Find Academic Supervisors

Bo BernhardssonView profile

Professor

• Automatic Control
• Control Theory
• Modeling and Control of Uncertain Systems
• +17 more

Bo Bernhardsson is a Professor in Automatic Control at the Department of Automatic Control, Faculty of Engineering (LTH), Lund University. He has been a full-time professor at Lund since 2010, following a decade (2001–2010) as an Expert in Mobile System Design and Optimization at Ericsson. He is affiliated with major research initiatives including ELLIIT (Excellence Center in Information Technology), LCCC (Lund Center for Control of Complex Engineering Systems), and WASP-AS (Wallenberg AI, Autonomous Systems and Software research school), where he has played a leadership role since 2016. His research focuses on modeling and control of uncertain and large-scale systems, with applications spanning industrial automation, mobile communications, particle accelerators, biomedical systems, and navigation technologies. He integrates theoretical control methods with practical implementations, particularly under constraints such as communication limitations, noise, and delays. His recent publications reveal a strong trend in networked control, communication-constrained estimation, and optimization-based control design. The works span theoretical advances in signal estimation under SNR constraints, event-based and stochastic control, and practical applications like IMU-radio fusion for navigation and RF field control in particle accelerators. Keywords include Control Theory, Communication Systems, Optimization, Signal Processing, and Networked Control , with subfields such as encoder-decoder co-design, virtual antenna arrays, and dynamic programming for time-delay systems. PhD in Control, Lund University, 1992 Professor in Automatic Control, Lund University, since 1999 Expert, Mobile Systems, Ericsson, 2001–2010 Bo Bernhardsson has supervised over 20 PhD and licentiate students, including Jacob Bergstedt (immune system modeling), Anders Mannesson (navigation and radio), and Erik Johannesson (control under communication constraints). His research has been funded by major entities such as the European Spallation Source and the Wallenberg Foundation. He teaches advanced courses in Linear Systems, Convex Optimization, and Robust Control, and has contributed significantly to both academic and industrial advancements in control engineering. He leads and collaborates on interdisciplinary projects involving real-time control, autonomous systems, and machine learning, often in partnership with industry and international research centers. His work in the RobotLab at LTH and on cloud-based control systems highlights his engagement with emerging technologies.

• Control Theory
• Real-Time Systems
• Embedded Systems
• +7 more

Anton Cervin is a Senior Lecturer at the Department of Automatic Control, Faculty of Engineering, Lund University. He is currently on leave of duty but remains actively involved in research and supervision. His work spans real-time systems, event-based control, cloud computing, and embedded systems, with strong ties to industrial applications and sustainable technologies. His research interests include: Event-Based and Stochastic Control Networked and Embedded Control Systems Cloud-Based Control and Resource Management Real-Time Scheduling and Performance Analysis Digital Twins and Fluid Modeling in Cloud Environments He has led major research projects funded by the Swedish Research Council, WASP, and ELLIIT, focusing on robust and secure cloud control, self-adaptive systems, and distributed learning. His software tools—TrueTime, Jitterbug, and TinyRealTime—are widely used in academia and industry for simulating and analyzing real-time control systems. The most recent publications highlight a shift toward intelligent, adaptive control using reinforcement learning, fluid modeling for microservices, and timing-robust cloud control—indicating a strong trend in merging traditional control theory with modern computing paradigms. His scientific contributions have been recognized with multiple Best Paper Awards: Best Paper Award - ECRTS 2021 Best Paper Award - RTNS 2016 Best Paper Award - RTCSA 2004 Best Paper Award - ECRTS 2003 Best Student Paper Award - RTCSA 1999 Anton Cervin has supervised numerous PhD students, including Max Nyberg Carlsson, Nils Vreman, and Claudio Mandrioli, and has served in key academic roles such as Director of PhD Studies and Deputy Head of Department. He has also led educational initiatives like doctoral study circles on programming languages and the history of control. He is affiliated with research environments such as WASP and ELLIIT and contributes to UN Sustainable Development Goals through advancements in smart systems and sustainable automation.

