Find Academic Supervisors

• Software Engineering
• Educational Technology
• Artificial Intelligence
• +7 more

Iván Ruiz-Rube is a prolific researcher with a focus on Software Engineering , Educational Technology , and Human-Computer Interaction . His work spans augmented reality , chatbots , and domain-specific languages (DSLs) , aiming to democratize technology for non-experts and educators. Key Contributions : Tools for end-user development, frameworks for conversational agents, and methodologies for immersive educational VR/AR scenarios. Collaborations : Juan Manuel Dodero, José Miguel Mota, Antonio Balderas, and Rubén Baena-Pérez. Research Themes : • Enhancing educational experiences through mobile apps and VR/AR. • Innovations in DSLs and model-driven development . • Applying linked data and privacy-preserving techniques to web and software engineering. • Leveraging block-based programming for IoT education . Article Trends : His recent work emphasizes chatbots and end-user development (2024–2025), while earlier studies focus on DSLs and augmented reality in education (2018–2020). Biomedical applications (2021) and linked data (2010–2017) also appear frequently.

Philipp WiedemannView profile

Professor

• Biotechnology
• Cell Culture Technology
• Process Monitoring
• +4 more

Prof. Philipp Wiedemann serves as a Professor at Mannheim University of Applied Sciences (Technische Hochschule Mannheim) within the Faculty of Biotechnology. His research program centers on advanced monitoring techniques for biotechnological processes, with particular expertise in developing and implementing in situ microscopy systems across diverse applications. His research spans multiple domains of biotechnology: Development and application of in situ microscopes for cell density and viability assessment Image analysis using Artificial Intelligence for bioprocess characterization Cell stress detection via mass spectrometry Glucose monitoring systems for animal cell cultures Applications in pharmaceutical production, wastewater treatment, blood banking, and bioethanol manufacturing Wiedemann's recent publications (2021-2025) reveal a strong interdisciplinary approach, integrating bioprocess engineering with medical diagnostics and environmental science. His work demonstrates consistent innovation in monitoring technologies, with increasing incorporation of AI and machine learning techniques for real-time process control. The publications show applications ranging from pharmaceutical manufacturing to wastewater treatment plants, highlighting the versatility of his monitoring approaches. He teaches several specialized courses: Applied Cell Biology (covering animal cell culture techniques) Quality Assurance in the Pharmaceutical Industry (GMP requirements and compliance) Advanced Animal Cell Technology (process development and practical applications) Prof. Wiedemann maintains active collaborations with industry partners including KVE Rhein-Neckar and Bilfinger Industrial Services Salzburg, as well as research institutions. His work on in situ microscopy has been implemented commercially for wastewater treatment monitoring (ismanalytics.com), demonstrating successful translation of academic research to industrial applications.

Nataša ŽivićView profile

Professor

• Information and Coding Theory
• Cryptography
• Information Security
• +11 more

Prof. Dr. Nataša Živić is a Professor of Information and Coding Theory and Real-Time Image Processing at the Faculty of Digital Transformation , HTWK Leipzig . Her work bridges theoretical foundations in coding, cryptography, and signal processing with practical applications in IoT, smart grids, automotive systems, and blockchain technologies. Academic background: Dr.-Ing. habil. and Dr.-Ing. in Electrical Engineering, University of Siegen; Magister and Dipl.-Ing. from University of Belgrade. Professional journey: Founder of Secutanta GmbH; Senior Technical Security Engineer at Volkswagen (Cariad); academic roles at University of Siegen. Her research focuses on secure and robust communication , including noise-tolerant data authentication, joint channel coding and cryptography, and real-time image processing. She explores probabilistic AI algorithms and distributed ledger technologies for industrial applications in mobility and energy systems. The 15 most recent publications highlight her leadership in applying blockchain and DLT to automotive and IoT contexts, advancing secure communication in smart metering and charging infrastructure, and integrating machine learning for environmental and financial prediction. Her work spans IEEE, MDPI, and Springer venues, reflecting strong academic impact. Scientific Awards: Best Paper and Innovation Award, IEEE SEGE 2015 Best Paper Award, UBICOMM 2010 She has led DAAD-funded international projects with universities in the USA, Korea, and China, and contributes to standardization as a member of DIN and ISO committees on security (SC 27) and AI (SC 42). She is also an IEEE Senior Member and active reviewer for top journals. Her research addresses real-world challenges in automotive security, smart energy, and digital transformation.

