Find Academic Supervisors

Manfred SchochView profile

Professor

• Digital Workplace
• IT Enterprise Architecture
• Strategic IT Management
• +3 more

Prof. Dr. Manfred Schoch serves as Professor of Business Informatics at Esslingen University of Applied Sciences' Faculty of Computer Science and Information Technology. He concurrently holds leadership roles at Fraunhofer FIT's Business Informatics branch and directs the FIM Research Institute for Information Management. His career bridges academic research with industrial digital transformation projects across sectors including transportation, finance, and manufacturing. His educational foundation includes: Summa cum laude doctorate from University of Hohenheim focusing on digital workplace communication technologies M.Sc. in Information-Oriented Business Administration and B.Sc. in Business Informatics from University of Augsburg Academic exchange at University of Pittsburgh's Joseph M. Katz Graduate School of Business Prof. Schoch's research centers on three interconnected domains: technology implementation in digital workplaces, strategic IT management and enterprise architecture, and data-driven workflow automation. He employs mixed-method approaches combining quantitative network/survey analysis with qualitative interview techniques to examine technology's organizational impact. Recent work investigates pandemic-driven remote work adaptations, AI integration challenges, and behavior change support systems for workplace stress management. His publication trajectory (2022-2025) reveals intensifying focus on generative AI applications, digital workplace resilience, and ethical technology adoption. Key themes include human-AI collaboration models, technostress mitigation, and CSR-guided digitalization. His work appears in premier venues like European Journal of Information Systems and ICIS proceedings. Professional recognition includes: Hohenheim Teaching Prize (2022) for innovative digital management pedagogy He actively supervises student theses through industry-collaborative projects with companies including DB Fernverkehr and Allianz. His research funding stems from Bavarian consortium initiatives like ForDigitHealth and international partnerships with MIT and Microsoft Research. Current grants focus on sustainable hybrid work models and AI-enhanced decision systems. As FIM Research Institute director, he leads cross-disciplinary teams developing practical digital transformation frameworks. The institute maintains strong industry connections through its Digital Leadership Academy and applied consulting projects addressing real-world challenges in workflow automation and IT-business alignment.

Ashwin RamView profile

Researcher

• Human-Computer Interaction
• Wearable Computing
• Augmented Reality
• +4 more

Ashwin Ram is a postdoctoral researcher at Saarland University's Human-Computer Interaction & Interactive Technologies Lab, under Prof. Jürgen Steimle. He holds a PhD in Computer Science from the National University of Singapore (NUS), advised by Prof. Shengdong Zhao, and a Bachelor's in Electronics Engineering from NIT Trichy. His research focuses on wearable augmented reality, smart glasses, and accessibility, leveraging cognitive and behavioral theories to design intelligent interfaces. Notable contributions include Mindful Moments (DIS '23, Honorable Mention), a mindfulness tool for smart glasses, and a quadruped robot guidance system for visually impaired individuals (CHI '24, Honorable Mention). He has served as an Associate Chair (AC) for UIST 2025 and CHI 2025. His work bridges HCI with wearable computing, exploring topics like video learning optimization (LSVP, IMWUT '21), sound source localization via neural networks (NCC '18), and accelerating Hawkes processes for event modeling (ICML '17 workshop). He collaborates internationally, including a research visit at UCL's Multi-Sensory Devices Group. Key achievements include 17 peer-reviewed publications (Google Scholar, ORCID: 0000-0003-1430-8770) and interdisciplinary projects like semantic floor map-based robot navigation. Beyond academia, he practices Carnatic music, plays guitar, and is fluent in Malayalam, Tamil, and English, with proficiency in French, German, and Hindi.