David OhlinView profile

Part-Time Lecturer

• Optimal Control
• Control of Large-Scale Networks
• Social Networks
• +4 more

David Ohlin is a PhD student and part-time lecturer in Automatic Control at Lund University's Faculty of Engineering (LTH), actively contributing to the Wallenberg AI, Autonomous Systems and Software Program (WASP) since 2021. His position bridges advanced doctoral research with instructional responsibilities across multiple control theory courses. He earned his MSc in Engineering Physics in 2021 with a thesis focused on machine learning applications for EEG signal interpretation, establishing his interdisciplinary approach at the intersection of control systems and biomedical engineering. His educational trajectory demonstrates a clear progression from foundational physics to specialized control theory expertise. Ohlin's research centers on optimal control methodologies for large-scale networked systems, with innovative applications to social network dynamics and opinion modeling. His work on graph search methods for controlling positive systems and nonlinear synchronization models represents significant contributions to both theoretical control frameworks and their real-world implementations in social dynamics. This dual focus on mathematical rigor and practical application characterizes his scholarly approach. His publication pattern reveals a growing expertise in network control systems, with recent work examining consensus formation in polarized networks, linear cost optimization, and heuristic search algorithms. These publications collectively demonstrate his ability to translate complex control theory concepts into solutions for networked social systems. Teaching since Fall 2021: Non-linear control, Learning-based control, and Network dynamics courses Research collaborations with prominent scholars including Anders Rantzer and Emma Tegling Active participant in WASP, Sweden's premier AI and autonomous systems initiative

Julie WallView profile

Professor

• Artificial Intelligence
• Advanced Computing
• Deep Learning
• +12 more

Professor Julie Wall is a faculty member at the University of West London, serving as Professor of AI and Advanced Computing in the School of Computing and Engineering. She is actively engaged in research, teaching, and professional service, including her role as an expert at the British Standards Institution (BSI) in the domain of artificial intelligence. Research Interests: Julie Wall's research is centered on the design and application of intelligent systems for processing and modeling temporal data, particularly in speech and language. She leverages neural network architectures—ranging from biologically inspired models to computationally efficient deep learning systems—to analyze diverse data types such as audio, video, images, tabular data, and 3D features. Her work extends to developing production-grade deep learning and natural language understanding systems for immersive environments like virtual and augmented reality. Publications and Research Trends: Her body of work, comprising over 50 high-quality papers and multiple patents, reflects a strong trajectory in AI systems that integrate multimodal data with temporal dynamics. The research spans core areas of machine learning, natural language processing, and applied AI, with increasing focus on real-world deployment, efficiency, and intelligent interaction in extended reality platforms. Scientific Awards: US Patent UK Patent Advising and Grants: Julie Wall supervises research students across disciplines including forensic science and artificial intelligence. She contributes extensively to academic programs, teaching courses such as BSc and MSc in Computer Science, Artificial Intelligence, Data Science, and specialized AI programs in cybercrime and criminal justice. While specific grant details are not listed, her patent holdings and publication volume suggest sustained research funding and project leadership. Labs and Teams: As a leading researcher in AI and advanced computing, she is likely involved in or leads research groups focused on intelligent systems, deep learning, and multimodal AI at the University of West London, though specific lab names are not mentioned in the text.

• Computational Electromagnetics
• Antenna Design
• Electromagnetic Scattering
• +3 more

Eliseo García García is a Professor at the University of Alcalá, affiliated with the Department of Automatic Control and Systems Engineering. He holds a Ph.D. from the University of Alcalá, awarded in 2005 for his thesis on computational electromagnetics. His primary research focuses on computational methods for electromagnetic analysis, including the development of efficient algorithms like the Characteristic Basis Function Method (CBFM) and hybrid techniques with the Multilevel Fast Multipole Algorithm (MLFMA). He is a core member of the GEC (Computational Electromagnetic Group), where he explores geophysical applications, antenna design, and high-frequency electromagnetic problems. His research interests bridge theoretical and applied electromagnetics, with particular emphasis on reducing computational costs in solving large-scale EM problems. Notable contributions include advancements in radar cross-section (RCS) computation, radome structure analysis, and geothermal exploration frameworks using hydrogeophysical methods. He has also published extensively on numerical techniques for antenna trajectory simulations and sparse matrix preconditioning. Eliseo’s work spans multiple disciplines, including aerospace engineering, environmental science, and software development, as evidenced by his contributions to Altair Feko 2023 updates. Despite no listed awards, his prolific publication record (over 70 articles from 2013–2024) underscores his active role in advancing computational electromagnetics and its interdisciplinary applications. His advising and grants section remains unreported, but his involvement in collaborative projects is implied through frequent co-authorships and institutional affiliations. He leads the GEC lab, focusing on cutting-edge computational tools and their practical deployment in real-world engineering challenges.

