Find Academic Supervisors

• Internet of Things (IoT)
• Smart Systems and Automation
• Telematics Engineering
• +4 more

Juan Ramón Velasco Pérez is a Full Professor at the Department of Automática within the Universidad Autónoma de Madrid . His research focuses on IoT systems, telematics engineering, and smart environments , with particular emphasis on applications in healthcare, education, and multi-agent systems. He holds a PhD from the Universidad Politécnica de Madrid (1992) and has supervised doctoral research in intelligent control systems. His work includes pioneering contributions to smart toy platforms for child development monitoring, secure IoT communication protocols , and ontology-based interoperability frameworks . He has developed innovative methods for automated negotiation algorithms in dynamic environments and multi-agent systems for smart homes and emergency networks. Recent projects address digital competence frameworks for university educators and real-time physical activity monitoring systems using wearable technologies. Key technical contributions span embedded fuzzy logic controllers for sensor networks, non-Euclidean clustering algorithms , and context-aware service architectures . His research integrates hardware-software co-design principles with advanced data analytics for healthcare and educational applications. Education: PhD in Telematics Engineering, Universidad Politécnica de Madrid (1992) Thesis: Arquitectura para sistemas de control inteligentes , supervised by Dr. Gregorio Fernández Fernández Key Projects: DiY Smart Experiences Project (2011) NetIS Research Group (Networks and Intelligent Systems) His work bridges theoretical advancements in multi-agent systems with practical implementations in smart cities infrastructure , ambient assisted living , and pedagogical technology . Current research trends emphasize cross-disciplinary frameworks for digital competence assessment in academia and secure IoT ecosystems for pediatric healthcare applications.

Harris MakatsorisView profile

Professor

• Sustainable Manufacturing Systems
• Process Intensification
• AI in Materials Science
• +7 more

Professor Harris Makatsoris is a Professor of Sustainable Manufacturing Systems at King's College London, based in the Department of Engineering within the Faculty of Natural, Mathematical & Engineering Sciences. His research focuses on integrating mechanical engineering, process systems engineering, and intelligent automation to advance sustainable manufacturing, particularly in high-value chemical production and vaccine manufacturing. He holds a graduate degree from Imperial College London and is a Chartered Engineer. Research Interests: Process intensification, flow technologies, AI-driven materials discovery, circular manufacturing, and bioprocessing for vaccines. His work emphasizes sustainable solutions through robotics, algorithmic optimization, and industrial automation. Awards: Recipient of the Royal Academy of Engineering's President's Special Award for Pandemic Service (2020) for contributions to vaccine production. Active in technology transfer, leading university spin-outs and collaborations with industry. Grants/Projects: Principal Investigator for initiatives like the £10M Future Manufacturing Vaccine Hub (EPSRC-funded), BiaB Biofoundry projects (Wellcome Leap), and AmorFlow (EPSRC). These projects address rapid vaccine manufacture, modular RNA production networks, and continuous pharmaceutical manufacturing. Labs/Teams: Affiliated with the London Centre for Nanotechnology and collaborates globally on RNA biology, climate sustainability, and biomedical engineering. Engages in interdisciplinary research across engineering, medicine, and environmental science.

• Control Systems
• Optimization
• Machine Learning
• +5 more

Prof. Maryam Kamgarpour is a faculty member at ETH Zurich's Automatic Control Laboratory within the Department of Information Technology and Electrical Engineering. Her research focuses on control systems, optimization, and machine learning, with applications in robotics, power systems, and multi-agent systems. She has contributed significantly to safe reinforcement learning, stochastic control, and distributed optimization frameworks. Her work bridges theoretical foundations and practical implementations in areas like safe trajectory planning, market mechanisms for energy systems, and algorithmic guarantees for greedy methods. Key technical areas include model-based multi-agent reinforcement learning, robust control policies under uncertainty, and parameterization techniques in control theory. Collaborations with institutions like ETH Zurich's Automatic Control Lab and researchers such as Andreas Krause highlight her interdisciplinary approach. Her research has been supported by grants from the Swiss National Science Foundation (NCCR Automation) and the European Union (Reliable Data-Driven Decision Making in Cyber-Physical Systems). Publications span top journals and conferences in control systems, machine learning, and robotics, emphasizing rigorous analysis and practical scalability. Recent work addresses challenges in safe black-box optimization, stochastic hazard management in robotics, and market-based resource allocation in power grids.

