Find Academic Supervisors

Alberto ZanardoView profile

Associate Professor

• Modal and Temporal logics
• Branching-time logics
• Fibring of logics
• +2 more

Alberto Zanardo serves as Associate Professor in Mathematical Logic within the Department of Mathematics at the University of Padua. His academic profile combines rigorous theoretical research with dedicated teaching across multiple mathematics programs. His research concentrates on: Modal and Temporal Logics, particularly Branching-time systems Fibring of Logics and combination methods Foundations and axiomatizations of scientific theories Mathematics Education and pedagogical frameworks Topological aspects of logical semantics Analysis of his 15 most recent publications reveals sustained contributions to temporal logic semantics, with significant work on branching-time structures, possible worlds quantification, and history-based models. His research demonstrates consistent output in premier logic journals (Studia Logica, Synthese) while maintaining strong international collaborations across Europe and South America. Methodologically, he bridges philosophical inquiry with mathematical rigor, often developing novel semantic frameworks for complex temporal phenomena. Teaching responsibilities span foundational courses including Axiomatic Method and Set Theory, Foundations of Mathematics, and Mathematics for Chemistry programs. His syllabi emphasize structural understanding through constructions like real numbers via homomorphisms and Peano axioms. All teaching materials are systematically organized through the University of Padua's Moodle platforms, reflecting his commitment to accessible mathematical education. Professor Zanardo maintains active research supervision and collaborates internationally, though specific grant details aren't publicly documented. His work continues to influence both theoretical logic and mathematics education through persistent scholarly output and pedagogical innovation.

Eleni GentekakiView profile

Associate Professor

• Microbial Diversity
• Microbial Ecology
• One Health
• +4 more

Dr. Eleni Gentekaki serves as an Associate Professor at the School of Veterinary Medicine, University of Nicosia, Cyprus, where she integrates veterinary science with advanced microbiological research through a One Health framework. Her work bridges human, animal, and environmental health with a focus on microbial ecology and emerging infectious diseases. Her academic credentials include: Bachelor of Science in Human Kinetics Master's degree in Immunology Doctor of Philosophy in Eukaryotic Microbiology from the University of Guelph, Canada Dr. Gentekaki's research centers on microbial diversity and ecology, with specialized expertise in protistan parasites (particularly Blastocystis), gut microbiome dynamics, and antimicrobial resistance. She employs multi-omics approaches including transcriptomics and metabolomics to investigate host-microbe interactions across diverse ecosystems. Her work consistently applies One Health principles to address complex challenges in infectious disease transmission and environmental health, with field studies conducted in Thailand, Iraq, Bangladesh, and Cyprus. Analysis of her recent publications (2023-2025) reveals a dominant focus on One Health applications, particularly in gut microbiome dynamics and protist ecology. Her research methodology emphasizes longitudinal field studies combined with advanced molecular techniques, often examining zoonotic transmission pathways and environmental reservoirs of pathogens. Geographical diversity characterizes her work, with significant contributions from Southeast Asia and the Eastern Mediterranean. No scientific awards were documented in the available information. While her extensive publication record indicates active research supervision, specific details regarding graduate student advising and research grant funding were not provided in source materials. Her collaborative publications suggest international research partnerships across multiple continents. The available documentation does not specify dedicated laboratory facilities or formal research teams, though her field-based studies imply coordination with local health authorities and veterinary services in study regions.

Ra GolanView profile

Lecturer

• Logic
• Philosophy of Logic
• Foundations of Logic
• +3 more

Dr. Ra Golan is a faculty member in the Department of Philosophy at the Faculty of Humanities and Social Sciences, Ben-Gurion University. He holds a doctorate in philosophy and conducts research on the foundations of logic, examining the validity of inferences and the relationship between descriptive and normative aspects of logical reasoning. His research focuses on the foundations of logic, specifically investigating when conclusions follow from premises and the significance of this derivation. Dr. Golan employs phenomenological analysis to explore how our perception of phenomena implicitly contains normative expectations that form the basis for logical inferences. His work bridges the gap between descriptive aspects of the world and the normative aspects of justification in logical reasoning. Dr. Golan's insight emphasizes that phenomena appearing obvious on the surface often reveal complex and counterintuitive dimensions when seriously examined. His research contributes to understanding how logical validity relates to both the structure of the world and normative standards of justification.

