Find Academic Supervisors

• Telecommunications
• Wireless Communication
• Machine Learning
• +14 more

Dr. Iakovos S. Venieris is a distinguished researcher at the University of Piraeus , Department of Digital Systems , with a prolific publication record spanning over 15 years. His work focuses on telecommunications , wireless networks , and machine learning applications in network optimization and security. Research Interests Telecommunications and Wireless Network Design Intelligent Metasurfaces (STARS) in 5G/6G Systems Edge Computing and DNN Inference Optimization Privacy-Aware Network Monitoring and Access Control Particle Swarm Optimization in Network Topology Context-Aware Systems and Semantic Rule Injection Recent Trends : His 2024–2025 publications emphasize stacked intelligent metasurfaces for MIMO networks, ML-driven eavesdropper detection in IIoT, and dynamic temporal encodings for IoT security. Earlier works delve into privacy legislation enforcement (2007) and adaptive QoS via neural networks (2006). Collaborations : Regular co-author with Dimitra I. Kaklamani , Symeon Chatzinotas , and Stylianos I. Venieris , often published in IEEE Transactions on Vehicular Technology, Wireless Communications, and Access.

Benedikt SpiesView profile

Researcher

• Transport Protocols
• Connection Migration
• Edge Computing
• +7 more

Benedikt Spies is a researcher at the Chair of Connected Mobility (I11) within the Department of Computer Engineering at the Technical University of Munich , affiliated with the TUM School of Computation, Information and Technology . His work focuses on transport protocols, edge computing, and network stack design, particularly leveraging technologies like QUIC and WebAssembly . Research Interests : Transport Protocols, Connection Migration, Edge Computing, QUIC, Middleboxes, Satellite Networks. Contact : benedikt.spies@in.tum.de | Office: 01.05.038, Boltzmannstr. 3, 85748 Garching. Recent publications highlight his exploration of composable network stacks using WebAssembly and QUIC (2025), secure middlebox-assisted QUIC implementations (2023), and performance evaluations of WebAssembly in non-web contexts (2021). These works reflect a consistent emphasis on optimizing network protocols and enabling flexible, secure communication architectures. Benedikt actively supervises student theses and practical courses in his research domain, including Hands-on Recommender Systems , Edge Computing , and Computer Network Simulation projects.

Fabian HummerView profile

Tutor

• Particle Physics
• Detector Development
• Calorimetry
• +3 more

Fabian Hummer is a Tutor at the Karlsruhe School of Elementary Particle and Astroparticle Physics: Science and Technology affiliated with the Institute for Data Processing and Electronics at Karlsruhe Institute of Technology (KIT). His work focuses on detector development for high-energy physics experiments, particularly the CMS High Granularity Calorimeter (HGCAL) at CERN. Education: Master's Degree from TU Munich (2022), Bachelor's Degree from Johannes Kepler University (2020) Research interests center on calorimetry , SiPM-on-Tile technology , and machine learning applications for particle shower reconstruction. His contributions include firmware development, real-time data processing, and time resolution optimization. Publications highlight advancements in: Full-stack integration of HGCAL with Serenity DAQ Timing performance analysis under radiation conditions ML-based five-dimensional shower separation Recent work presented at: TWEPP 2024 (Glasgow) DPG Spring Meeting 2024 HGCAL Summer Workshop 2024 He serves as a lab course tutor for Electronics for Physicists and co-organized the 9th Matter and Technologies Student Retreat.