Omar AL-BuraikiView profile

Professor

• AI/ML Robotic Vision
• Autonomous Systems
• Automatic Control
• +5 more

Omar AL-Buraiki is a Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo. He specializes in Robotics Automation, Machine Intelligence Algorithms, and Autonomous Systems, with over 12 years of research experience across Canadian and international institutions. His work focuses on developing industrially oriented solutions for defense, robotics, and telecommunications sectors. Education: Ph.D., Electrical and Computer Engineering, University of Ottawa M.A.Sc., Systems Engineering, King Fahad University B.Sc., Electronics and Communications Engineering, Hadhramout University Research Interests: His research spans AI/ML Robotic Vision, Autonomous Systems, Automatic Control, Intelligent Automation, and Multi-Robot Coordination. He has pioneered nonlinear control systems, task allocation algorithms, and machine learning-driven robotic vision solutions, notably through his leadership of the SMART Lab during his PhD. Publications & Trends: His 20+ publications emphasize probabilistic task allocation, sensor fusion, and adaptive control in robotics. Recent work (2023–2025) focuses on slip-compensated visual-inertial odometry and heterogeneous robotic systems under actuator delays. Earlier papers (2016–2020) established foundational methods for specialized agent task assignment in swarm robotics. Achievements: Secured a USPTO patent for robotics automation technology Over 20 peer-reviewed articles and 12+ conference presentations Teaching & Advising: Instructor for courses on control systems, robotics, and AI-based vision at both undergraduate and postgraduate levels Developed specialized courses like Autonomous Vehicles Navigation and Control Labs & Teams: Former leader of the SMART Lab (University of Ottawa), currently active in robotics research at the University of Waterloo’s Mechanical and Mechatronics Engineering Department.

Raffaele RossiView profile

Professor

• Macroeconomics
• Public Finance
• Applied Time Series Econometrics
• +4 more

Raffaele Rossi is a Professor of Economics in the Department of Economics at the Birmingham Business School, University of Birmingham , where he also serves as Director of the MSc Money, Banking and Finance Programme. He joined the university in July 2023, having previously held the position of Reader at the University of Manchester. PhD, University of Glasgow MSc, University of Edinburgh BSc, University of Milano-Bicocca His research lies at the intersection of macroeconomics, public finance, and applied time series econometrics , with additional interests in inequality, household finance, monetary policy, and fiscal policy. His work often employs structural estimation and dynamic macroeconomic modeling to analyze tax reforms, fiscal-monetary interactions, and economic shocks. The recent publications of Professor Rossi reveal a strong focus on the long-term effects of taxation, particularly marginal and consumption tax changes, using structural models. His work also addresses contemporary macroeconomic challenges such as the economic impacts of the COVID-19 pandemic and uncertainty. A recurring theme is the design and evaluation of optimal fiscal and monetary policy rules in complex economic environments, often incorporating habits, rule-of-thumb consumers, and sectoral heterogeneity. While no formal awards are listed in the provided texts, his publications in leading journals such as the Journal of Monetary Economics , American Economic Journal: Economic Policy , and European Economic Review attest to the high caliber of his research. His work demonstrates a consistent commitment to rigorous empirical and theoretical analysis of critical policy issues in modern macroeconomics. Professor Rossi supervises research in macroeconomic policy and econometrics, though specific student names are not listed. He is actively engaged in ongoing research, including working papers on taxing consumption in unequal economies and housing credit supply shocks. He is based at the University of Birmingham, contributing to the research and teaching mission of the Department of Economics.

