Find Academic Supervisors

Beate FlathView profile

Professor

• Transdisciplinary Event Research
• Cultural Management
• Popular Music Cultures
• +5 more

Prof. Dr. Beate Flath serves as Vice President for Teaching, Studies and Quality Management at the University of Paderborn since April 2025, while simultaneously leading the C:POP. Transdisciplinary Research Center for Popular Music Cultures and Creative Economies as Managing Director since June 2023. Her academic appointment is as Professor (W2) for Event Management with a focus on pop music cultures and digital media cultures within the Faculty of Arts and Humanities, Department of Music at the University of Paderborn. Her educational foundation includes: Diplomstudium (Master's equivalent) in Musicology at Karl-Franzens-University Graz (2000-2005) Doktoratsstudium (PhD) in Musicology at Karl-Franzens-University Graz (2005-2009), specializing in Systematic Musicology with Historical Musicology as secondary focus Dissertation: 'Sound und Image. Eine experimentelle Untersuchung zum Einfluss von Klangqualitäten auf die Wahrnehmung eines Produktimages im Kontext von Fernsehwerbung.' Flath's research program centers on transdisciplinary event research, examining the societal and cultural-political dimensions of event and cultural management. She investigates co-creation and participation processes in digital network media contexts and approaches music business research as music(business)culture research. Her methodology often incorporates innovative approaches like 'Sound Sculpting' to explore sensory experiences and cultural meaning. Her recent work increasingly addresses sustainability challenges in cultural contexts, reflecting her leadership in projects examining sustainable practices in cultural events and venues. Her scholarly output reveals a strong trajectory toward transdisciplinary frameworks that integrate cultural studies, musicology, and sustainability science. She examines the evolving relationship between pop culture, digital media, and event management, with particular attention to how cultural venues can adapt to ecological challenges. The recurring theme across her work is the exploration of how cultural practices intersect with economic structures in popular music contexts, often focusing on participation, accessibility, and sustainable development. Prof. Flath leads significant research initiatives including 'NachhaltigkeitsKulturOWL' (2024-2027), developing innovative sustainability strategies for the cultural event industry in East Westphalia-Lippe, and 'Datenraum Kultur' (2022-2025), focusing on networked cultural platforms. She previously directed the BMBF project 'kulturPreis' (2019-2022), which examined innovative pricing concepts to increase cultural participation. As Managing Director of C:POP, she oversees a transdisciplinary research center dedicated to studying popular music cultures and creative economies. Her leadership extends to university committees including the Commission for Teaching, Studies and Quality Management, and she serves on advisory boards for multiple research projects and academic journals in popular music studies, demonstrating her significant influence in both academic administration and cultural research.

Matt CastleView profile

Researcher

• Modelling for Food Security
• Plant Disease Modelling
• Infectious Diseases and Food Security
• +7 more

Dr. Matt Castle is a Researcher affiliated with the University of Cambridge , specializing in interdisciplinary approaches to food security and plant sciences. He serves as the Head of Bioinformatics Training and Head of PSLS Biostatistics Initiative within the Department of Plant Sciences . His work spans multiple domains, including plant disease modelling, infectious disease dynamics, and global governance of food systems. Research Themes: Modelling for Food Security, Plant Disease Modelling, Food Landscapes, Political Economy of Hunger His recent publications highlight expertise in ecological and agricultural modelling, with a focus on: Aflatoxin contamination in maize Urban forest pest dynamics Climate-driven range expansions Size-structured ecosystem resilience While his work intersects with food supply chains, land resources, and health, no specific scientific awards or student advisement details were listed in available public records.