• Public Health Sociology
• Implementation Science
• Harm Reduction
• +5 more

Lyu Azbel serves as an Associate Research Scientist in the Department of Internal Medicine at Yale School of Medicine, specializing in Infectious Diseases with a focus on implementation science in high-risk settings. Their work primarily centers on the intersection of substance use disorders and infectious diseases, particularly among marginalized populations including incarcerated individuals and queer communities across Eastern Europe, Central Asia, Latin America, and South Asia. Azbel completed their PhD at the London School of Hygiene and Tropical Medicine in 2020. Their academic journey has led them to focus on qualitative methodologies to unpack the social dimensions of health interventions where drug use and infectious diseases intersect. Their research interests span public health sociology, implementation science, harm reduction strategies, and prison health systems. Azbel employs qualitative methods to investigate how medical interventions translate across different cultural and institutional settings, particularly focusing on the structural barriers to effective treatment implementation in resource-limited contexts. Their work has significantly contributed to understanding the social relations of treatment among people who use drugs and those living with HIV in correctional settings. Analysis of Azbel's publication record from 2013-2020 reveals a consistent focus on prison health systems, harm reduction, and the implementation of evidence-based interventions in challenging environments. Their research demonstrates strong interdisciplinary connections between infectious disease epidemiology, medical sociology, and implementation science, with particular emphasis on Eastern Europe and Central Asia. The publications show an evolution from descriptive studies of drug use patterns to more complex analyses of intervention implementation and the sociopolitical dimensions of treatment access. Azbel maintains active research collaborations with prominent scholars including Frederick Lewis Altice and Jeffrey A. Wickersham. Their work is closely affiliated with the J. Meyer Lab at Yale and contributes to several major research initiatives including the HIV & Aging Center for Implementation Science and projects focused on Eastern Europe/Central Asia. While specific grant funding isn't detailed in the provided information, their extensive publication record suggests significant research activity in prison health and harm reduction implementation. Their laboratory and team affiliations include the Infectious Diseases section of Yale's Department of Internal Medicine, with particular connections to the HIV & Aging Center for Implementation Science and the Malaysian Implementation Science Training (MIST) Program. Azbel's research contributes to Yale's broader initiatives in global health implementation science, particularly regarding substance use disorders and infectious diseases in correctional settings across multiple international contexts.

Clark BarrettView profile

Professor

• Formal Methods
• Automated Reasoning
• Verification
• +7 more

Clark Barrett is a Professor in the Department of Computer Science at Stanford University, where he conducts research in formal methods, automated reasoning, and verification. He is affiliated with several research centers including the Stanford Center for Automated Reasoning, Stanford Center for AI Safety, Stanford Agile Hardware Project, and Stanford Center for Blockchain Research. His research focuses on developing formal methods and tools for verifying complex systems, with particular emphasis on satisfiability modulo theories (SMT), verification of neural networks, hardware design verification, and security. His work bridges theoretical foundations with practical applications across multiple domains. Over the past decade, Barrett's research has evolved from foundational work in SMT solving to increasingly diverse applications including neural network verification, hardware verification, and AI safety. His recent publications demonstrate a strong focus on practical verification techniques for real-world systems, particularly in the areas of hardware design, neural networks, and programming languages. The trend shows an expansion from core verification techniques to broader applications in AI safety and secure systems design. 2021 CAV (Computer Aided Verification) Award Barrett leads several major research initiatives and collaborates extensively with industry partners. His work on the Marabou neural network verification framework, SMT-LIB standard, and Symbolic QED verification methodology have had significant impact in both academic and industrial settings. He has supervised numerous PhD students and postdoctoral researchers who have gone on to successful careers in academia and industry. He is a key member of the Stanford Center for Automated Reasoning, which develops foundational technologies for automated reasoning, and the Stanford Center for AI Safety, where he focuses on formal methods for ensuring the safety and reliability of AI systems. His work on the Stanford Agile Hardware Project aims to revolutionize hardware design through formal methods and verification techniques.

Frank KellerView profile

Professor

• Natural Language Processing
• Cognitive Science
• Computational Narrative
• +2 more

Frank Keller is a Professor in the School of Informatics at the University of Edinburgh, affiliated with EdinburghNLP, the Natural Language Processing Group. His research spans natural language processing, cognitive science, and computational narrative, with dual foci on language-vision integration and narrative modeling. Professor Keller's primary research encompasses natural language processing and cognitive science, specifically investigating language and vision tasks such as image description, visual grounding, video summarization, and visual story telling. His secondary focus involves computational narrative modeling, where he develops frameworks for analyzing characters, plot turning points, and suspense in long-form texts including movie scripts and books—addressing challenges in LLM comprehension of extended narratives. Recent publications (2023-2025) reveal strong trends in multimodal narrative generation, particularly visual story creation with grounded characters and movie script summarization. His work bridges cognitive modeling with practical NLP applications, exploring human reading mechanisms through neural attention models and advancing procedural video understanding through implicit argument prediction. Scientific Awards: EMNLP Best Paper Award (2002) Nominated for ACL Best Short Paper Award (2019) Professor Keller actively supervises eight current PhD students including Anil Batra and Gautier Dagan, and has mentored 26 alumni now at institutions like MIT, Google DeepMind, and Copenhagen University. His research receives substantial funding through the UKRI Centre for Doctoral Training in Designing Responsible NLP, supporting next-generation NLP researchers. As a core member of EdinburghNLP, he leads interdisciplinary teams collaborating with the Pioneer Center for AI and Copenhagen University. Current projects integrate cognitive science with multimodal learning, focusing on narrative structure analysis, visual grounding, and human-AI interaction systems for complex tasks like trailer creation and scientific poster summarization.