Sabine C. LangerView profile

Professor

• Acoustics
• Modeling and Simulation
• Numerical Acoustics
• +7 more

Prof. Dr.-Ing. Sabine C. Langer is a Full Professor of Acoustics and Director of the Institute of Acoustics at Technische Universität Braunschweig. She holds a PhD in Engineering and has extensive experience in academia, including leadership roles such as President of the Deutsche Gesellschaft für Akustik (DEGA) and Deputy Speaker of the DFG Collaborative Research Center 880 (SFB 880). Her research focuses on acoustics, numerical modeling, aircraft noise reduction, and innovative materials for sound absorption. She has pioneered studies on acoustic black holes, metamaterials, and AI-driven design optimization. Langer’s work also includes contributions to educational platforms, such as developing MATLAB-based sound quality analysis tools and online learning resources for engineering students. Education: Civil Engineering degree (1991–1996, TU Braunschweig), PhD in Engineering (2001, TU Braunschweig). Key positions include W2 Professor for Vibroacoustics (2013–2018) and Junior Professor for Wave Propagation and Building Acoustics (2003–2013). She led the Graduate School at SFB 880 and advised numerous research initiatives in structural acoustics and noise mitigation. Research interests span numerical acoustics, sound quality assessment, and sustainable acoustic design. Her recent work emphasizes AI integration in engineering design, stochastic modeling, and additive manufacturing of acoustic materials. She has published extensively on aircraft cabin noise prediction, vibration isolation, and metamaterial applications. Professional roles include membership in the DIN/VDI Normenausschuss Akustik and the Advisory Board of the Excellence Cluster Hearing4All. She has organized major acoustics conferences, including DAGA 2020 in Hannover, and contributed to standard-setting in noise reduction and vibration technology.

• Database Systems
• Distributed Systems
• Cloud Computing
• +4 more

Dr. Kenneth Salem is a Professor at the University of Waterloo, Canada , with a distinguished career spanning over three decades in database systems, distributed computing, and data management. His work has significantly influenced transaction processing, replication, and scalability in modern databases. Institution: University of Waterloo Collaborations: Frequent co-author with Hector Garcia-Molina, Ashraf Aboulnaga, Umar Farooq Minhas, Khuzaima Daudjee Research Interests: Dr. Salem’s research focuses on database systems, particularly in transaction processing , distributed databases , cloud computing , and energy-efficient data storage . He has pioneered techniques for schema design in NoSQL , adaptive caching , and RDMA-based data transfer . His work often addresses challenges in high availability , workload-aware optimization , and cardinality estimation . Recent Article Trends: His latest publications (2023-2025) explore ad hoc transactions , eventual durability , and summary-based cardinality estimation , emphasizing practical solutions for real-world database scalability and consistency. Earlier works (2018-2022) covered memory power optimization , RDMA abstractions , and workload-aware CPU scaling , reflecting a sustained focus on performance and efficiency. Advising and Collaborations: Dr. Salem has mentored numerous co-authors in database research, including Ashraf Aboulnaga, Umar Farooq Minhas, and Khuzaima Daudjee. His collaborative projects span Apache Spark caching , RemusDB high availability , and DimmStore memory optimization . Labs and Teams: He has been a key contributor to the DaMoN and Versatile Database Systems workshops, focusing on hardware-aware database design. His work with teams at Waterloo and collaborations with institutions like ETH Zurich and MIT has advanced self-managing databases and edge replication technologies.

Andrea BarthView profile

Professor

• Stochastic Partial Differential Equations
• Uncertainty Quantification
• Monte Carlo Methods
• +4 more

Andrea Barth is a W3-Professor of Computational Methods for Uncertainty Quantification at the University of Stuttgart, leading the Research Group for Computational Methods for Uncertainty Quantification within the Excellence Cluster for Simulation Technology. She holds a Ph.D. from the University of Oslo (2009) and has held positions at ETH Zürich and the University of Stuttgart. Her work focuses on stochastic partial differential equations, numerical methods for uncertainty quantification, and applications in engineering and natural sciences. Education: Ph.D. in Mathematics, University of Oslo (2006–2009) Lecturer/Postdoc at ETH Zürich (2010–2013) Junior Professor at University of Stuttgart (2013–2017) Research Interests: Stochastic PDEs, uncertainty quantification, Monte Carlo methods, Bayesian inverse problems, and numerical analysis of random fields. Her work bridges stochastic analysis and numerical simulations, addressing challenges in modeling and simulating complex systems with uncertainties. Grants & Funding: Principal Investigator in projects like 'Data-Integrated Simulation Science' (ExC 2075) and 'Quantitative Methods for Visual Computing' (SFB/TRR 161). Her research also explores applications in porous media, carbon dioxide storage, and optical flow analysis. Supervision: Advised PhD students including Oliver König, Fabio Musco, and Robin Merkle. Current students focus on topics like deep learning for stochastic PDEs and continuous level Monte Carlo methods.