• Optical Networking
• Elastic Optical Networks
• Machine Learning for Network Management
• +3 more

Georgios Ellinas is a Professor at the University of Cyprus, specializing in optical networking, machine learning for network management, and UAV swarm coordination. His research spans critical areas such as Elastic Optical Networks (EONs) , Physical Layer Security , and Multi-Agent Reinforcement Learning for autonomous systems. Recent work includes quantile regression models for handling uncertainty in network traffic, edge-assisted collision warning systems for urban mobility, and multi-task learning architectures for drone state identification. He applies distributed estimation techniques to jamming aerial targets and explores probabilistically robust trajectory planning for autonomous vehicles. His contributions extend to fair resource allocation in optical networks, UAV swarm coordination using ROS-LoRa integration, and quantum key distribution optimization. Collaborations with researchers like Tania Panayiotou and Panayiotis Kolios highlight his interdisciplinary approach.

Mario FritzView profile

Professor

• Trustworthy Artificial Intelligence
• Machine Learning
• Information Security
• +4 more

Mario Fritz is a faculty member at the CISPA Helmholtz Center for Information Security , an honorary professor at Saarland University , and a fellow of the European Laboratory for Learning and Intelligent Systems (ELLIS) . Previously, he led a research group at the Max Planck Institute for Informatics (2011-2018) and conducted postdoctoral work at UC Berkeley. His research focuses on trustworthy artificial intelligence at the intersection of information security and machine learning , with recent projects including the EU-funded ELSA - European Lighthouse on Secure and Safe AI . Current roles: CISPA faculty (2018-present), Saarland University professor (2019-present) Past roles: Max Planck senior researcher (2011-2018), ICSI/UC Berkeley postdoc (2008-2010) Education: PhD from TU Darmstadt, computer science studies at FAU Erlangen-Nuremberg His research spans AI security , privacy-preserving machine learning , computer vision , and deep generative models . Recent work includes LLM-based code deobfuscation , certified malware detectors , and membership inference attacks on DocVQA models . He serves as Associate Editor for the journal IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) and leads projects like Trustworthy Federated Data Analytics , PriSyn (synthetic health data with privacy), and ImageTox (automated toxicity detection). As of 2025, he has published over 100 scientific articles , including 80 in top venues like ICML, ICLR, and CVPR.

Viktor KunčakView profile

Associate Professor

• Program Synthesis
• Program Verification
• Automated Reasoning
• +3 more

Viktor Kunčak is an Associate Professor with tenure at the École Polytechnique Fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences. He leads the Laboratory for Automated Reasoning and Analysis (LARA) and has been at EPFL since 2007 after completing his PhD at the Massachusetts Institute of Technology (MIT). His educational background includes: PhD from Massachusetts Institute of Technology (MIT), 2007 Professor Kunčak's research focuses on bridging the gap between human goals and computational realizations through program synthesis , verification , and automated reasoning . His work has significant applications in software development, formal methods, and programming languages. He is particularly known for developing practical tools like Leon and Stainless that implement theoretical advances in automated reasoning. His recent publications demonstrate a consistent focus on advancing program synthesis techniques, verification frameworks, and formal methods. The research trajectory shows progression from foundational theoretical work to practical applications and tools that can be used by developers. Many papers focus on making verification and synthesis more accessible and efficient for real-world programming tasks. His notable scientific achievements include: ACM SIGSOFT Distinguished Paper Award for work on automated testing European Research Council (ERC) Grant of 1.5M EUR (2012) Communications of the ACM Research Highlight for a PLDI paper Professor Kunčak has supervised 13 completed PhD theses and teaches courses on functional and parallel programming, compilers, and verification at EPFL. He has also co-taught a popular MOOC on Parallel Programming that reached over 100,000 learners worldwide. His research has been supported by significant funding including a 5-year ERC grant. He has served in leadership roles for major conferences including as program co-chair for FMCAD 2014 and VMCAI 2012. He leads the Laboratory for Automated Reasoning and Analysis (LARA) at EPFL, which develops tools like Stainless for program verification. The lab has established an international presence through collaborations including a European COST Action to establish standardized formats for verification and synthesis (Rich Model Toolkit).