Pengpeng HuView profile

Senior Lecturer

• Fashion Technology
• Geometric Deep Learning
• 3D Human Body Reconstruction
• +5 more

Dr Pengpeng Hu is a Senior Lecturer in Fashion Technology at the Department of Materials, The University of Manchester, UK. His research focuses on geometric deep learning, 3D human body reconstruction, point cloud processing, and smart textiles, bridging fashion technology with biomedical and engineering applications. Associate Editor: IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Automation Science and Engineering Academic Editor: PLOS ONE Editorial Board Member: Scientific Reports Programme Chair: 25th UK Workshop on Computational Intelligence Area Chair: 35th British Machine Vision Conference His work advances vision-based measurement systems, wearable technology, and 3D scanning for clothing and healthcare. Recent publications include innovations in MXene-based electronic textiles, 4D hand measurement extraction, and anthropometric analysis from depth images. Recipient of the Emerald Literati Award for an outstanding paper in 2019 Dr Hu accepts self-funded PhD students in areas like 3D human reconstruction, point cloud processing, and smart textiles. His editorial roles and conference leadership highlight his influence in computational intelligence and machine vision communities.

• Crowdsourcing
• Human-Computer Interaction
• Digital Health
• +7 more

Simo Hosio is an Academy Research Fellow (2022-2027) and Professor of Computer Science and Engineering at University of Oulu's Center for Ubiquitous Computing, where he leads the Crowd Computing Research Group. He also maintains a visiting position at University of Tokyo, Japan. Having graduated as the first Finnish scholar under Microsoft Research Cambridge's Ph.D. scholarship program, he has published over 150 peer-reviewed scientific articles spanning two decades of research. Hosio's research spans three primary domains: crowdsourcing methodologies, human-computer interaction, and digital health applications. His work pioneers novel approaches to online labor markets, investigates the suitability of crowdsourcing for diverse applications, and explores HCI aspects of digital health solutions for chronic conditions. His research group, founded in 2020, has secured nearly two million USD in funding, demonstrating significant research impact and recognition. Analysis of Hosio's recent publications reveals a strong trend toward interdisciplinary research at the intersection of crowdsourcing, healthcare technology, and emerging AI systems. His work increasingly focuses on practical applications of crowd computing in health contexts, with growing attention to mental health, women's health, and workplace well-being solutions. The integration of AI and machine learning techniques with traditional HCI approaches represents another significant trajectory in his recent scholarship. Distinguished Paper Award (2024) Best Paper Honourable Mention Award (2022) PMCJ Best Research Paper (awarded in 2024) Best Paper Award (2022) Best Full Paper Award (2015) Honorable Mention Award (2014) Best Paper Presentation award (2010) As an educator, Hosio has taught Human-Computer Interaction (2019-2025) to over 260 students in 2024, Social Computing (2018-2021) to approximately 60 students annually, and Applied Computing (2015-2018) to around 50 students each year. His research group's nearly two million USD in secured funding demonstrates significant grant acquisition success, supporting innovative work at the intersection of crowd computing, health technology, and human-centered AI systems. The Crowd Computing Research Group, founded by Hosio in 2020, represents a significant research infrastructure focused on advancing methodologies for crowd-powered systems. The group's work spans from fundamental research on crowd labor markets to applied projects in healthcare, workplace well-being, and social computing, demonstrating a strong commitment to both theoretical advancement and practical impact.

Montek SinghView profile

Associate Professor

• High-performance digital systems
• Low-power digital systems
• Asynchronous circuits
• +5 more