Miljana L. MilićView profile

Professor

• Electronics
• VLSI Design
• Analog and Digital Circuit Diagnosis
• +7 more

Miljana L. Milić is a Full Professor at the Faculty of Electronics, University of Niš, Serbia, Department of Electronics. She has been an integral part of this institution since earning her degrees and advancing through academic ranks, culminating in her appointment as full professor in 2024. Education: PhD in Electronics, Faculty of Electronics, University of Niš (2009) Master’s in Electronics, Faculty of Electronics, University of Niš (2005) Bachelor’s in Electronics, Faculty of Electronics, University of Niš (2001) Her research interests span a broad spectrum of electronics engineering, with emphasis on VLSI design, analog and digital circuit diagnosis, cryptographic hardware security, timing analysis under aging, and performance optimization in neural prediction systems. She applies simulation, statistical methods, and AI techniques to solve complex problems in electronic systems design and reliability. The analysis of her recent publications reveals a strong focus on hardware-level innovation, including secure cryptographic cells, fault diagnosis in analog circuits, performance modeling under fading and shadowing, and timing degradation in VLSI systems. Her work bridges theoretical analysis with practical implementation in electronic design and communication systems. She leads the Laboratory for Design of Electronic Processes, Circuits and Automatic Control Systems, and is currently involved in one national research project. Her contributions include over 10 journal publications in high-impact venues. Scientific Contributions: Head of Laboratory for Design of Electronic Processes, Circuits and Automatic Control Systems Active participant in national research projects Author/co-author of 10+ journal papers with impact factor She mentors students through research supervision and contributes to academic leadership within her department. Her work continues to influence both academic research and practical applications in electronic systems engineering.

• Control Engineering
• Automatic Control
• Sliding Mode Control
• +3 more

Staniša Perić is an Associate Professor at the Department of Automation, Faculty of Electronic Engineering, University of Niš, Serbia. Elected to this position in 2023, he specializes in control systems and signal processing with 21 impact-factor journal publications to his name. Education: PhD in Systems Control, Faculty of Electronic Engineering, University of Niš (2016) Diploma in Automation, Faculty of Electronic Engineering, University of Niš (2009) Research Focus: Dr. Perić's work bridges Control Engineering and Signal Processing , with groundbreaking contributions in Sliding Mode Control for Automotive Systems and Advanced FIR Filter Design . His research integrates Orthogonal Endocrine Neural Networks for real-time control applications, particularly in Anti-lock Braking Systems (ABS), while developing ultra-selective multiplierless filters for hardware-efficient signal processing. Publication Analysis: His 11 representative publications (2010-2017) reveal a clear trajectory: early work focused on orthogonal function applications in antenna systems and filter design, evolving into neural network-enhanced sliding mode control for automotive safety systems. The 2015-2017 period shows intensive development of biologically inspired neural networks for dynamic system modeling and time-series forecasting. Research Engagement: National Research Projects: 2 International Research Projects: 4 Collaborative Environment: As a core member of the Department of Automation, Dr. Perić contributes to research groups specializing in intelligent control systems and advanced signal processing. His work directly supports the faculty's strategic focus on automotive electronics and embedded control solutions, with experimental validation conducted through university-industry partnerships in automotive safety systems.

Boris JutziView profile

Professor

• Active Optical Sensors
• Computer Vision
• Laser Scanning
• +7 more

Prof. Dr. Boris Jutzi is a leading academic in photogrammetry and remote sensing, currently serving as Professor at Karlsruhe Institute of Technology (KIT) and acting head of the Chair of Photogrammetry and Remote Sensing at Technical University of Munich (TUM). His research focuses on active optical sensors, computer vision, laser scanning, and 3D reconstruction techniques. He holds a diploma in electrical engineering from University of Kaiserslautern, a PhD from TUM, and venia legendi from KIT. Affiliations: KIT Institute of Photogrammetry and Remote Sensing, TUM Chair of Photogrammetry and Remote Sensing Education: Diploma in Electrical Engineering (University of Kaiserslautern) Doctorate (TUM) Venia Legendi (KIT) His research interests include: Neural Radiance Fields (NeRF) for 3D reconstruction LiDAR technology and applications UAV-based remote sensing Geospatial data fusion Computer vision in environmental monitoring Awards: Faculty Teaching Award (2020) Best Paper Awards (2019, 2016, 2014, 2006) His work emphasizes novel sensor integration and automated scene analysis , with contributions to urban and environmental 3D modeling. Current projects include underwater scene reconstruction via NeRFs and large-scale digital twin datasets (e.g., TUM2TWIN).