Christine GerberView profile

Research Fellow

• Digitilization of work
• Precarious work
• Labour process and control
• +3 more

Dr. Christine Gerber is a Research Fellow at the WZB Berlin Social Science Center, specializing in the sociology of work and digitalization. She leads research in the group 'Globalization, Work, and Production,' focusing on platform work, labor processes, and Industry 4.0. Her recent projects include 'Generative AI in the world of work (GENKIA)' (2024–2026) and 'Automation, digitization and virtualization in the world of work during the pandemic' (2021–2023). Education: M.A. in International Relations (Free University Berlin/Humboldt University Berlin/University of Potsdam, 2011–2014); B.A. in Liberal Arts and Sciences (University College Maastricht/Santiago de Chile, 2007–2010). Dissertation: 'Platform work and the future of work' (defended January 2023). Research interests include digitalization's impact on labor, precarious work dynamics, and the transformation of work processes through algorithmic systems. Key topics: platform economy, wearable technologies in manufacturing, and post-pandemic labor market shifts. Collaborations: Extensive co-authorship with Martin Krzywdzinski and colleagues on digital labor studies. Key publications address AI's role in workplace change, pandemic-driven digitalization trends, and comparative analyses of platform work in Germany and the U.S. Her work bridges social theory and empirical research, emphasizing policy implications for digital labor markets. Current projects explore generative AI's societal impact and labor control mechanisms in crowdwork platforms.

Sisi FanView profile

Researcher

• DNA Nanotechnology
• Synthetic Biology
• Biosensors
• +3 more

Sisi Fan is a Researcher at the 2nd Physics Institute, University of Stuttgart, specializing in DNA nanotechnology and synthetic biology. Her work focuses on engineering DNA-based nanoscale systems for applications in materials science, biomedicine, and molecular computing. Her research interests include DNA origami structures, programmable molecular systems, and their integration into synthetic cells and diagnostic platforms. Notable projects involve reconfigurable DNA networks for membrane engineering and spatiotemporal control of biochemical reactions. Recent publications highlight advancements in DNA-based photonic materials, enzyme-free catalytic circuits, and nanomedicine applications using gold nanostars for targeted therapy. She explores interdisciplinary interfaces between nanotechnology and cell biology, with contributions to cellular nanomechanics and immune response modulation via nanoparticle systems. Dr. Fan collaborates with interdisciplinary teams to advance nanotechnology-driven solutions in diagnostics, therapeutics, and biomaterials. Her lab at the University of Stuttgart emphasizes both fundamental research and translational biomedical applications.

