Find Academic Supervisors

• Computer Vision
• Machine Learning
• Adversarial Robustness
• +4 more

Jenny Schmalfuss is a Doctoral Researcher at the Institute for Visualization and Interactive Systems (VIS) within the Faculty of Computer Science, Electrical Engineering, and Information Technology at the University of Stuttgart. She is also a scholar of the International Max Planck Research School for Intelligent Systems (IMPRS-IS). Her research focuses on computer vision and machine learning, specifically investigating robustness of deep learning methods against distribution shifts and adversarial attacks. Her primary research interests include computer vision, machine learning, and the intersection of these fields with robustness analysis. She has made significant contributions to understanding weaknesses in vision language models and motion estimation techniques like optical flow. Her work explores how to quantify and improve model robustness through adversarial testing frameworks. Her publication record shows a strong focus on adversarial robustness in motion estimation, with multiple papers at top-tier conferences including CVPR, ICCV, and ECCV. Recent work includes the PARC framework for analyzing vision language models (CVPR 2025), Distracting Downpour for weather-based adversarial attacks (ICCV 2023), and foundational work on adversarial snow attacks (ECCV AROW 2022). Poster Award at ICVSS 2023 Best Paper Award at ECCV AROW Workshop 2022 Best SimTech Bachelor's thesis 2021 (supervised) Jenny actively supervises numerous Master's theses, Bachelor's theses, and research projects annually, focusing primarily on optical flow robustness, adversarial attacks, and motion estimation. She has also completed an internship with NVIDIA's Autonomous Vehicle Perception Research Group in Santa Clara, CA, USA from April to November 2024, and previously worked as a research intern at the National University of Singapore and University of Houston. She teaches regularly in the Computer Vision and Intelligent Systems program, organizing colloquia and supervising seminars on Recent Advances in Computer Vision since 2021. Her teaching portfolio includes coordinating tutorials for Computer Vision and Imaging Science courses.

• Music Informatics
• Sonification
• Digital Media Production
• +6 more

Professor Axel Berndt holds a Professorship for Modeling of Linked Virtual Data Spaces at Paderborn University's Musicology Seminar Detmold/Paderborn through KreativInstitut.OWL since 2023. His interdisciplinary work bridges musicology, computer science, and digital media, with appointments spanning multiple institutions including OWL University of Applied Sciences, University of Music Detmold, and Technischen Universität Dresden. His research focuses on music informatics , particularly sonification (data-to-sound conversion), AI in music composition , and human-technology interaction in musical contexts. Recent projects include coral reef sonification (winning the 2025 Data Sonification Award), Mozart Deconstructions using AI, and the BMBF-funded IdiN project developing digital sheet music systems for opera theaters. Professor Berndt's publication trends reveal a consistent focus on practical applications of music technology: 2024: FlowScore (MEI streaming), Arpeggiatorum (audio-controlled MIDI), Mozart Deconstructions 2023: Sonification as artistic composition technique, Generative Art Conference publications His scientific recognition includes: Data Sonification Awards 2025 - Climate Change Category for 'The Reef' BMBF DATIpilot Funding for IdiN project (2024) As Principal Investigator for the BMBF-funded IdiN project with Deutsche Oper Berlin, Professor Berndt leads research in human-technology interaction for cultural institutions. His lab develops practical solutions like Arpeggiatorum for pipe organs and the LOSCOPe system for opera score management, with strong industry connections to the games industry, organ building, and museum technology sectors. KreativInstitut.OWL serves as his primary research hub, fostering collaborations between OWL University of Applied Sciences, Detmold University of Music, and Paderborn University. Current projects include Interface Modules for Musical XR, OCANIA networked performances, and ASCIImage Rhapsody live coding installations.

