence and distributed AI, his work explores cognitive computing continuums across 6G networks, IoT systems, and industrial metaverse applications. Recent Trends: Recent publications reveal two key directions: 1) AI optimization for 6G wireless networks (handover management, semantic slicing), and 2) intelligent data management frameworks (data fabric, message brokers) for distributed systems. Industry Experience: Combines 20 years of software industry expertise with academic research, having served as founder, CTO, and advisor in AI startups.

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Julie K Johnsonمشاهده پروفایل

استاد مدعو

Northwestern UniversityUnited States

Julie K Johnson, MSPH, PhD, serves as an Adjunct Professor in the Department of Surgery (Surgical Oncology) at Northwestern University Feinberg School of Medicine, focusing on healthcare quality improvement through collaborative research, teaching, and clinical initiatives. Her work bridges academic rigor with practical healthcare delivery enhancements across diverse clinical settings. Education: MSPH, University of North Carolina (1993) PhD in Evaluative Clinical Sciences, Dartmouth College (2000) Dr. Johnson specializes in qualitative research methodologies applied to patient safety and clinical microsystem evaluation. Her expertise spans surgical quality improvement, error prevention in pediatric and adult settings, team communication dynamics, and handover processes. Current research includes leading the qualitative evaluation of the Illinois Surgical Quality Improvement Collaborative (ISQIC), examining firearm injury prevention in surgical practice, and developing patient-centered tools for peripheral artery disease management. She emphasizes mixed-methods approaches to translate research into actionable quality improvement strategies. Recent publications demonstrate consistent focus on surgical safety, implementation science, and social determinants of health. Key trends include opioid stewardship protocols, trauma system redesign, patient activation in chronic disease management, and the impact of neighborhood factors on health outcomes. Her work frequently employs qualitative frameworks to uncover systemic barriers and facilitators in healthcare delivery. Awards: Research Mentor Award, Northwestern University Department of Surgery (2022) Dr. Johnson actively contributes to the Institute for Public Health and Medicine (IPHAM) - Center for Health Services & Outcomes Research, the Northwestern University Clinical and Translational Sciences Institute (NUCATS), and the Robert J. Havey, MD Institute for Global Health (IGH). Her collaborative approach engages clinicians, patients, and families in co-designing quality improvement initiatives, particularly through statewide surgical collaboratives and community-based health equity projects.

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Shahid Khanمشاهده پروفایل

استادیار

Gdańsk University of TechnologyPoland

Dr. Shahid Khan serves as an Assistant Professor in the Department of Microelectronic Systems at the Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology. His academic appointment is firmly situated within the engineering faculty, where he contributes to research and teaching in microelectronics and telecommunications systems. Research Interests: Dr. Khan's primary research spans wireless communications for 5G and beyond (B5G), with a concentrated focus on Internet of Things (IoT) applications. His work encompasses the design of advanced antenna systems including MIMO configurations for millimeter-wave frequencies, beam steering techniques, and the integration of machine learning for mobility management in autonomous vehicle networks. He also investigates electromagnetic structures such as frequency selective surfaces and metamaterials to enhance wireless coverage and reduce path loss in advanced communication systems. Publication Trends: His 2025 publications demonstrate a cohesive research trajectory centered on innovative solutions for 5G IoT infrastructure. Key themes include compact antenna array design for millimeter-wave bands, port isolation techniques using metamaterials, and machine learning algorithms for seamless handovers in vehicular networks. These contributions appear in high-impact journals including IEEE Internet of Things Journal and Scientific Reports, reflecting his specialization in advancing wireless communication technologies for next-generation applications. Scientific Awards: No specific awards, fellowships, or medals were mentioned in the provided information. Advising and Grants: The available text contains no details regarding graduate students supervised by Dr. Khan or research grants secured for his projects. His academic profile emphasizes publication output rather than mentoring or funding activities. Laboratory Affiliations: While specific laboratory facilities aren't explicitly detailed, his research on 3D-printed dielectric lenses and metamaterial integration suggests active involvement with antenna fabrication and testing facilities within the Department of Microelectronic Systems.