Heng LiView profile

Assistant Professor

• Software Engineering
• Software Analytics
• Software Observability
• +7 more

Heng Li is an Assistant Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montreal, Canada. He leads the Measurement, Observation, and Optimization of Software and its Evolution (MOOSE) lab, focusing on software engineering research with emphasis on observability, log analysis, and performance engineering. His work bridges academic research with practical industry applications, drawing from his prior experience as a software engineer at Synopsys and BlackBerry. Education: Ph.D. in Computing from Queen's University, Canada M.Sc. from Fudan University, China B.Eng. from Sun Yat-sen University, China Heng Li's research spans multiple critical areas in modern software engineering. His primary focus is on software monitoring and observability , where he develops techniques to make software systems more transparent and understandable during operation. He has made significant contributions to software log mining , creating novel approaches for parsing and analyzing log data to detect anomalies and performance issues. His work in intelligent operations of software systems applies machine learning to automate various aspects of software operations. Additionally, he researches software performance engineering and mining software repositories to understand development practices and improve software quality. An analysis of Dr. Li's recent publications reveals a strong focus on practical applications of software analytics. His work consistently addresses real-world challenges in software observability, particularly log analysis and performance monitoring. A notable trend is his exploration of machine learning applications in software operations (AIOps), with increasing emphasis on efficient algorithms for log processing and anomaly detection. His research shows a progression from foundational techniques in log parsing to more sophisticated approaches for performance regression detection and privacy preservation in software logs. Many of his papers include empirical studies from industry settings, demonstrating his commitment to bridging the gap between academic research and industrial practice. Professional Service: Program Committee member for multiple top software engineering conferences including ASE, ICSE, ESEC/FSE Active participation in workshops and special tracks related to software analytics and AIOps Dr. Li leads the MOOSE (Measurement, Observation, and Optimization of Software and its Evolution) laboratory at Polytechnique Montreal. The lab focuses on developing innovative techniques for monitoring software systems, analyzing their behavior through logs and performance metrics, and optimizing their operation. Current projects in the lab include advanced log parsing algorithms, performance regression detection systems, and privacy-preserving techniques for software logs. The lab maintains strong connections with industry partners to ensure research relevance to real-world challenges.

Fatemeh Hendijani FardView profile

Assistant Professor

• Code Intelligence
• Transfer Learning
• AI4SE
• +5 more

Fatemeh Hendijani Fard is an Assistant Professor in the Department of Computer Science at the University of British Columbia's Okanagan campus. She serves as a graduate student supervisor and teaches courses in Computer Science and Data Science. Dr. Fard is a member of the CITECH program and MMRI, part of the Killam family of scholars, and an active member of both IEEE and ACM. Her research focuses on the intersection of Natural Language Processing and Software Engineering, with particular emphasis on developing code intelligence models for low-resource programming languages like R. She conducts empirical studies and develops techniques to improve the computational efficiency of code-language models while making them accessible to communities with restricted GPU access. Her work strongly advocates for Diversity and Inclusion in STEM, particularly for underrepresented females. Analysis of Dr. Fard's recent publications reveals a strong research trajectory in adapting Large Language Models for code intelligence with a focus on efficiency and accessibility. Her work spans multiple dimensions including code summarization, method name prediction, code search, code clone detection, and program repair, with special attention to low-resource programming languages. A notable trend is her exploration of adapter-based approaches for knowledge transfer that reduce computational requirements while maintaining performance. Izaak Walton Killam Memorial Scholarship Alberta Innovates Technology Futures (AITF) NSERC Discovery NSERC CREATE Mitacs Accelerate UBC Start-up Fund Dr. Fard has secured significant research funding including NSERC Discovery, NSERC CREATE, Mitacs Accelerate, and UBC Start-up funds to support her work on code intelligence for low-resource programming languages. She actively serves as a graduate student supervisor, guiding research in areas related to code representation learning and mining software repositories. Her service to the academic community is extensive, having served on program committees for major conferences including FSE, MSR, ASE, SANER, and ICSME across multiple years. Dr. Fard leads research initiatives focused on making code intelligence accessible to communities working with understudied programming languages. Her team conducts empirical studies and develops new techniques specifically designed for low-resource languages, with particular attention to the R programming language. This work addresses diversity and inclusion in AI tools by ensuring developers with limited computational resources can benefit from advances in neural networks and automated tools.