Qianwen LiView profile

Assistant Professor

• Intelligent Transportation Systems
• Vehicle Automation
• Traffic Safety and Efficiency
• +4 more

Dr. Qianwen (Cami) Li is an Assistant Professor in the School of Environmental, Civil, Agricultural and Mechanical Engineering (ECAM) at the University of Georgia. She leads the Cooperative Automated Mobility Innovations (CAMIs) Lab, focusing on enhancing transportation safety and efficiency through automation, vehicle communication, electrification, and smart infrastructure integration. Her work spans theoretical modeling, simulation tools, and real-world experimentation in connected and automated vehicle systems. Education details are not explicitly stated in the provided text, but her title indicates a doctoral degree. Her research emphasizes cutting-edge topics such as trajectory optimization for modular buses, safety-aware neural networks for AVs, and energy consumption analysis in transit systems. She has contributed to foundational studies on mixed traffic dynamics, pedestrian safety through roadway lighting, and policy frameworks for ACES (Automated, Connected, Electric, Shared) transportation systems. Dr. Li’s publications (15 most recent listed) highlight her expertise in CAV technologies, traffic modeling, and infrastructure integration. She has developed datasets for AV-traffic light interactions and pioneered methods to identify automated vehicles in mixed traffic using machine learning. Her work also addresses challenges like nighttime pedestrian crash modeling and optimal evacuation planning for electric vehicles. While no specific awards or grants are listed, her lab’s focus on cooperative automated mobility suggests active engagement in funded research projects. The CAMIs Lab collaborates on real-world applications, such as Florida’s ACES roadmap and trajectory control experiments for platooned vehicles.

Sonja GrünView profile

Professor

• Neuroscience
• Computational Neuroscience
• Neural Networks
• +3 more

Prof. Sonja Grün is a Professor and Director of the Computational and Systems Neuroscience division (IAS-6) and the JARA-Institute Brain structure-function relationships (INM-10) at Forschungszentrum Jülich. She leads the Statistical Neuroscience research group, focusing on cell assemblies, dynamical neuronal interactions in cortex, higher-order correlation analysis, and reproducible workflows. Her work bridges experimental and computational approaches to understand neural coding and network dynamics. Key contributions include methodologies for spike pattern detection (e.g., SPADE) and tools for data curation (UnitRefine). She actively develops neuroinformatics standards (e.g., Neuroelectrophysiology Analysis Ontology) and promotes reproducible research through provenance tracking initiatives like NFDI-Neuro. Her research spans motor cortex activity, visual processing, and model validation frameworks. Research interests emphasize spatio-temporal spike patterns, cortical network models, and artifact detection in high-density recordings. She collaborates on projects integrating electrophysiological data with computational simulations (e.g., NEST) and brain wave analysis (Cobrawap). Current efforts address challenges in data sharing, artifact removal, and scalable analysis pipelines for heterogeneous datasets.