Volker HeunView profile

Professor

• Algorithmic Bioinformatics
• Protein Folding
• Data Structures
• +4 more

Volker Heun is a Professor of Bioinformatics at Ludwig-Maximilians-Universität München (LMU), holding positions within the Faculty of Mathematics, Computer Science, and Statistics since 2003. He currently serves as Vice Dean of the faculty and holds various academic coordination roles, including Bioinformatics program coordination and ERASMUS coordination. His academic journey includes a Ph.D. from TU München (1996) and research fellowships at the International Computer Science Institute (Berkeley, 1997–1998). Education: Studied Computer Science and Mathematics at Johann Wolfgang Goethe-Universität Frankfurt (1984–1991), followed by research roles at TU München and other institutions. Professional roles include Research Assistant (1991–1996) and Research Associate (1996–2003). Research focuses on algorithmic bioinformatics, protein folding, data structures, and computational biology. Key contributions include work on RNA sequence-structure analysis, chemical shift correction tools (e.g., CheckShift), and efficient algorithms for range queries and suffix arrays. He has authored multiple influential books on algorithms and bioinformatics. Publications span over two decades, emphasizing algorithm design, bioinformatics applications, and parallel computing. Supervised PhD students include Benjamin Albrecht (2016), Luca Chiarabini (2009), and Simon W. Ginzinger (2008). Teaching includes courses on Algorithmic Bioinformatics, Algorithms on Sequences, and bioinformatics-related seminars. Administrative roles include serving as Vice Dean (2004–2007, 2013–2017, 2019–present) and Dean (2011–2013, 2017–2019). His work bridges theoretical computer science and applied bioinformatics, with a focus on interdisciplinary research.

• Automation Engineering
• Control Systems
• Industrial Automation
• +5 more

Срђан Вукмировић is a Full Professor at the Department of Computer Science and Automation, Faculty of Technical Sciences, University of Novi Sad. He specializes in automation, control systems, and industrial data management. His academic journey includes a B.Sc. (2000), M.Sc. (2004), and Ph.D. (2011) from the University of Novi Sad. Education: B.Sc. in Computer Technology and System Control (2000) M.Sc. in Automatic Control (2004), Thesis: 'Application of OPC XML-DA Servers in Supervisory Control Systems' Ph.D. (2011), Thesis: 'Intelligent Task Scheduling in Large Supervisory Control Systems' Research focuses on industrial automation, distributed control systems, and optimization techniques. He has participated in 6 scientific projects and conducted international collaboration through training at the University of Lugano (Switzerland) and University of Cologne (Germany) under COST EU projects (2011). Teaching includes courses such as Automatic Control Systems, System Modeling & Simulation, Optimization Methods, and Distributed Control Systems. Affiliations include IEEE and Microsoft Professional. His work emphasizes practical implementation of industrial control devices and data acquisition systems, combining theoretical expertise with real-world applications.

• Biomedical Engineering
• Biomedical Signal Processing
• Entropy Analysis
• +7 more

Georgios Manis is an Associate Professor in the Department of Computer Science and Engineering at the School of Engineering, University of Ioannina, Greece. He holds a PhD from the National Technical University of Athens and has been a faculty member at the University of Ioannina since 2002, progressing from Lecturer to Associate Professor in 2018. He has also served as temporary teaching staff at the University of Patras, University of Crete, and University of Ioannina in the late 1990s and early 2000s. Education: B.Sc. in Computer Engineering (Diploma), National Technical University of Athens (NTUA), 1987–1992 MSc in Advanced Methods in Computer Science (Distributed and Parallel Systems), Queen Mary, University of London, 1992–1993 PhD in Computer Engineering, NTUA, School of Electrical and Computer Engineering, 1993–1997 His research interests lie at the intersection of Biomedical Engineering and Computing Systems , with a strong emphasis on Biomedical Signal Processing , Entropy Analysis , and Machine Learning . He has pioneered work in Bubble Entropy —a parameter-free entropy measure—and developed fast algorithms for entropy computation. His work also extends to compiler design and parallel computing, particularly in the automatic parallelization of recursive functions and loops. The trends in his recent publications reflect a dual focus: (1) biomedical applications involving entropy, heart rate analysis, and disease diagnosis using machine learning (especially Random Forests and SVMs), and (2) high-performance computing, including parallelization techniques and compiler optimizations for multi-core and SVP architectures. His research is highly interdisciplinary, combining signal processing, algorithm design, and clinical applications. Scientific Leadership and Recognition: Guest Editor, Special Issue on “Entropy in Biomedical Engineering”, Entropy (MDPI) Member of the IPAN Laboratory, University of Ioannina Active contributor to IEEE, Elsevier, and MDPI journals He has supervised several graduate students and is involved in funded research projects such as Palimpsest and Homore , focusing on smart systems for cultural interaction and elderly monitoring. His advising contributions are evident in co-authored papers with students like Evanthia Tripoliti and Aristeidis Mastoras. He teaches both undergraduate and postgraduate courses, including Compilers I/II and Biomedical Data Analysis . Laboratories and Teams: He is a member of the IPAN lab at the University of Ioannina, which supports interdisciplinary research in informatics and biomedical applications. His collaborative network includes researchers from Greece and abroad, particularly in the fields of biomedical signal analysis and entropy-based methods.