Juri RappsilberView profile

Professor

• Proteomics
• Mass Spectrometry
• Protein Structure
• +4 more

Prof. Juri Rappsilber is a Professor at the Technical University of Berlin's Institute of Biotechnology and Group Leader of Research Unit E in the UniSysCat Cluster of Excellence. His affiliations include Visiting Professorship at Kyoto University (2017, JSPS Fellow) and Senior Research Fellowships at the Wellcome Trust (2009-2019). He leads the Rappsilber Laboratory, focused on developing mass spectrometry technologies to study protein structure and interactions. Research interests center on proteomics , crosslinking mass spectrometry , and protein-network analysis . Key areas include: Functional protein networks through co-regulation studies Chromatin dynamics and mitotic chromosome composition In-cell structural proteomics integrating deep learning Development of bioorthogonal catalysis for medical applications His publication record demonstrates consistent output in high-impact journals, with recent work emphasizing: Structural mechanisms of protein complexes (γ-tubulin, condensin) Crosslinking MS methodology innovation and error control Integration of AI with experimental structural biology Catalytic processes in bioinorganic systems Awards and honors: EMBO Membership (2021) BSPR Lectureship (2014) Einstein Professorship (2011) Wellcome Trust Senior Research Fellow (2009-2019) Marie Curie Excellence Fellow (2005-2010) He actively advises doctoral students, including DAAD Hilde-Domin Program recipients, and secures substantial funding through ERC Synergy Grants, Wellcome Trust awards, and national initiatives. The lab focuses on developing anti-cancer therapeutics and sustainable chemistry solutions while pursuing Green Lab Certification.

Mathias Sablé-MeyerView profile

Research Fellow

• Mechanistic implementation of compositional mental representation
• Geometry perception in humans and non-human primates
• Human reasoning and cognitive fallacies
• +5 more

Mathias Sablé-Meyer is a Postdoctoral Researcher at University College London's Sainsbury Wellcome Centre, working in Tim Behrens's lab. He completed his PhD under the supervision of Stanislas Dehaene at PSL/Collège de France and NeuroSpin, CEA, where he investigated humans' ability to manipulate highly abstract structures, particularly focusing on the perception of geometry. His research spans cognitive neuroscience, computational modeling, and experimental psychology, with a focus on understanding the mechanistic implementation of compositional mental representations. He employs methodologies including MEG, fMRI, behavioral experiments, and computational models to investigate how humans mentally represent abstract structures like geometric shapes, language, and mathematical concepts. Sablé-Meyer's work reveals fascinating insights about human cognitive uniqueness, particularly in geometric perception compared to non-human primates. His recent research examines sequence processing mechanisms and aims to establish foundations for mechanistic implementations of Language of Thought models. He has published in top journals including Cognitive Psychology , Trends in Cognitive Sciences , PNAS , and Journal of Neuroscience . Glushko Dissertation Prize from the Cognitive Science Society (2023) As a supervisor, he co-advises Master's students including Maxime Cauté, who is exploring cross-modal representation of sequences, and is involved with several other students including Svenja Kuchenhoff, Amy Wong, and others. His lab follows open science principles, with code systematically published on the Open Science Framework alongside articles. His research program bridges cognitive science, neuroscience, and artificial intelligence, with implications for understanding both human cognition and developing more human-like AI systems. He maintains active collaborations across institutions including UCL, Collège de France, MIT, and École Normale Supérieure.

Jessica EkomaneView profile

Lecturer

• Sound Studies
• Sonic Arts
• Computer Music
• +5 more

Jessica Ekomane is a French-born and Berlin-based electronic musician and sound artist serving as Lecturer in Sound Studies and Sonic Arts at Berlin University of the Arts. Her work explores the transformative potential of sound through quadraphonic performances that examine the relationship between individual perception and collective dynamics. Her research interests focus on: The societal roots of listening expectations Psychoacoustic phenomena and cathartic effects The interplay of rhythmic structures, noise and melody Sound as a social practice and transformative element Non-Western sound synthesis and traditional practices Ekomane's artistic output reveals consistent exploration of spatial audio and perception, with recent works like 'Manifolds' (2024) demonstrating her evolving approach to immersive sonic landscapes. Her compositions often unfold as 'static situations in which change happens not in sequences, but in the slowly shifting relationship between elements,' creating psychoacoustic experiments that carry 'the possibility of catharsis and emancipation.' Her notable achievements include: Villa Romana Prize 2023 ZKM Giga-Hertz production prize 2023 Berlin Artistic Research Programme fellowship (2024-25) Selection for German Pavilion at 2019 Venice Biennale Ekomane has presented her work internationally at prestigious venues including CTM Festival (Berlin), Ars Electronica (Linz), Dommune (Tokyo), Bemis Center for Contemporary Arts (Omaha), Berghain, Cafe OTO, Hamburger Bahnhof, Reina Sofia, Art Basel, KW, and Villa Massimo. Her practice combines technical expertise with social inquiry, particularly examining how sound can challenge listening conventions and create new collective experiences.