Eva RentschlerView profile

Professor

• Molecular Magnetism
• Inorganic Chemistry
• Bioinorganic Chemistry
• +7 more

Prof. Dr. Eva Rentschler is a full Professor in the Department of Chemistry at Johannes Gutenberg-Universität Mainz, Faculty 09 - Chemistry, Pharmaceutical Sciences and Geosciences. She leads an active research group focused on molecular magnetism, inorganic and bioinorganic chemistry, and the synthesis of polynuclear metal clusters. Her teaching includes advanced courses such as Anorganische Chemie II–IV, Bioanorganische Chemie, and Magnetische Werkstoffe. Her research interests lie at the intersection of coordination chemistry and materials science, particularly in designing magnetic molecular systems, studying exchange interactions in transition metal clusters, and exploring supramolecular architectures with tailored magnetic properties. She is involved in the Transregional Collaborative Research Center SFB/TRR 173 "Spin+X – Spin in its collective environment" and the Max Planck Graduate Center, highlighting her leadership in interdisciplinary research. The recent publications reflect a strong focus on polynuclear transition metal complexes (Fe, Mn, Co, Cu, Ni), heterometallic systems, ligand design, magnetic coupling, and structural characterization. These works span synthesis, crystallography, spectroscopy, electrochemistry, and computational modeling, demonstrating a comprehensive and multidisciplinary approach to molecular magnetism and functional materials. Prof. Rentschler actively supervises students, with multiple bachelor's and master’s graduates acknowledged recently. Her group contributes to major collaborative projects, indicating sustained funding and research activity. She also participates in educational initiatives such as the Summer School: MolSpin 2018 and Master Class – MolMag. Laboratories and Teams: She leads the research group "Group of Prof. Dr. Eva Rentschler" at the Institute of Inorganic and Analytical Chemistry. Her team collaborates within the SFB/TRR 173 and the Max Planck Graduate Center, working on spin-related phenomena in molecular and nanoscale systems.

• Computer Architecture
• Operating Systems
• Memory Management
• +5 more

Youngjin Kwon is an Associate Professor at the School of Computing, KAIST, and a member of the Computer Architecture and Systems Lab (CASYS). His work bridges systems research with practical applications in memory management, concurrency debugging, and energy-efficient computing. Recipient of Best Paper Awards at ACM SOSP'24, SOSP'21, and USENIX ATC'18 Honored with KAIST's EWON Endowed Chair Professor (2021) and Soo-Young Lee Teaching Innovation Award (2021) Awarded KAIST Breakthrough (2023) and Technology Innovation Award (2023) Research focuses on: Processing-in-Memory (PIM) and DRAM architectures Concurrency bugs in kernel and hypervisor systems Energy-efficient frameworks for large language models Memory disaggregation and tiered memory systems Trusted Execution Environments (TEE) for secure computing SmartNIC offloading and eBPF-based optimizations His recent publications highlight innovations in speculative decoding, memory safety, and system scalability. Awards reflect both technical excellence and pedagogical impact. He actively mentors graduate and undergraduate students in his lab, emphasizing hands-on research in cutting-edge system design.

Manfred KudlekView profile

Professor

• Theoretical Computer Science
• Formal Languages
• Petri Nets
• +8 more

Prof. Manfred Kudlek was a Professor of Theoretical Computer Science at the University of Hamburg (Department of Computer Science) from 1977 until his retirement in 2005. He held an honorary professorship at the University of Iași, Romania since 2002. His academic career began with studies in physics (Diploma: 1966; PhD: 1970), followed by research and teaching in computer science. He was deeply involved in the European Association for Theoretical Computer Science (EATCS), attending all ICALP conferences and contributing reports to the EATCS Bulletin. A special issue of Fundamenta Informaticae (2014) was dedicated to his memory, highlighting his research legacy in formal languages and concurrency theory. His research focused on foundational topics such as minimal Turing machines, Lindenmayer systems, Petri nets, and multiset automata. He also explored cross-disciplinary areas including numerical systems in indigenous languages and LaTeX encoding for non-Latin scripts. Manfred’s work emphasized international collaboration, particularly with Eastern European researchers, and he actively participated in global academic events until his death in 2012 during the Turing Centenary Conference in Cambridge, England. Survived by his wife and daughter, condolences were accepted via dedicated email and postal addresses managed by the university. Manfred held leadership roles including membership in the Departmental Council, Curriculum Planning Committees, and the Library Committee. His post-retirement activities remained prolific, maintaining teaching and research engagement until his sudden passing. Notable for his passion for travel and conferences, he left a legacy of over 211 scientific publications and 152 conference reports.