• Software Engineering
• Agile Methodology
• Simulation and Modeling
• +4 more

Arne Styve is an Associate Teaching Professor at the Department of Information and Communication Technology and Natural Sciences, Norwegian University of Science and Technology (NTNU). He serves as a Studyprogram coordinator for Computing Science and teaches object-oriented programming and system development at the Bachelor level, along with simulation and visualization at the Master level. Education: B.Eng. w/Hons (Sivilingeniør) in Microelectronics and Software Engineering, University of Newcastle upon Tyne Research Interests: Specializing in Agile development, simulation modeling, and technology education. His work focuses on programming pedagogy, digital twin applications, and co-simulation frameworks. Recent research explores integrating generative AI into critical thinking practices in programming courses. Publication Trends: His publications over the past decade demonstrate expertise in simulation modeling for maritime systems, educational technology innovations, and software engineering frameworks. Key themes include digital twins, flipped classroom methodologies, and cross-campus programming education. Teaching Contributions: Instructs courses including IDATA2505 (Practice-Based Learning), IDATT2003 (Programming 2), and IDATA2302 (Algorithms & Data Structures). His pedagogical approach combines industry experience with academic innovation. Industry Experience: Over 20 years in Norwegian IT industry, including roles at Offshore Simulator Center (OSC AS), developing advanced maritime simulators and command control systems for defense applications.

• Control Engineering
• Electric Drive Technology
• Power Electronics
• +4 more

Prof. Dr.-Ing. Rudolf Mecke is a Professor of Control Engineering and Electrical Drives at Harz University of Applied Sciences since 2006. His affiliations include the Faculty of Automation and Information and the Department of Automation and Computer Science. Studied Electrical Engineering at Otto von Guericke University Magdeburg (1985–1990) Doctorate in Electrical Engineering (1995) focusing on stator flux-oriented control Research interests span control engineering , electric drive technology , power electronics , and energy conversion/storage . Key contributions include: Dynamic control systems for three-phase drives Model-based state variable determination Inductive contactless power transmission Energy-efficient control strategies Power converter topologies for renewable energy EMC analysis for industrial systems His publications focus on power electronics, wireless energy transfer, and efficiency optimization. Recent work includes multilevel inverters and SiC/GaN semiconductor applications. Research groups under his supervision explored topics like: Contactless energy transmission systems PWM inverter topologies Rotor flux control in induction machines Converter integration in PV/wind systems EMC behavior of IGBT systems High-frequency drive analysis

Casey NicholsView profile

Researcher

• Marine Renewable Energy
• Embedded Systems
• Automated Composites Manufacturing
• +3 more

Casey Nichols is a Researcher in Mechanical Engineering at the National Renewable Energy Laboratory (NREL), specializing in embedded systems for marine renewable energy validation and automated wind blade manufacturing within the Center for Energy Conversion and Storage Systems. Education: Master of Applied Energy and Electromechanical Systems, University of North Carolina at Charlotte Bachelor of Mechanical Engineering Technology, University of North Carolina at Charlotte Research Focus: Nichols develops embedded testing systems for ocean energy devices through the MODAQ (Modular Ocean Data Acquisition) project using LabVIEW and compact RIO controllers. Research spans marine renewable energy system validation , automated composites manufacturing , and wind turbine blade production , with emphasis on field-deployable instrumentation and robotic fabrication techniques. Publication Trends: Recent work (2021-2025) shows concentrated activity in marine energy validation (wave/tidal) and wind manufacturing automation. Key themes include cost-effective data acquisition, structural health monitoring of energy devices, and additive manufacturing integration for composite components. Research Infrastructure: Active in NREL's Center for Energy Conversion and Storage Systems, Nichols develops the MODAQ platform for ocean energy testing while collaborating on wind blade automation projects involving robotic finishing systems and toolpath optimization.

• Robotics
• Mechanical Systems
• Aerospace Engineering
• +5 more

Laura Salamina is a Fixed-Term Assistant Professor at the Politecnico di Torino within the Department of Mechanical and Aerospace Engineering (DIMEAS) . Her work bridges robotics, mechanical design, and aerospace applications, with a focus on inflatable structures and human-robot collaboration. Research Groups: Mechatronics and Servosystems Teaching: Digital Twins for Mechanical Systems Prognostics, Product Components (Materials and Design) Her research explores robotics for planetary exploration , collaborative manipulation , and digital twin technologies . Recent work includes inflatable robotic arms for space debris removal, spherical planetary rovers, and safety frameworks for industrial robotics. Publications highlight interdisciplinary applications in aerospace, recycling, and energy systems. Key trends in her publications include: Inflatable deployable/retractable structures for aerospace Human-robot collaboration in industrial settings Digital twins for predictive maintenance and leak detection Gyroscopic control systems for planetary rovers Labs/Teams: Active member of the Mechatronics and Servosystems research group.