Volker RodehorstView profile

Professor

• Computer Vision
• Image Analysis
• 3D Reconstruction
• +5 more

Univ.-Prof. Dr.-Ing. habil. Volker Rodehorst is a full professor of computer vision at Bauhaus-Universität Weimar, holding positions in both the Faculty of Media and Faculty of Civil Engineering. His research focuses on photogrammetric computer vision, image analysis, 3D reconstruction, and structural health monitoring with applications in civil infrastructure inspection and urban modeling. He leads projects like ev.AI.luate and InfraCloud, leveraging AI and UAS technologies for infrastructure assessment. Education: PhD (2003): Technical University of Berlin, Faculty of Civil Engineering & Applied Geosciences Habilitation (2013): TU Berlin, Faculty of Electrical Engineering & Computer Science Computer Science Diploma (1994): TU Berlin Research Interests: UAS-based structural inspection using multi-view stereo and deep learning Crack detection and segmentation in concrete structures Automated building age estimation for energy modeling Flight path planning optimization for complex structures Integration of computer vision into BIM workflows Publications: Recent work emphasizes robust algorithms for crack detection (Omnicrack30k benchmark), UAS flight path optimization, and semantic segmentation challenges in bridge inspections. Key contributions include MVCrackViT and CISOL datasets advancing structural analysis methodologies. Awards: Best Academic Performance Prize (1994) - TU Berlin ISPRS Presidential Citation (2008) for WG III/2 leadership Grants & Labs: Leads Bauhaus' 3D-RealityCapture-ScanLab and coordinates EU projects like AISTEC-PRO. Active in developing modular solutions like smoodPLAN for infrastructure inspection. Teaching: Offers courses in photogrammetric computer vision, geodesy, and parallel systems. Supervises PhD students in structural health monitoring and computer vision.

Hamid ZargariaslView profile

Researcher

• Computer Networks
• IoT and Sensor Technology
• RFID Systems
• +3 more

Dr. Hamid Zargariasl is a Researcher in the Computer Engineering Department at BTU Cottbus-Senftenberg. His work focuses on IoT systems, RFID technology, social network analysis, and distributed computing. He leads the UBICO Team and contributes to the Computer Engineering Group, exploring interdisciplinary applications of telecommunications and sensor networks. His research integrates theoretical frameworks with practical implementations, addressing challenges in smart city infrastructure, healthcare systems, and educational technology. Key research areas include optimizing RFID and sensor performance, analyzing social object interactions in IoT networks, and developing protocols for distributed computing. His experimental studies bridge academic performance metrics with mobile social network dynamics, and he has pioneered methodologies for network integration and centrality analysis in evolving systems. Publications span 15 years (2009–2024), emphasizing real-world data analysis and system optimization. Notable work includes enhancing digital thread functionality in aerospace engineering and evaluating smart parking sensor technologies. His contributions inform both technical systems and socio-economic policy recommendations. Dr. Zargariasl collaborates within interdisciplinary teams, contributing to the BTU's research initiatives while maintaining active engagement in the academic community through lectures and student mentorship.

Athanasios AndreouView profile

Researcher

• AI Ethics
• Cybersecurity
• Data Privacy
• +3 more

Athanasios (Thanos) Andreou is a Postdoctoral Researcher at the NYU Tandon School of Engineering under Damon McCoy's team. He holds a PhD from Sorbonne Université (conducted at EURECOM), supervised by Patrick Loiseau and Oana Goga, and a Diploma (5-year) in Electrical and Computer Engineering from NTUA. His research focuses on AI ethics, cybersecurity, privacy, and e-crime, with a particular emphasis on auditing social media advertising ecosystems and transparency mechanisms. His academic journey includes a MSc in Communications & Computer Security from EURECOM. Key research interests span internet measurements, transparency in digital advertising, and mitigating privacy risks in social platforms. Notable contributions include developing the Facebook Ads Monitor tool and investigating privacy vulnerabilities in data brokers' interfaces. Publications: Over a decade of work, his publications address critical issues such as ad transparency limitations, privacy risks in Facebook targeting, and identity disclosure risks in multi-profile user scenarios. Awards: Winner of the 2020 CNIL-Inria Award, runner-up for the Caspar Bowden PET Award, and recipient of best paper runner-up at ASONAM 2017. His work bridges social media analysis with practical tools like AdAnalyst, aiming to enhance user awareness of targeted advertising practices. Current affiliations include NYU Tandon, with prior involvement at EURECOM and Sorbonne Université.