• Cybersecurity
• Software Security
• Phishing Detection
• +4 more

Adam Doupé is a full professor at Arizona State University, specializing in cybersecurity and software security. His research focuses on automated vulnerability analysis, phishing detection, binary decompilation, and security in web technologies. Key research areas include: Cybersecurity Software Security Phishing and Fraud Detection Binary Analysis Automated Vulnerability Discovery His recent work explores large-scale phishing mitigation using machine learning (e.g., ScamNet), improving binary decompilation techniques (e.g., SAILR), and analyzing fraud browser detection via fingerprints. Trends show a strong emphasis on practical security tools, human-centric security analysis, and firmware vulnerability discovery. While no specific awards or grants are listed in the DBLP data, Doupé actively contributes to security education through frameworks like SENSAI and CTF-as-a-service. He collaborates extensively with researchers such as Yan Shoshitaishvili, Ruoyu Wang, and Tiffany Bao.

Dirk ReiserView profile

Researcher

• Plasma Physics
• Numerical Methods
• Plasma Transport
• +10 more

Dr. Dirk Reiser serves as Team Leader for "Theory and Numerical Simulations" at Forschungszentrum Jülich, specifically within the Plasma Physics (IFN-1) group of the Institute of Fusion Energy and Nuclear Waste Management. His research focuses on advancing computational methods for plasma physics and fusion energy applications, with particular emphasis on plasma edge physics and divertor operation in tokamak devices. Dr. Reiser's expertise spans multiple critical areas of computational plasma physics: Numerical Methods and Partial Differential Equations for plasma modeling Plasma Transport and Turbulence analysis using advanced computational techniques Statistical approaches including Bayesian Inference and Monte Carlo Methods Machine learning applications for plasma modeling and data analysis Plasma-material interactions and surface physics His research bridges theoretical plasma physics with practical computational approaches to solve complex fusion energy problems, particularly related to impurity transport, plasma edge physics, and divertor operation. He has made significant contributions to the EMC3-EIRENE simulation framework, which is widely used in the international fusion community for modeling plasma edge and divertor physics. Analysis of his recent publications (2021-2025) reveals a strong focus on applying advanced computational methods to fusion energy challenges, with increasing integration of artificial intelligence techniques alongside traditional physics-based modeling. His work demonstrates consistent contributions to major international fusion projects including ITER, ASDEX Upgrade, and JET, addressing critical challenges in plasma exhaust, impurity control, and plasma-material interactions essential for future fusion reactors. As a team leader at one of Europe's largest research institutions, Dr. Reiser oversees research efforts that contribute significantly to the international fusion energy research community. His work helps advance the physics basis for ITER operation and future fusion power plants, with particular emphasis on solving the complex plasma physics challenges at the boundary between hot plasma and material surfaces.

Christian PrauseView profile

Professor

• Software Engineering
• Cybersecurity
• Software Quality Assurance
• +5 more

Christian Prause is a Professor at the Institute for Information Systems (IEM) at Technische Hochschule Mittelhessen (THM). He supervises bachelor's and master's theses in software engineering and cybersecurity, emphasizing practical topics related to his research areas. Research Interests: Software Quality Assurance Cybersecurity Software Verification & Validation Agile and Hybrid Development Models Research Software Engineering Documentation & Knowledge Management His recent publications focus on software reliability in spaceflight, automated verification tools, gamification for coding standards, and hybrid development practices. He leads the Software Quality Engineering Laboratory and contributes to cybersecurity initiatives at THM. Professor Prause is actively involved in curriculum development, offering courses in cyber security, software engineering, IoT projects, and network security. He maintains regular office hours for student consultations in Friedberg.