Montek Singh serves as an Associate Professor and Associate Chair for Academic Affairs in the Department of Computer Science at the University of North Carolina at Chapel Hill. His research focuses on high-performance and energy-efficient digital systems with particular emphasis on asynchronous and mixed-timing circuit design. Dr. Singh received his Ph.D. in Computer Science from Columbia University in 2002 and his B.Tech. in Electrical Engineering from IIT Delhi, India, in 1993. His primary research interests span high-performance and low-power digital systems, with specialization in asynchronous or clockless and mixed-timing integrated chip design. His work encompasses circuit design methodologies, CAD tools for automated synthesis, analysis and optimization techniques. He has also explored applications in energy-efficient mobile graphics hardware, secure chip design for computer security, and design challenges in emerging computing technologies. His research has practical applications in industry, with work transferred to companies including IBM, Boeing, and Handshake Solutions. Analysis of Dr. Singh's publications reveals a strong focus on asynchronous circuit design spanning two decades. His work covers fundamental pipeline architectures (MOUSETRAP), high-speed asynchronous systems, latency-insensitive design methodologies, and practical applications in graphics hardware and mobile devices. The research demonstrates consistent innovation in making asynchronous design more practical for real-world implementation while addressing performance, power efficiency, and testing challenges. His notable scientific achievements include: Best Paper Award at the 6th IEEE Intl. Symp. on Adv. Res. in Async. Circ. and Syst. (ASYNC-2000) Best Paper Finalist at the 8th IEEE Intl. Symp. on Async. Circ. and Syst. (ASYNC-02) Dr. Singh has secured significant research funding including participation in the DARPA CLASS Program (led by Boeing) in 2005, where he collaborated with Philips/Handshake Solutions to develop an industrial-strength automated synthesis flow for high-speed asynchronous systems. His research has strong industry connections and practical applications, with technology transferred to major companies including IBM and Boeing. He has also organized major academic events such as the International Symposium on Asynchronous Circuits and Systems 2009 (ASYNC 2009) at UNC Chapel Hill. Dr. Singh leads research in asynchronous systems design with connections to industry partners and practical applications. His work has been featured in prominent media outlets including The New York Times, International Herald Tribune, and Technology Review Magazine, highlighting the significance of clockless design approaches as traditional synchronous design approaches face limitations.

Priyanko GuchaitView profile

Professor

• Organizational Behavior
• Error Management Culture
• Leadership
• +7 more

Priyanko Guchait is a tenured Full Professor and Program Director of the Doctorate in Global Hospitality Leadership (DGHL) at the Conrad N. Hilton College of Global Hospitality Leadership , University of Houston. His research focuses on organizational behavior, leadership, human resources, and service management in hospitality contexts, with over 75 peer-reviewed articles published. Education: B.E. in Mechanical Engineering, University of Pune, India M.S. in Hospitality Management, University of Missouri M.S. in Human Resources and Employment Relations Ph.D. in Hospitality Management, The Pennsylvania State University Research Interests include error management culture, psychological safety, service recovery performance, leader behavioral integrity, and AI’s impact on hospitality workers’ mental health. His work examines shame, forgiveness climate, and team dynamics in service environments. Article Trends show a focus on multi-level error management, human-robot collaboration in service recovery, diversity inclusion climates, and cross-cultural leadership studies. Recent papers explore AI ethics, pandemic response strategies, and emotional labor in hospitality roles. Awards & Honors Stephen Rushmore/HVS Research Excellence Award (2023, 2015) Donald Greenaway Excellence in Research, Teaching, and Service Award (2022) Best Paper Award, The Service Industries Journal (2023) ICHRIE Faculty Collegiality Award (2021) ICHRIE McCool Breakthrough Award (2021) Honored as 50-in-5 Scholar (2021) Provost’s Excellence Award (2015) Best Reviewer Awards (IJCHM 2016-2017) Committee & Editorial Roles include Associate Editor of IJCHM, Coordinating Editor of IJHM, and leadership positions at ICHRIE (President 2020-2021, Vice President 2019-2020). He has served on university curriculum, research, and Ph.D. selection committees.

• Student participation in university teaching
• Expressive writing in career guidance
• Affectivity in student learning processes
• +3 more

Alessandro Di Vita is an Associate Professor at the Department of Psychological, Pedagogical, Physical Exercise and Training Sciences, School of Medicine and Surgery, Università degli Studi di Palermo (UNIPA). His work centers on educational psychology, career orientation, and pedagogical methodologies for adolescents and university students. Research Interests: Expressive writing for life planning, self-efficacy development, performance anxiety management, peer tutoring, and intercultural education. Key Projects: «Telemaco» (remote peer tutoring), «FOrCe» (career guidance interventions), and «FOrP» (school-university transition). Collaborations: Worked with international institutions like Universidad Austral (Argentina) and Universidad de Estudios de Palermo (Italy). His publications from 2007–2025 reflect a consistent focus on adolescent relationships, educational reform, and digital pedagogy. He has contributed to validation studies for psychological scales like the Worry Emotionality-Junior (WE-J) and developed methodologies such as «SeCo» for post-diploma decision-making. Alessandro also emphasizes Student Voice in educational processes, promoting active participation and resource utilization. Recent works include international comparative studies on peer tutoring and training programs for secondary school teachers.