Lukas GrundmannView profile

Lecturer

• Sound Studies
• Sonic Arts
• Generative Music
• +3 more

Lukas Grundmann serves as Lecturer and Technical Equipment / Studio Administrator for the Master's programs in Sound Studies and Sound Studies and Sonic Arts at Berlin University of the Arts, operating under the Central Institute for Continuing Education and Transfer. He provides consultation and equipment rentals through the Tech Lab with designated hours on Wednesdays and Fridays (1:30-3:00 p.m.) and appointment-based support. His educational background includes: Cultural Studies and Digital Media at Leuphana University Lüneburg Sound Studies at Berlin University of the Arts Grundmann's research investigates fundamental relationships between medium and message, signal and noise, and temporal dimensions of sound. His work bridges theoretical frameworks in Media Theory with practical applications in Sonic Arts and Generative Music, emphasizing how sound functions as both communication vehicle and artistic material. This interdisciplinary approach connects Cultural Studies perspectives with contemporary Digital Media practices. Professionally, he co-hosts the radioshow "Chronopolis" on Cashmere Radio focusing on algorithmic composition, while managing technical infrastructure for student studios. His operational role ensures practical resources align with academic curriculum requirements in sound-based programs.

Albert AnsmannView profile

Associate Professor

• Atmospheric Remote Sensing
• Lidar Technology
• Aerosol-Cloud Interactions
• +4 more

Dr. Albert Ansmann is a distinguished Associate Professor at the University of Leipzig and Head of the Ground-Based Remote Sensing Working Group at the Leibniz Institute for Tropospheric Research (TROPOS) in Leipzig, Germany. His career spans over three decades dedicated to advancing atmospheric remote sensing technologies and understanding aerosol-cloud interactions. At TROPOS, he leads the Ground-based Remote Sensing Group within the Department of Remote Sensing of Atmospheric Processes. Leibniz Institute for Tropospheric Research (TROPOS): Head of Ground-Based Remote Sensing Working Group since 1992 University of Leipzig: Associate Professor since 2005, Private Lecturer since 1999 Max Planck Institute for Meteorology: PhD research (1984-1988) Research Center Geesthacht: Postdoctoral researcher (1989-1992) Dr. Ansmann completed his Meteorology studies at the University of Hamburg (1977-1984) and earned his PhD from the Max Planck Institute for Meteorology in Hamburg (1984-1988). He achieved his Habilitation at the University of Leipzig in 1999, which qualified him as a university professor. His research focuses on developing lidar instruments and methodologies for investigating aerosols, clouds, and aerosol-cloud interactions, with particular emphasis on heterogeneous ice formation processes. His work has significantly advanced our understanding of mineral dust transport, Saharan aerosol long-range transport, and their impacts on cloud microphysics and climate. Dr. Ansmann's research integrates field campaigns across diverse geographical regions including Portugal, Morocco, Cape Verde, and the Arctic. The 15 most recent publications reveal a strong focus on Arctic atmospheric processes, wildfire smoke impacts on cirrus formation, mineral dust properties, and advanced lidar methodologies. His research increasingly addresses climate-relevant questions through international collaborations such as the MOSAiC expedition, SALTRACE, and BACCHUS projects, demonstrating a shift toward understanding the climate implications of aerosol-cloud interactions in polar regions. Inaba Prize (1994) for outstanding research on Raman lidar observation of the stratospheric Pinatubo aerosol layer American Geophysical Union Editor's Citation for Excellence in Refereeing (2005, 2010) Dr. Ansmann has been actively involved in mentoring doctoral students through seminars at TROPOS and lectures on active remote sensing at the University of Leipzig. His research has been supported through numerous international projects including SALTRACE, BACCHUS, and participation in major field campaigns across Europe, Africa, and polar regions. He has served on scientific steering committees, including the EU BACCHUS Project (2013-2017), and as guest editor for Atmospheric Measurement Techniques (2013-2015). The Ground-based Remote Sensing Group at TROPOS, which Dr. Ansmann leads, operates advanced lidar systems for atmospheric observations and participates in international networks like EARLINET. His team's work integrates ground-based, airborne, and satellite observations to address fundamental questions about aerosol-cloud interactions and their climate implications, with particular focus on polar regions through the MOSAiC expedition and related research.