Robert RaussendorfView profile

Professor

• Quantum Information
• Measurement-Based Quantum Computation
• Quantum Fault-Tolerance
• +4 more

Robert Raussendorf is a Professor at the Institute of Theoretical Physics, part of the Faculty of Mathematics and Physics at Leibniz University Hannover. He leads the research group focusing on quantum information, particularly measurement-based quantum computation (MBQC) and quantum fault-tolerance. His work includes the invention of the one-way quantum computer (QCc), a paradigm where quantum computations are performed via local measurements on entangled cluster states. Raussendorf’s research bridges foundational quantum mechanics with practical applications, emphasizing the role of contextuality and resource states in quantum advantage. Research Interests: His primary areas include quantum computation models, quantum cellular automata, topological error correction, and the foundational aspects of quantum mechanics. He explores how quantum principles like entanglement and contextuality enable computational power, with recent focus on symmetry-protected systems and efficient quantum architectures. Articles Trends: Recent publications highlight advancements in measurement-based computation, error correction strategies, and theoretical frameworks like contextuality and cohomology. Notable work includes high-error-threshold architectures and the application of dual-unitary circuits in one-dimensional systems. Lab/Team: His team includes postdocs (e.g., Markus Frembs, Martin Plávala) and doctoral candidates (e.g., Arnab Adhikary, Ruben Campos Delgado), collaborating on topics like quantum error tolerance, computational phases of matter, and algorithm optimization. The group also engages in interdisciplinary projects with institutions like the Stewart Blusson Quantum Matter Institute.

Karl R. GegenfurtnerView profile

Professor

• Visual Perception
• Color Vision
• Cognitive Neuroscience
• +7 more

Prof. Dr. Karl R. Gegenfurtner is a full Professor for General Psychology at the Department of Psychology, Faculty of Psychology and Sports Science, Justus-Liebig-University Giessen. He has held this position since 2001 and leads a prominent research group on visual perception. His work bridges low-level sensory processing with higher cognitive functions and motor control. Education: Psychology Student at the University of Regensburg, Diploma in Psychology, 1986 Ph.D. in Experimental Psychology, New York University, 1990 Postdoc at Howard Hughes Medical Institute and Center for Neural Science, NYU, 1990–1993 Research Scientist at Max Planck Institute for Biological Cybernetics, Tübingen, 1993–2000 Habilitation in Medical Psychology and Behavioral Neurobiology, 1998 Professor for Biological Psychology, Otto-von-Guericke University Magdeburg, 2000–2001 His research focuses on the neural and cognitive mechanisms of visual perception, particularly color vision, object recognition, eye movements, and sensorimotor integration. He investigates how humans perceive complex scenes and objects in natural environments, how these are represented in the brain, and how visual information guides motor actions. His recent work explores topics such as color categorization in neural networks, lightness perception, dynamic size recalibration, and the role of eye movements in perceptual decisions. The 15 most recent articles reflect a strong trend toward understanding perception in real-world contexts, integrating computational modeling, psychophysics, and neuroscientific methods. Key themes include color and shape perception, attention, eye movement control, and the interplay between perception and action. Scientific Awards: Member, German National Academy of Sciences Leopoldina (2015) Wilhelm Wundt Medal, German Society for Psychology (2016) Palmer Lecture, Colour Group (UK) (2019) Turrell Lecture Berlin (2019) Russell Devalois Memorial Lecture, UC Berkeley (2024) ICVS Verriest Medal (2024) Pineapple Science Award (2024) Prof. Gegenfurtner has supervised numerous research projects and training networks, including the DFG Collaborative Research Center TRR 135 on 'Cardinal mechanisms of perception' and the International Research Training Group BrainAct. He has received major funding, including an ERC Advanced Grant (2020) for 'Color 3.0'. He has served on editorial boards of top journals such as Journal of Vision , Vision Research , and Psychological Review , and was President of the Vision Science Society (2012–2013). He is actively involved in academic service, including the Alexander von Humboldt Foundation’s fellowship selection committee. He leads the Visual Perception research group at Giessen, which investigates cortical mechanisms of vision, perception of natural scenes, and the integration of sensory and motor information. The lab employs psychophysical experiments, eye tracking, computational modeling, and neuroimaging to study perception in ecologically valid settings.