Bo Kum JungView profile

Researcher

• THz communication
• Cellular mobile communication
• Wireless backhaul systems
• +2 more

Bo Kum Jung is a Researcher at the Institute of Communications Engineering, Technical University of Braunschweig, specializing in Terahertz communications and wireless backhaul systems. Working under Prof. Dr.-Ing. Thomas Kürner in the Mobile Communications Systems Department, Jung contributes to cutting-edge research in high-frequency wireless communications, with a focus on 300 GHz systems and reconfigurable intelligent surfaces. Education: Bachelor's degree in Electrical Engineering from INHA University, South Korea (2009-2015) Master's degree in Electrical Engineering from Technical University of Braunschweig (2016-2019) Jung's research focuses on Terahertz (THz) communication systems, particularly at 300 GHz frequencies. Their work addresses critical challenges in wireless backhaul networks, including channel modeling, interference management, and the application of Reconfigurable Intelligent Surfaces (RIS) to enhance signal propagation. They have developed automatic planning algorithms for THz backhaul links using various topologies and analyzed the impact of environmental factors on system performance. The research has practical applications for future 6G networks and high-capacity wireless infrastructure. Analysis of Jung's publication record shows a consistent focus on practical implementation of THz communication systems. Their research spans channel measurements, performance analysis, and system design for 300 GHz wireless networks. A notable trend is the increasing focus on Reconfigurable Intelligent Surfaces as a key technology for overcoming propagation challenges at these high frequencies. Their work bridges theoretical modeling with experimental validation through collaborations with the Institute for Communications Engineering. As a research staff member at TU Braunschweig, Jung collaborates with Prof. Thomas Kürner and other researchers in the Mobile Communications Systems Department. Their work is supported by the university's research infrastructure and contributes to the institution's strategic focus on next-generation communication technologies. The research has potential applications in 6G network development, industrial wireless communications, and high-capacity backhaul solutions.

Louis-Noël PouchetView profile

Associate Professor

• polyhedral compilation
• iterative and adaptive compilation
• auto-tuning compilers
• +15 more

Louis-Noël Pouchet is an Associate Professor in the Department of Computer Science at Colorado State University, with a joint appointment in the Electrical and Computer Engineering department. He leads research in high-performance computing, focusing on polyhedral compilation, performance portability, and hardware-software co-design. His research interests include polyhedral compilation, iterative and adaptive compilation, machine learning for compilers, performance-oriented domain-specific languages, energy-aware program optimization, and high-level synthesis. He develops compiler technologies to optimize and parallelize code for heterogeneous platforms, with applications in scientific computing and embedded systems. The 15 most recent publications highlight a strong focus on compiler optimization for high-performance systems, particularly using the polyhedral model. Key themes include data locality, parallelization, vectorization, memory access optimization, and performance modeling. His work spans both theoretical advances in program transformation and practical implementations in tools like PoCC and PolyOpt. Member, Center for Domain-Specific Computing (NSF) Member, DSL Technology for Exascale Computing (DoE) Lead, Polyhedral Compilation Research (NSF and Intel ISRA) Former member, Platform-Aware Compilation Environment (DARPA) He teaches courses on polyhedral compilation and has developed widely used software tools such as PoCC, PolyBench/C, and PolyOpt/C. His research is supported by major funding agencies including NSF, DoE, and Intel.