Luciano BaresiView profile

Professor

• Software Engineering
• Self-Adaptive Systems
• Edge Computing
• +5 more

Luciano Baresi is a Full Professor at the Polytechnic University of Milan (Politecnico di Milano), Italy, affiliated with the Department of Electronics, Information and Bioengineering. He earned his laurea (MSc) and PhD in Computer Science from the same institution and has held visiting positions at the University of Oregon (USA), Tongji University (China), and the University of Paderborn (Germany). His research spans software engineering, with current focuses on self-adaptive systems, edge computing, and AI/ML-based software. His work integrates formal methods with practical applications, emphasizing autonomous systems, cloud-edge continuum, and federated learning. Recent publications highlight AI-driven advancements in software testing, resource optimization, and educational tools. Key research themes include: AI/ML for autonomous driving testing and data augmentation Serverless computing at the edge Federated learning system architectures Containerization and cloud resource management Awarded for impactful contributions: RE 2020 Most Influential Paper ICSOC 2020 Best Paper SEAMS 2022 Best Paper He advises 14+ PhD students and leads projects like Ketonet (health app), WHO's Essential Items Estimator, and dynaSpark. As Editor-in-Chief of Proceedings of the ACM on Software Engineering and senior editor for multiple journals, he shapes academic discourse in adaptive systems and software engineering.

• Software Evolution
• Empirical Software Engineering
• Domain-Specific Languages
• +2 more

Thomas Degueule is a researcher at CNRS (Centre National de la Recherche Scientifique) in France, actively contributing to software engineering research since 2015. He serves on program committees for major conferences including ASE, ICSE, and SLE, with primary research interests in Software Evolution, Empirical Software Engineering, and Domain-Specific Languages. His work focuses on breaking change analysis in APIs and libraries, client-library compatibility testing, and dependency management. He develops practical tools like Roseau for source-based breaking change detection and investigates semantic versioning impacts in ecosystems like Maven Central. His empirical approach leverages large-scale repository analysis to address real-world software maintenance challenges, particularly in Java ecosystems. Recent publications (2023-2025) show consistent contributions to breaking change analysis and compatibility testing, appearing in top venues like ASE, ICSE, and ISSTA. His research bridges theoretical insights with practical tooling for software evolution challenges, demonstrating strong empirical methodology and tool-oriented contributions. No scientific awards are documented in the available information. Degueule has advised no publicly listed students and holds no mentioned research grants. His organizational roles include Program Co-Chair for SLE 2023 and committee positions across multiple conferences, reflecting significant service to the software engineering community.

Đorđe ŽikelićView profile

Assistant Professor

• Formal Methods
• Program Analysis and Verification
• Trustworthy AI
• +5 more

Đorđe Žikelić is an Assistant Professor of Computer Science at the School of Computing and Information Systems at Singapore Management University (SMU) in Singapore. He completed his PhD in 2023 at the Institute of Science and Technology Austria (ISTA) under Krishnendu Chatterjee and Petr Novotný, receiving both Outstanding PhD Thesis and Outstanding Scientific Achievement awards. Prior to his doctorate, he earned bachelor's and master's degrees in mathematics from the University of Cambridge. His educational background includes: PhD in Computer Science, Institute of Science and Technology Austria (ISTA), 2023 Bachelor's and Master's in Mathematics, University of Cambridge Dr. Žikelić's research focuses on advancing formal methods to ensure software and AI systems are correct, safe, and trustworthy. His work bridges theoretical aspects of formal reasoning about probabilistic systems with practical automated verification methods. His primary research interests span three interconnected areas: Program Analysis and Verification: He develops techniques for analyzing probabilistic programs, numerical programs, and efficient quantifier elimination methods, addressing fundamental challenges in verifying complex software systems. Trustworthy AI and Safe Autonomy: He creates formal verification frameworks for learning-enabled control systems and neural networks, ensuring AI operates safely in uncertain environments through methods like runtime monitoring and certificate repair. Probabilistic System Verification: He explores broader applications including bidding games on graphs and blockchain protocol analysis, extending formal methods to novel domains beyond traditional finite-state verification. His publication trajectory shows a consistent progression from theoretical foundations to practical applications, with recent work increasingly focused on integrating formal verification with machine learning. His 2024-2025 publications demonstrate growing expertise in verifying learning-based systems and developing practical tools like PolyQEnt for quantified entailment solving. His scientific achievements have been recognized with: Outstanding PhD Thesis Award at ISTA Outstanding Scientific Achievement Award at ISTA Distinguished Paper Award at FM 2024 Dr. Žikelić serves on program committees for major conferences including TACAS, PLDI, AAAI, and CAV. He actively mentors through the Programming Languages Mentoring Workshop (PLMW) at PLDI 2025. His research group at SMU focuses on developing novel algorithms for verifying correctness of programs and AI systems, with current projects spanning formal methods, artificial intelligence, and programming languages.