Mihai SanduleanuView profile

Associate Professor

• RF Integrated Circuit Design
• Analog Mixed-Signal Integrated Circuit Design
• Wireless Communication Circuits
• +7 more

Dr. Mihai Sanduleanu is an Associate Professor of Electrical Engineering at Khalifa University of Science and Technology. He has extensive industry experience from Philips Semiconductors, Philips Research Eindhoven, IMEC, and IBM T.J. Watson Research Center, combined with academic appointments including Adjunct Professor at Eindhoven University of Technology. His educational background includes: MSc from Gh. Asachi Technical University of Iasi, Romania MEE from Technical University Eindhoven, The Netherlands PhD from University of Twente, The Netherlands Dr. Sanduleanu's research focuses on cutting-edge integrated circuit design across the frequency spectrum from RF to THz. His work spans wireless transceiver design, analog/mixed-signal circuits, high-speed communication systems, and innovative applications in healthcare monitoring. He has pioneered developments in mm-wave imaging for skin cancer detection, ultra-low power radios, and high-performance analog-to-digital converters. His scholarly contributions include: 53 granted US patents Over 104 papers published in IEEE Journals and Conferences 9 books or book chapters Citation h-index of 22 and i10-index of 46 Dr. Sanduleanu has received significant recognition including multiple Philips and IBM Research Awards. He serves on the Editorial Board of the Analog Integrated Circuits and Signal Processing Journal and has previously been Associate Editor for IEEE Transactions on Circuits and Systems. He has successfully mentored 21 MSc students and 7 PhD students to graduation. Currently, he advises PhD student Ahmed Mahdy and MSc student Aaron Zerai Tekleab. His research is supported through affiliations with the Center for Cyber-Physical Systems, with current projects focused on vital signs monitoring using 160GHz radar and non-invasive glucose detection using 120GHz sub-mm wave technology.

François GouletteView profile

Professor

• 3D Point Cloud Processing
• LiDAR Perception
• Autonomous Systems
• +7 more

François Goulette is a Professor and Deputy Director of the Computer Science and Systems Engineering Unit (U2IS) at ENSTA Paris, part of Institut Polytechnique de Paris. His research focuses on 3D point cloud processing, LiDAR perception, and autonomous systems within the Robotics Center (CAOR). His primary research interests lie in 3D point cloud processing , LiDAR perception , and autonomous systems . His work spans fundamental algorithm development to practical applications in autonomous driving, cultural heritage digitization, and robotics. He has made significant contributions to domain generalization of LiDAR perception, semantic segmentation of 3D point clouds, and point cloud registration techniques. The analysis of his recent publications reveals a strong focus on domain generalization for LiDAR perception systems, with multiple papers addressing challenges in 3D semantic segmentation across different environments. His work combines multi-scale architectures , unsupervised learning , and dataset creation to advance the state-of-the-art in autonomous systems perception. The research spans both theoretical algorithm development and practical applications in urban environments. François Goulette leads research activities within the Robotics Center (CAOR) at ENSTA Paris. His team develops advanced techniques for 3D environment understanding, with applications in autonomous vehicles, cultural heritage preservation, and industrial robotics. The research combines computer vision, machine learning, and robotics to solve challenging problems in 3D perception and scene understanding.

Bogdan IancuView profile

Lecturer

• Artificial Intelligence
• Computer Vision
• Maritime Object Detection
• +5 more