Henrik WalterView profile

Professor

• Psychiatry
• Neuroscience
• Psychology
• +8 more

Henrik Walter is a Full Professor (W3) of Psychiatry with a focus on Psychiatric Neuroscience and Neurophilosophy at Charité – Universitätsmedizin Berlin. He serves as Director of the Mind and Brain Research Division and Deputy Medical Director (Research) at the Department of Psychiatry and Psychotherapy, Charité Campus Mitte. Walter is also a faculty member at the Berlin School of Mind and Brain , a faculty member of the Bernstein Computational Center Berlin , and a principal investigator at the Berlin Center for Advanced Neuroimaging . Clinical expertise: Schizophrenia and affective disorders Empirical research: Working memory, volition, reward mechanisms, emotion regulation, mentalization, imaging genetics, connectomics Philosophical research: Philosophy of mind, neurophilosophy, neuroethics, philosophy of psychiatry Research trends in his 15 most recent publications (2009-2024) emphasize connectome-based machine learning , dynamic network reconfiguration , self-control mechanisms , and predictive models for psychiatric relapse . His work explores the intersection of neural network organization , emotional processing , and philosophical frameworks in mental health. Walter oversees major projects including environMENTAL (data harmonization in large cohorts) and FOR5187 PREACT (personalized psychotherapy). His team actively trains students and researchers through internships, theses supervision, and doctoral programs.

Jan VogesView profile

Researcher

• Genomic Data Compression
• DNA Data Storage
• Bioinformatics
• +3 more

Dr. Jan Voges is a Research Group Leader at the Institute for Information Processing and the L3S Research Center at Leibniz University Hannover, where he leads the BioAI Lab. He has held previous research leadership positions at the same institution (2022-2024), CIMA University of Navarra (2024-2025), and maintains a visiting position at the Peter L. Reichertz Institute for Medical Informatics. Dr. Voges' research spans the intersection of computer science, genomics, and medical informatics, with a focus on: Developing AI methods for multi-omics data analysis DNA sequencing data compression and storage 3D genome reconstruction Single-cell RNA sequencing data modeling International standardization of genomic data His recent work demonstrates a strategic shift toward integrating artificial intelligence with genomic data analysis, particularly for medical applications. The development of Genie, the first open-source ISO/IEC encoder for genomic data, represents a significant contribution to genomic data standards. His research shows strong translational potential, bridging computational methods with clinical applications as evidenced by his P4D Dashboard project for depression cohort monitoring. Dr. Voges has received recognition for his work, most notably earning his Dr.-Ing. degree with distinction in 2022. His active participation in ISO/IEC standardization committees and collaborations with international institutions demonstrates the impact of his work beyond traditional academic boundaries. As a supervisor, Dr. Voges maintains a focused lab structure with 3 PhD students, emphasizing quality mentorship and opportunities for students to contribute to high-impact projects with real-world applications. His lab provides unique opportunities at the cutting edge of genomic data science, with exposure to international standardization processes and interdisciplinary collaborations.

Andreas HertenView profile

Researcher

• High-Performance Computing (HPC)
• GPU Programming
• Parallel Computing
• +6 more

Andreas Herten is a Researcher at the Jülich Supercomputing Centre (JSC) within Research Center Jülich GmbH. He serves as Co-Lead of the Novel System Architecture Design division and heads the ATML Accelerating Devices group, focusing on GPU programming, parallel computing, and high-performance computing (HPC) optimizations. Key Expertise: GPU programming, parallel algorithms, HPC systems, benchmarking, Python, LaTeX Research Focus: Accelerating scientific applications on GPUs, European exascale initiatives, AI workload evaluation, and heterogeneous computing architectures His recent publications highlight advancements in GPU-accelerated materials science, AI training on HPC systems, and exascale benchmarking. Herten contributes to projects like OpenGPT-X, JUPITER, and CARAML, with work spanning computational physics, environmental science, and machine learning applications.