Sven ApelView profile

Professor

• Software Engineering
• Software Variability and Configuration
• AI-based Program Generation and Optimization
• +7 more

Sven Apel is Professor of Computer Science at Saarland University, where he holds the Chair of Software Engineering and directs the Saarbrücken Graduate School of Computer Science within the Saarland Informatics Campus. His research aims to advance software engineering into an era of intensive automation by developing methods, tools, and theories for building efficient, reliable, and maintainable software systems, with a strong emphasis on the human factor and interdisciplinary inquiry. His primary research interests include software variability and configuration, AI-based program generation and optimization, socio-technical software analysis, and the application of empirical and neurophysiological methods to study program comprehension. He actively collaborates with industry partners such as Siemens AG, Bosch Engineering, and Airbus Helicopters to apply his research in real-world contexts. His recent publications demonstrate a strong trend towards integrating artificial intelligence and neurocognitive methods into software engineering, focusing on configurable systems, performance modeling, debugging processes, and the scientific validity of empirical studies. His work spans top venues like ICSE, FSE, ASE, and IEEE TSE. ERC Advanced Grant “Brains On Code” ASE Fellow ACM Distinguished Member Hugo Junkers Award for Research and Innovation Heisenberg Professorship (DFG) Emmy-Noether Fellowship (DFG) Best Doctoral Dissertation Awards (University of Magdeburg, Ernst-Denert Foundation, 2007) Most Influential Paper Awards (SPLC'19, ICPC'22, GPCE'23) ACM SIGSOFT Distinguished Paper Awards (ICSE'15, ICSE'21) Best Paper Awards (SPLC'11, Modularity'15, Academy of Management'18) Distinguished Reviewer Awards (ASE'18, ICSE'24, FSE'24) Sven Apel has secured significant research funding, including an ERC Advanced Grant (€2.5M) and multiple DFG grants as Principal Investigator and Project Leader. He has advised numerous PhD and Master’s students and is actively involved in the academic community through program committees for major conferences like ICSE, FSE, and ASE. His work is conducted within a collaborative environment that includes close partnerships with researchers at the Max Planck Institute for Informatics and other institutions within the Saarland Informatics Campus.

Christof RöhrigView profile

Professor

• Robotics
• Mobile Robotics
• Wireless Sensor Networks
• +3 more

Christof Röhrig is a Professor at the FH Dortmund - University of Applied Sciences and Arts , conducting research at the Institute for the Digitalization of Work and Living Environments (IDiAL). He leads the Intelligent Mobile Systems Lab , focusing on robotics, wireless sensor networks, and kinematic modeling. His research spans mobile robotics , indoor localization , and industrial automation , with a strong emphasis on IoT , 5G networks , and rescue robotics . Key trends in his recent work include LoRaWAN localization , modular robot design , and digital twin architecture . He collaborates extensively on motion control , sensor fusion , and energy-efficient systems , though no specific students, awards, or grants are listed in the provided data. The lab at IDiAL explores robotics in emergency response and industrial IoT applications , with a focus on precision localization and collaborative automation .

Jan PfisterView profile

Researcher

• Natural Language Processing
• Deep Learning
• Sentiment Analysis
• +5 more

Jan Pfister is a researcher at the Chair of Data Science (Informatik X) , affiliated with the Faculty of Mathematics and Computer Science at the University of Würzburg . Holding an M.Sc. in Computer Science from 2021, he contributes to the DMIR group while maintaining the BibSonomy platform. His work bridges Natural Language Processing and Deep Learning , with a focus on structured sentiment analysis and German language modeling. His research explores the integration of Large Language Models with Pointer Networks to extract fine-grained sentiment information. He has developed ModernGBERT , a German-only encoder model, and LLäMmlein , advancing NLP capabilities for the language. Pfister's recent publications highlight trends in encoder-decoder architectures, model-agnostic hallucination detection, and multi-label classification frameworks that refine LLM outputs. He has taught courses including Information Retrieval (SS '22), Text Mining (WS '23), and Selected Topics in Machine Learning (SS'21, WS '21, WS'24). His collaborative projects span medical informatics, human-AI interaction, and social media analysis, often involving interdisciplinary teams and real-world data.