Alf KimmsView profile

Professor

• Operations Research
• Logistics and Supply Chain Management
• Revenue Management
• +6 more

Prof. Alf Kimms is a full professor at the University of Duisburg-Essen, holding the chair of Logistics and Traffic Management. He previously served as a full professor at the Technical University of Freiberg (2001–2006). His research focuses on applying operations research methods to logistics, supply chain optimization, revenue management, and evacuation planning. He earned his Ph.D. in Business Administration from the University of Kiel (1996) and his postdoctoral lecturer qualification (2001), both focusing on project management and production scheduling. Kimms' academic career is marked by contributions to high-impact journals such as European Journal of Operational Research and Annals of Operations Research . He has led projects for companies like Bayer, Lufthansa, and DaimlerChrysler, emphasizing practical applications of optimization. A 2005 Handelsblatt ranking placed him among Germany’s top ten business administration professors. He actively participates in professional societies, including the German OR Society (GOR), where he founded the Revenue Management working group. His research spans network design, disaster response logistics, cooperative game theory, and airline alliance strategies. Notable projects include evacuation modeling for urban areas and revenue management frameworks for broadcasting industries. Kimms reviews for the German Research Foundation (DFG) and serves on international conference committees, balancing academic rigor with industry collaboration.

Peter WägemannView profile

Researcher

• Real-Time Systems
• Embedded Systems
• Worst-Case Analysis
• +5 more

Peter Wägemann is a postdoctoral researcher leading the Embedded Systems Software group at the Chair of Computer Science 4 (System Software) at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). His research focuses on real-time systems, energy-constrained systems, worst-case analysis, and fault tolerance in embedded systems. He has received multiple awards, including the Best Paper Award at ECRTS '24 and Outstanding Paper Awards at ECRTS '18 and RTAS '17. His work spans topics like clock reconfiguration, energy-neutral systems, and Byzantine fault tolerance. Wägemann's teaching includes courses such as System-Level Programming, Real-Time Systems, and Dependable Real-Time Systems. He has organized conferences like WCET and RTSS and serves on program committees for top venues. His funded projects include DFG grants for Byzantine Fault Tolerance (BFTeam), whole-system analysis (Watwa), and power-constrained systems (ResPECT). He also collaborates with industry partners like Schaeffler AG on safety-critical AI systems. Key contributions include the Platin WCET analysis tool, TinyBFT for resource-constrained systems, and energy-efficient frameworks like FusionClock. His work bridges theoretical analysis with practical implementations in embedded systems, emphasizing sustainability and real-time guarantees.

• Robotics
• Artificial Intelligence
• Autonomous Systems
• +5 more

Prof. Ferrein is a Professor at the Institute for Mobile Autonomous Systems and Robotics (MASKOR) within the Faculty of Electrical Engineering and Information Technology at Aachen University of Applied Sciences. He has taught core courses including Fundamentals of Computer Science, Robotics, Artificial Intelligence, and Robot Programming with ROS for Electrical Engineering students from 2014 to 2016, establishing himself as a key educator in applied robotics. His research spans Robotics , Artificial Intelligence , and Industrial Automation , with concentrated expertise in logistics systems, mining automation, and smart manufacturing. As leader of the Carologistics RoboCup Logistics Team, he leverages competitive robotics to develop real-world factory automation solutions, focusing on multi-robot coordination, sensor fusion, and ROS-based implementations for industrial challenges. Analysis of his 2023-2025 publications reveals a decisive shift toward solving industry-specific problems: anomaly detection in metal-textile production, autonomous vehicle control in mining, and AI-supported work system design. His work consistently bridges academic research and industrial deployment through practical ROS integrations, emphasizing human-robot collaboration and cognitive load reduction in quality control workflows. MASKOR institute serves as the operational hub for Prof. Ferrein's activities, driving initiatives like the ROS Summer School and RoboCup Logistics League participation. This environment fosters industry-academia collaboration through educational programs and competitive benchmarks that validate cyber-physical systems for factory automation, with significant contributions to mining robotics and rescue operations.

• Mechatronics
• Embedded Systems
• Industrial Automation
• +6 more

Prof. Dr.-Ing. Jörg Wollert serves as Professor and Director of the Institute for Applied Automation and Mechatronics within the Department of Mechanical Engineering and Mechatronics at Aachen University of Applied Sciences. He actively teaches Mechatronics and Embedded Systems while participating in university governance through the Rectorate Commission for Research and Development. His research spans embedded systems implementation across industrial automation and automotive domains, with particular emphasis on wireless building technologies (Thread, AllJoyn, IEEE802.15.4), industrial communication protocols (OPC-UA, IO-Link, CAN-FD, BroadR-Reach), and safety-critical architectures. Current projects involve FPGA-based safety stacks, autonomous vehicle networking, and secure embedded communication solutions using Arduino platforms. As Director of the Institute for Applied Automation and Mechatronics and affiliate of the Institute for Mobile Autonomous Systems and Cognitive Robotics (MASKOR), he supervises numerous final theses in embedded system design. His laboratory work focuses on practical implementations including delta kinematics robots, vehicle control systems, and building automation demonstrations for lighting, HVAC, and wireless HART protocols.