Bogdan Iancu is a University Lecturer in the Department of Information Technology at the Faculty of Science and Engineering, Åbo Akademi University. He holds a PhD and Docent qualification in Computer Science, with extensive expertise in artificial intelligence and computer vision applications, particularly in the maritime domain. His academic career spans numerous research projects and publications that bridge theoretical AI concepts with practical industry applications. Dr. Iancu's research focuses on AI applications in maritime technology, with special emphasis on object detection systems, security challenges in AI models, and sustainable technological solutions. He has developed benchmark datasets like ABOships and ABOships-PLUS that have become valuable resources for researchers in maritime computer vision. His work addresses critical challenges including adversarial attacks on object detection systems, as evidenced by his 2025 publication on TOG Adversarial Attacks in YOLO Models. The analysis of his recent publications reveals a clear progression from foundational dataset creation to advanced security analysis and neurosymbolic approaches that combine neural networks with symbolic reasoning. His research shows increasing sophistication in addressing real-world challenges in maritime AI systems, with particular attention to robustness, security, and practical implementation. Dr. Iancu actively participates in numerous research projects including EDISS (Engineering of Data-intensive Intelligent Software Systems), SMARTER (Sea4Value Smart Terminals), and DECATRIP (Decarbonizing Transport Corridors). These projects involve collaboration with industry partners across Finland and Europe, focusing on applying AI to solve real-world challenges in maritime transport, digitalization, and sustainability. He has contributed to the academic community through teaching courses in Artificial Intelligence, Data Science, and Graph Algorithms, and through active participation in the Finnish Artificial Intelligence Society. His work aligns with UN Sustainable Development Goals, particularly those related to industry innovation, infrastructure, and climate action through projects like DECATRIP that focus on decarbonizing transport corridors.

• Channel decoders
• Circuits for communications
• Cryptography
• +8 more

Guido Masera is a Full Professor at the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin, where he has been actively involved in teaching and research for over two decades. He serves as a Member of the Board of Directors, Member of the GEDI Observatory for Gender Equality, Diversity and Inclusion, and Member of the Permanent University Observatory for monitoring the academic supply chain. His research interests span across channel decoders, circuits for communications, cryptography, deep learning, digital integrated circuits, field programmable gate arrays (FPGA), and hardware design. His work focuses on VLSI architectures for image and video coding, digital architectures for error correcting codes, application specific approximate computing, VLSI architectures for machine learning, digital architectures for bio-inspired processing, digital architectures for post-quantum cryptography, bio-inspired electronics for robotics and biomedical applications, RISC-V extensions and hardware accelerators, and circuit architectures for efficient machine learning and artificial intelligence. His recent publications (2025) demonstrate a strong focus on RISC-V architecture, particularly in the context of cryptographic implementations, hardware security, and post-quantum cryptography. His research group VLSILAB is actively engaged in cutting-edge research in hardware security, efficient processor design, and specialized computing architectures. Among his notable recognitions are the Premio Francesco Carassa awarded by the Telecommunications and Information Technologies Group Association (gtti) in 2010, and his recognition as a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) since 2007. He also serves as an Associate Editor for several prestigious journals including ELECTRONICS (2019-present), IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS (2015-2019), and IET CIRCUITS, DEVICES & SYSTEMS (2013-2016). Professor Masera has advised numerous PhD students working on advanced topics in VLSI design, post-quantum cryptography, hardware accelerators, and machine learning implementations. His current research projects include ISOLDE (2023-2026) and TRISTAN (2022-2025), both EU-funded projects focused on RISC-V technology and domain-specific ecosystems. He leads the VLSILAB research group at the Department of Electronics and Telecommunications, which focuses on cutting-edge research in VLSI architectures, hardware security, and specialized computing systems. The group collaborates with industry partners and participates in major European research initiatives.