Ivelina StoyanovaView profile

Researcher

• Smart Grids
• Energy Optimization
• Multi-Energy Systems
• +3 more

Dr. Ivelina Stoyanova is a Researcher at the Institute for Automation of Complex Power Systems at RWTH Aachen University. Her work focuses on energy flexibility management and optimization, particularly in smart cities and multi-energy systems. She serves as Research Exploitation Coordinator at the institute. RWTH Aachen University Institute for Automation of Complex Power Systems Academic Rank: Researcher Her research interests span Smart Grids, Energy Optimization, Multi-Energy Systems, and Demand Side Management. She specializes in model predictive control, cross-domain optimization, and statistical process control applications in energy systems. Her publications highlight trends in smart grid technologies and urban energy systems, emphasizing distributed control strategies, Pareto optimization, and modular modeling approaches for integrated power and thermal grids. Key themes include load variation analysis, multi-domain simulation, and TSO-DSO coordination challenges.

Emanuele D'OsualdoView profile

Professor

• Programming Languages
• Verification
• Security
• +8 more

Emanuele D'Osualdo is a Tenure-Track Professor of Formal Methods for Software Engineering at the University of Konstanz, Department of Computer and Information Science. Previously, he was a Postdoctoral Researcher at Max Planck Institute for Software Systems (MPI-SWS) in Saarbrücken until April 2024, working with Derek Dreyer on verification of concurrent software. Before that, until September 2020, he was a Marie Curie Fellow at Imperial College London, working with Prof. P. Gardner. From 2015 to 2017, he was a PostDoc in the Concurrency Theory Group at the University of Kaiserslautern, working with Prof. Roland Meyer. His educational background includes: PhD (DPhil) in Computer Science from the University of Oxford (2015), supervised by Prof. C.-H. Luke Ong Undergraduate and master's studies at the University of Udine, Italy, graduating with honors and supported by the Scuola Superiore scholarship Emanuele D'Osualdo's research focuses on Formal Methods for the verification of software, with particular emphasis on two main approaches: automatic verification methods using static analysis and infinite-state model checking; and compositional methods, focusing on program logics for properties beyond safety. His work spans several areas including Programming Languages, Verification, Security, Concurrency Theory, Probabilistic Programs, Types, Static Analysis, Process Algebra, and Model Checking. His research has led to the development of tools such as Soter for automatic safety verification of Erlang programs and James Bound for analyzing π-calculus. His recent publications demonstrate a strong focus on advanced verification techniques for concurrent and distributed systems, with particular attention to linearizability, session types, security protocols, and probabilistic reasoning. His work bridges theoretical foundations with practical applications in software verification, showing a progression from foundational work on π-calculus to more applied verification of concurrent data structures and probabilistic systems. He has received notable recognition for his work, including: Winner of the 2016 CPHC/BCS Distinguished Dissertation award Marie Curie Fellow Emanuele actively supervises students and leads research in formal methods. He is involved in several research projects related to software verification and has presented his work at top-tier conferences including POPL, OOPSLA, ESOP, and CAV. He is scheduled to give a keynote at HYPER'25 in Zagreb and will be attending POPL'25. His research group appears to focus on developing theoretically sound yet practical verification techniques for modern concurrent and distributed software systems.