Anh Vu DoanView profile

Lecturer

• Embedded Systems Design
• Combinatorial Optimization
• Problem Modeling
• +3 more

Dr. Ir. Anh Vu Doan is a Lecturer at the Technical University of Munich (TUM) under the Chair of Integrated Systems and a Senior Project Leader at Infineon in Neubiberg, Germany. With a Belgian-Vietnamese background and prior residence in Japan, he has held academic roles including postdoctoral fellowships at Keio University and TUM, as well as teaching assistant and stand-in lecturer positions at Université libre de Bruxelles (ULB) and IÉSEG School of Management. Research Interests: Embedded systems design Combinatorial optimization Problem modeling and decision aiding Approximate computing and 3D-stacking memory Machine learning reliability and safety Network-on-Chip (NoC) optimization Recent Publications focus on neuromorphic systems, power optimization for multicore processors, adversarial attacks in ML, and multi-objective design strategies using genetic algorithms. His work bridges hardware-software co-design and sustainable mobility decision frameworks. Scientific Awards: Erasmus-Mundus Grant (EASED program) JST/CREST Research Program Education: MSc in Electrical Engineering (ULB, 2009) PhD in Engineering Sciences (ULB, 2015)

• Materials Science
• Computational Materials Design
• High Entropy Alloys
• +4 more

Dr. Fritz Körmann is a Senior Research Scientist at the University of Stuttgart and a Guest Researcher at ICAMS, Ruhr-University Bochum. He currently leads the Project Group 'Complex Concentrated Alloys' at the Max Planck Institute for Sustainable Materials. His research focuses on computational materials design, with expertise in machine learning interatomic potentials, density functional theory, and magnetism. Key areas include high entropy alloys, steels, and materials for magnetic applications. Education: PhD in Physics, MPIE Düsseldorf (2007–2011) Master's in Physics, Humboldt University Berlin (2004–2007) Bachelor's in Physics, RWTH Aachen (2001–2004) Research interests span computational modeling of alloy phase stability, mechanical properties, and magnetic behavior. He has pioneered methods combining machine learning with ab initio calculations to accelerate material discovery. Recent work highlights include designing ultrastrong ductile medium-entropy alloys and exploring hydrogen accommodation in complex alloys. His articles emphasize machine learning applications in materials science, phase transition modeling, and structural properties of complex alloys. Collaborations include institutions like UCLA, TU Delft, and BAM Berlin. He leads projects funded by DFG and EU grants, focusing on computational tools for advanced alloy development. His group develops novel high-entropy alloys with tailored mechanical and magnetic properties, bridging theory and experimental validation. Dr. Körmann's work is supported by grants enabling advanced computational infrastructure and experimental collaborations. He contributes to labs focused on atomistic simulations and has pioneered automated approaches for calculating material melting points. Professional networks include active roles in the MPIE Alumni Network and academic partnerships across Europe and the US.

• Materials Science
• Alloy Design
• Metallurgy
• +3 more

Laura Gabriela Torres Mejia is a Researcher at the Max Planck Institute for Sustainable Materials, affiliated with the Department of Microstructure Physics and Alloy Design. Her work focuses on the development and characterization of advanced materials, particularly high-entropy alloys and multi-component systems. She holds a position within the institute’s active research members, contributing to cutting-edge studies in materials science and metallurgy. Her research interests span the fields of materials science and metallurgy, with a focus on alloy design, magnetic properties of materials, and the computational analysis of structural and thermodynamic properties. She investigates the effects of deformation, doping, and composition on material behavior, employing both experimental and theoretical approaches. Key areas include the study of stacking fault energy in multi-principal element alloys and the design of novel alloys using ab initio calculations. Recent publications highlight her contributions to understanding deformation-induced magnetic property changes in high-entropy alloys and the role of boron doping in multi-component systems. These studies bridge experimental and computational methods to advance material performance predictions. No scientific awards have been listed in the provided information. No advising or grant information is available in the provided content. She is part of the Department of Microstructure Physics and Alloy Design at the Max Planck Institute for Sustainable Materials, contributing to collaborative research projects within the institute’s broader network.