• Hardware Security
• Embedded Systems
• Energy-Efficient Computing
• +5 more

Mahdi Fazeli is an Associate Professor at the School of Information Technology, Halmstad University, Sweden, specializing in hardware security and trust, energy-efficient computing, and embedded and cyber-physical systems. His academic journey began with a Ph.D. in Computer Engineering from Sharif University of Technology, Iran, in 2011. His career progression includes positions as Associate Professor at Bogazici University (2019-2021) and Iran University of Science and Technology (2016-2019), and Assistant Professor at the same institution (2011-2016). His research interests focus on hardware security and trust, reliable VLSI circuits and systems, energy-efficient computing, and dependable embedded systems. His work bridges the gap between theoretical security concepts and practical implementations in real-world systems, particularly in IoT and embedded environments. He has established himself as a leading researcher in Physical Unclonable Functions (PUFs), hardware trojans detection, and energy-efficient security solutions for resource-constrained devices. His publication record shows a clear progression and deepening expertise in hardware security, with recent work focusing on cutting-edge applications in edge computing, vehicular networks, and IoT security. His 2023-2025 publications demonstrate significant contributions to magnetic memory-based security primitives, anomaly detection systems, and energy-efficient security mechanisms. Throughout his career, Fazeli has led multiple research initiatives including the Dependable Systems and Architecture Lab (DSA) and the Networked and Embedded Systems Lab at Iran University of Science and Technology. His leadership extends to heading the Hardware Group and serving as Vice Chair for Educational Affairs, demonstrating his commitment to both research excellence and academic administration.

Leila De FlorianiView profile

Professor

• Geometric Modeling
• Data Visualization
• Spatial Data Representation and Processing
• +6 more

Leila De Floriani is a Professor at the University of Maryland, with appointments in the Department of Geographical Sciences and the University of Maryland Institute for Advanced Computer Studies (UMIACS). She previously served as a professor at the University of Genova (Italy) since 1990, where she developed Italy's first undergraduate and graduate curricula in computer graphics and directed the Ph.D. program in Computer Science for eight years. Her professional activities include serving as the 2020 President of the IEEE Computer Society and currently as IEEE Division VIII Director for 2023-24. Professor De Floriani's research spans geometric modeling, data visualization, spatial data representation and processing, computer graphics, shape analysis, and topological data analysis. Her work focuses on developing mathematical models and algorithms for representing, analyzing, and visualizing complex spatial data, particularly through hierarchical models, mesh-based representations, and topology-based approaches. Her research group, the GeoVis group, investigates applications in terrain modeling, environmental data analysis, and forest structure mapping using LiDAR technology. Analysis of her recent publications reveals a strong focus on terrain representation and processing, with increasing emphasis on topological data analysis, machine learning integration, and efficient algorithms for large-scale spatial data. Her work bridges theoretical foundations in computational topology with practical applications in geospatial sciences, demonstrating consistent innovation in data structures and visualization techniques. Scientific Awards & Recognitions Fellow of IEEE (2016) for contributions to geometric modeling and scientific visualization Fellow of International Association for Pattern Recognition (IAPR) (1998) for contributions to geometric modeling and image analysis Fellow of Eurographics Association (2020) for outstanding contributions to computer graphics and visualization Pioneer of Solid Modeling Association (2017) for seminal work in solid and feature-based modeling Inducted Member of IEEE Visualization Academy (2020) IEEE Computer Society Golden Medal Award (2018) Inducted Member of IEEE Honor Society Eta Kappa Nu (2019) Multiple best paper awards at major conferences including Shape Modeling International (2015), IEEE/EG Symposium on Volume and Point-Based Graphics (2008), and ACM SIGSPATIAL (2008) Professor De Floriani has successfully advised numerous PhD students including Xin Xu, Yunting Song, and Noel Dyer, whose recent dissertations focused on topology-based individual tree mapping, efficient terrain analysis, and bathymetric data visualization respectively. Her research has been funded by prestigious agencies including the National Science Foundation, NASA, and the European Commission. As the leader of the UMD GeoVis group, she oversees a research program that develops open-source tools for spatial data analysis available on GitHub, with current projects focusing on forest point cloud processing and topology-based geospatial data visualization. The GeoVis group, affiliated with the Department of Geographical Sciences, UMIACS, and the Center for Geospatial Information Sciences, maintains a strong collaborative environment with ongoing projects in geometric modeling, spatial data structures, topology-based machine learning, and mesh-based terrain modeling. The group has received recent funding from NASA's HPOSS program for developing an open-source library for forest point cloud processing based on topological data analysis.