Alexandre StrubeView profile

Researcher

• High-Performance Computing
• Parallel Computing
• Scientific Computing
• +2 more

Dr. Alexandre Strube is a researcher at the Jülich Supercomputing Center (JSC) within Forschungszentrum Jülich, Germany's largest interdisciplinary research institution and a member of the Helmholtz Association. The JSC operates some of Europe's most powerful supercomputers, providing critical computational infrastructure for scientific research across physics, chemistry, biology, climate science, and engineering disciplines. His research focuses on advancing computational methodologies through: High-Performance Computing (HPC) system optimization Parallel algorithm development for exascale architectures Scientific simulation frameworks for multiscale modeling Big data analytics pipelines for research datasets AI/ML integration in computational workflows The Jülich Supercomputing Center serves as Germany's national supercomputing hub, supporting over 1,000 research projects annually through cutting-edge hardware like the JUWELS system and specialized expertise in code optimization, data management, and emerging computing paradigms. As part of Europe's PRACE infrastructure, JSC enables large-scale simulations for international scientific collaborations. While specific details about Dr. Strube's advising activities are not publicly documented, researchers at JSC typically supervise doctoral candidates through the Jülich Graduate Academy and collaborate with university partners like RWTH Aachen. Grant funding for JSC researchers primarily flows through Helmholtz Association programs, European HPC initiatives like EuroHPC, and national funding bodies such as the German Research Foundation (DFG).

Laurie C MurphyView profile

Researcher

• Computer Science Education
• Programming Pedagogy
• Novice Programming
• +6 more

Laurie C Murphy is a researcher at Pacific Lutheran University, Tacoma, WA, USA, specializing in computer science education and pedagogy. Her work focuses on novice programming, debugging strategies, recursive algorithms, and student mindset theories. Her research explores student-centered learning , code explanation techniques , and assessment methodologies in programming education. Key topics include debugging strategies , self-theories in computing , and learning style comparisons between programming and mathematics. Recent publications (2017–2012) highlight trends in student-centered classroom practices debugging error analysis recursive/iterative comprehension code literacy assessments She collaborates with institutions like Grand Valley State University and College of Charleston on studies about instructional practices and programming education challenges.

Michael TeichmannView profile

Researcher

• Modeling intelligent systems
• Adaptive systems
• Learning mechanisms
• +2 more

Michael Teichmann is a Researcher at the Professorship of Artificial Intelligence, Department of Computer Science, Chemnitz University of Technology. He has held this position since April 2015, following his role as a PhD student (2012–2015) in the interdisciplinary Research Training Group 'Crossworlds,' which explored connections between virtual and real social environments in communication, emotions, sensomotorics, and learning. Education: Dr. rer. nat. in Artificial Intelligence (2018), Chemnitz University of Technology. Dissertation: 'A plastic multilayer network of the early visual system inspired by the neocortical circuit.' Major in Computer Science with minors in Artificial Intelligence and Operation Research (2004–2010), Chemnitz University of Technology. Research Focus: His work centers on biologically inspired computational models, including: Adaptive learning mechanisms in neural networks Visual perception and invariance learning Emotion-driven perceptual processing Robustness in intelligent systems under information loss Publication Trends: His 15 most recent articles demonstrate a consistent focus on neural plasticity, bio-inspired vision systems, and computational neuroscience. Key thematic clusters include Hebbian learning stabilization, spiking neural networks for image processing, emotion-computer vision intersections, and competitive learning for enhanced robustness in feature detection. Awards: University award for best computer science thesis (2010) Affiliations: He operates within the Professorship of Artificial Intelligence lab, contributing to projects on neural modeling and vision systems. His prior involvement in the 'Crossworlds' research group emphasized interdisciplinary collaboration between computer science and social sciences.