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Sathish Kumarمشاهده پروفایل

دانشیار

Cleveland State UniversityUnited States

Sathish Kumar is an Associate Professor in the Department of Electrical Engineering and Computer Science at Cleveland State University's Washkewicz College of Engineering. He serves as Director of the Intelligent Secure Cyber-Systems Analytics and Applications Research (ISCAR) Lab and holds editorial positions with PLOS One, IEEE Access, and Nature Scientific Reports. With over a decade of industry experience prior to joining academia in 2013, Dr. Kumar has established himself as a prominent researcher in cybersecurity and emerging technologies. Dr. Kumar's research spans Cybersecurity, Machine Learning, Distributed Systems, and Quantum Computing, with applications in Intelligent Cyber Physical Social Systems, Smart Cities, Blockchain, Disaster Resilience, and Health Informatics. His work demonstrates a consistent focus on practical security solutions for emerging technologies, particularly in IoT and IIOT environments. Recent publications show increasing emphasis on quantum machine learning applications and reinforcement learning approaches to security challenges. His research program has attracted significant funding, including multiple NSF grants as PI and Co-PI, CDC and NIH funding for public health applications, and industry partnerships. Dr. Kumar has published over 80 technical papers and co-edited a book on IoT security challenges. His editorial roles with major journals reflect his standing in the research community. National Science Foundation Grant ($799,985) as PI for quantum sensor research (2022-2025) National Science Foundation Grant ($434,431) as Co-PI for HPC infrastructure (2022-2025) Multiple additional NSF, CDC, and industry-funded projects Dr. Kumar actively mentors students at all levels, currently supervising multiple PhD students, postdoctoral researchers, and undergraduate honors students. His lab provides opportunities for students to engage in cutting-edge research with practical applications in cybersecurity and emerging technologies, supported by substantial external funding that ensures resources for student participation.

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Wolfram Remlingerمشاهده پروفایل

استاد

University of StuttgartGermany

Wolfram Remlinger is a Professor and Head of Interior Design Engineering at the Institute for Engineering Design and Industrial Design, University of Stuttgart. His work focuses on the analysis, evaluation, and design of vehicle interiors and cockpits, with particular emphasis on innovative computer-aided and model-based design methods for automated driving systems. Professor Remlinger completed his dissertation "Analyse von Sichteinschränkungen im Fahrzeug" (Analysis of Sight Restrictions in Vehicles) at the Technical University of Munich in 2013, earning his Dr.-Ing. (Doctor of Engineering) degree. His academic journey reflects a deep specialization in automotive human factors and ergonomics. Professor Remlinger's research spans vehicle interior design for automated driving , digital human modeling , and ergonomic evaluation methods . He specializes in developing innovative approaches to assess comfort, safety, and usability in next-generation vehicle interiors. His work bridges traditional automotive engineering with emerging technologies like virtual reality , mixed reality , and serious gaming for interior evaluation. A key focus area is analyzing driver take-over scenarios in automated driving systems, examining both physical readiness and cognitive aspects of the human-machine handover process. Analysis of his recent publications (2023-2025) reveals a strong research trajectory focusing on shared automated vehicles, with particular attention to passenger security, comfort optimization, and user acceptance. His methodological approach increasingly incorporates immersive technologies and user-centered frameworks , reflecting the evolving challenges of designing interiors for fully automated mobility. The interdisciplinary nature of his work connects automotive engineering with human factors, cognitive science, and industrial design. Professor Remlinger maintains an active research program with numerous industry collaborations, particularly evident from his extensive patent portfolio with automotive manufacturers like Audi AG. His work demonstrates consistent contribution to both academic knowledge and practical automotive design solutions. Based at the University of Stuttgart in Room 1.204 at Pfaffenwaldring 9, Professor Remlinger leads a research group utilizing advanced simulation technologies and digital human modeling tools to address contemporary challenges in vehicle interior design. His team's work is particularly relevant as the automotive industry transitions toward higher levels of automation and shared mobility concepts.

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