• Space Robotics
• Control Theory
• Computer Vision
• +4 more

Pedro Roque is a Postdoctoral Researcher at KTH Royal Institute of Technology in Stockholm, affiliated with the Wallenberg AI, Autonomous Systems and Software Program (WASP) and associated with the Division of Decision and Control Systems (DCS). He obtained his Ph.D. in 2024 from the same division under the supervision of Prof. Dimos Dimarogonas, Prof. Mikael Johansson, and Prof. Jana Tumova. His research focuses on practically applicable theoretical results in robotics and control, with emphasis on space and aerial systems. Dr. Roque is particularly interested in developing algorithms that directly contribute to system performance and enhanced capabilities. He currently leads the setup of a Space Robotics Laboratory at KTH, associated with the Space Center and the WASP NEST DISCOWER project. He is an advocate for open-source software and hardware, contributing to NASA Astrobee and PX4 projects, with his research tested on the International Space Station and indoor flight arenas. Dr. Roque's work demonstrates a clear progression from theoretical foundations to practical implementation in space environments. His recent publications show an increasing focus on multi-agent coordination in microgravity, with significant contributions to model predictive control for space robotics applications. The research spans from fundamental control theory to complete system implementation, reflecting his commitment to bridging theory and practice. ICRA 2022 Outstanding Coordination Award for work on decentralized model predictive control for collaborative UAV bar transportation Dr. Roque actively mentors Master's students in Space Robotics, Control, and Vision, with supervision details available on his personal website. He has collaborated extensively with NASA Astrobee and PX4 projects, and his DISCOWER project involves collaboration with 3 Ph.D. students, 2 Master's students, 6 Professors, and one Post-doc. He also completed a 4-month internship at JPL within the Maritime and Multi-Agent Systems group. He leads the Space Robotics Laboratory at KTH, associated with the Space Center and the WASP NEST DISCOWER project, which has already demonstrated capabilities to Digital Futures, SAAB AB, SAAB Inc., and Purdue scholars. The laboratory focuses on weightless robotics, collaborative robotics (Space Cobot), and exploration robotics (MoonHopper), with practical testing on the International Space Station.

• Learning Theory
• Neural Networks
• Deep Learning
• +6 more

Professor Dingxuan Zhou is a distinguished academic serving as Professor and Head of School of Mathematics and Statistics at The University of Sydney, joining the institution on August 29, 2022. He is also a member of The Net Zero Institute and has held significant editorial positions, including editor-in-chief of the journal "Analysis and Application" of "Mathematical Foundations of Computing" and serving on the editorial boards of over ten international journals. Educational Background: BSc in Mathematics from Zhejiang University, China (1988) PhD in Mathematics from Zhejiang University, China (1991) Professor Zhou's research spans learning theory, neural networks, wavelet analysis, and approximation theory, with his current focus on the theory of deep learning. His work aligns with the Faculty of Science Research Strengths in Complex Systems, Precision and Digital Health, Data and Decisions, and National Security. His research demonstrates a consistent progression from foundational mathematical theory to cutting-edge applications in machine learning and artificial intelligence, with particular emphasis on understanding the theoretical underpinnings of neural networks and deep learning systems. His extensive publication record reveals a strong trend toward distributed learning frameworks, approximation theory for neural networks, and the mathematical foundations of deep learning. Recent work focuses on federated learning, transformers, physics-informed neural networks, and the theoretical analysis of over-parameterized networks, reflecting the evolving landscape of machine learning research with increasing emphasis on theoretical guarantees and practical applications. Scientific Awards: Humboldt Research Fellowship (1993) Fund for Distinguished Young Scholars from the National Science Foundation of China (2005) Highly-cited Researcher by Thomson Reuters/Clarivate Analytics (2014-17) World's Top 2% Scientist by Stanford University (2021, 2022, 2023) Professor Zhou has demonstrated exceptional leadership in research and mentorship, having conducted over 40 research grants as Principal Investigator, supervised more than 20 PhD students, and co-organized over 20 international conferences. His collaborative approach is evident in his extensive co-authorship network across multiple institutions globally. He has also served in significant administrative roles including Head of Department of Mathematics (2006-12), Associate Dean of School of Data Science (2018-22), and Director of the Liu Bie Ju Centre for Mathematical Sciences (2019-22) at City University of Hong Kong.