Loris D'AntoniView profile

Associate Professor

• Program Synthesis
• Formal Methods
• Trustworthy Software
• +3 more

Loris D'Antoni is an Associate Professor at the University of California San Diego, affiliated with the Programming Systems Group and serving as a visiting academic at AWS . Previously, he co-founded a research group at UW-Madison. His research focuses on trustworthy software through Program synthesis (e.g., SemGuS toolkit) Formal verification of machine learning and network protocols Automata theory and symbolic constraints Trustworthy LLMs with grammar alignment Recent work explores semantics-guided synthesis and unrealizability logic , with applications to decision trees, LSTMs, and network routing. Publications span top venues like PLDI , OOPSLA , NeurIPS , and CAV . Notable scientific awards include Best Paper Award at ICDCN 23 Distinguished Paper Award at SBES 21 Oral Presentation at EMNLP 21 Nomination for EAPLS Award (part of ESOP 20 ) He teaches courses in programming languages ( CS-536 ) and synthesis/verification ( CS-703 ), and actively contributes to program committees at conferences like PLDI , CAV , and POPL .

• Assistive Technology
• Embedded Systems
• Real-time Operating Systems
• +3 more

Dr. Florian von Zabiensky is a Lecturer at Technische Hochschule Mittelhessen , where he has taught courses such as Embedded Systems Internship, Real-time Systems, and Software Engineering Project since 2016. He holds a PhD and M.Sc. in Computer Science, with a focus on embedded systems and assistive technologies for the blind. His research spans real-time operating systems, domain-specific languages, and simulation of embedded systems. Education : B.Sc. and M.Sc. in Computer Science, with thesis work on memory management and wireless sensor networks. Research Interests : Assistive technology, embedded systems, real-time systems, domain-specific languages, and sensor networks. Publications : Focus on electronic travel aids, AADL for ROS2 architectures, and neural networks in accessibility solutions. Industry Role : Software developer at Schmidt Embedded Systems GmbH since 2020 and self-employed developer in embedded systems.

• Engineering Practice
• Sustainability
• Operations Management
• +9 more

Dr. Ifije Ohiomah is a Senior Lecturer in Engineering Practice and Sustainability at the School of Engineering, University of the West of England (UWE). Specializing in operations management, project management, and manufacturing engineering, her research bridges sustainability, digitalization, and supply chain dynamics across construction, healthcare, and manufacturing sectors in South Africa and Nigeria. B.Eng in Production Engineering MPhil in Engineering Management PhD in Operations Management Her expertise includes digitalisation , quality management , and machine learning applications in operations. Recent work focuses on modular building practices , multi-criteria decision-making in sustainable construction , and IoT integration in South African retail . She explores pandemic resilience in built environments and emerging technologies in mining, emphasizing circular economy principles. Key themes in her publications include reverse supply chain models , barriers to industrialized building systems , and conflict resolution in construction projects . Methodologies range from empirical analysis to structural equation modelling, reflecting her interdisciplinary approach. Her collaborations span global operations , healthcare service operations , and AI-driven sustainability across industries. Contact: Ifije.Ohiomah@uwe.ac.uk

Asztalos MárkView profile

Associate Professor

• Model-Driven Engineering
• Software Engineering
• Graph Rewriting Systems
• +3 more

Márk Asztalos is an Associate Professor at the Budapest University of Technology and Economics , affiliated with the Faculty of Electrical Engineering and Informatics and the Department of Automation and Applied Informatics . He leads research in the Visual Modeling Group, focusing on model-driven engineering, graph rewriting systems, and domain-specific languages. Research Interests: Model transformation verification, text-based modeling, graph pattern matching, and cloud/mobile system modeling. Contact: E-mail: Asztalos.Mark@aut.bme.hu , Office: Q.B226, Department of Automation and Applied Informatics, BME. His publications emphasize model transformation verification (2010-2015), graph rewriting techniques for pattern matching (2015-2017), and domain-specific language design (2014). Recent work (2020) analyzes model integration challenges in model-driven methodologies. Contact details: Address: Budapest 1117, Magyar tudósok krt. 2, Hungary Phone: +36 (1) 463-3702