Johannes T. MargrafView profile

Professor

• Machine Learning in Chemistry
• Electronic Structure Theory
• Density Functional Theory
• +3 more

Prof. Johannes T. Margraf is a Professor and Chair of Physical Chemistry V: Theory and Machine Learning at the University of Bayreuth. His research group specializes in applying machine learning to chemical phenomena, including predicting properties of molecules and materials, understanding complex reaction networks, and developing data-efficient models that incorporate physical principles like size-extensivity and accurate descriptions of long-range interactions. The group also focuses on electronic structure theory, particularly bridging wavefunction and density functional methods. Margraf's research interests center on machine learning applications in chemistry and materials science, including non-local machine learning-based density functional theory, chemical reaction network analysis, and the development of physics-informed ML models. His work aims to achieve accurate chemical simulations at unprecedented scales for materials discovery and optimization. Analysis of recent publications shows a strong focus on machine learning potentials for materials simulation, density functional theory advancements, catalytic reaction networks, and computational spectroscopy. His research consistently integrates machine learning with fundamental physics principles to solve challenging problems in computational chemistry and materials science. Margraf leads a research team including postdoctoral researchers (Dr. Maciej Baradyn, Dr. Hyunwook Jung, Dr. Karlo Sovi´c) and PhD students (Nils Gönnheimer, David Greten, Konstantin Jakob, Sachin Rangaswamy, Robert Strothmann, Martin Vondrák). The group actively organizes scientific workshops and collaborates with institutions like the Fritz Haber Institute in Berlin.

• Computer Vision
• Natural Language Processing
• Sign Language Technologies
• +5 more

Gül Varol is a permanent researcher (equivalent to Associate Professor) at École des Ponts ParisTech, where she is part of the IMAGINE group within the Laboratoire d'Informatique Gaspard-Monge (LIGM). She holds additional affiliations as an ELLIS Scholar and a Guest Scientist at the Max Planck Institute (MPI). Her academic journey includes a postdoctoral position at the University of Oxford's Visual Geometry Group (VGG) under Andrew Zisserman, and a PhD from the WILLOW team at Inria Paris and École Normale Supérieure. Her educational background includes BS and MS degrees from Boğaziçi University, followed by doctoral studies at Inria Paris and École Normale Supérieure. During her PhD, she spent research periods at MPI, Adobe, and Google, gaining diverse industry and academic experience. Dr. Varol's research focuses on the intersection of computer vision and language processing, with particular expertise in video representation learning, human motion synthesis, and sign language technologies. Her work bridges theoretical advances with practical applications, especially in accessibility technologies like audio description for visually impaired audiences and sign language recognition systems. She has pioneered approaches for text-driven 3D human motion generation, sign language translation with contextual cues, and film-grammar-aware audio description generation. Her research often leverages large language models and vision-language models to solve complex multimodal problems without requiring extensive training data. Analysis of her recent publications reveals a clear trajectory toward more sophisticated multimodal systems that integrate temporal understanding, contextual awareness, and fine-grained control. Her work increasingly focuses on practical applications in accessibility, with significant contributions to sign language technologies and audio description systems. She has demonstrated leadership in developing large-scale datasets like BOBSL (BBC-Oxford British Sign Language Dataset) and advancing methods for zero-shot and training-free approaches that can be deployed without extensive fine-tuning. Her scientific achievements have been recognized with several prestigious awards: ELLIS 2020 PhD Award AFRIF 2019 PhD thesis award from the French association for pattern recognition Google Research Scholar award (2023) Best application paper award at ACCV'20 Dr. Varol has received significant research funding including an ANR JCJC project "CorVis" and research gifts from Google and Adobe. She actively mentors students and researchers, with prospective students encouraged to apply through her lab's application form. Her leadership in the academic community is evident through her service as Program Chair for ECCV'24, Senior Area Chair for CVPR 2025, and associate editor for the International Journal of Computer Vision (IJCV). She is a key member of the IMAGINE research group at École des Ponts ParisTech, which focuses on image analysis and computer vision. Her collaborative work extends to multiple institutions including MPI, Oxford, and various industry research labs. She has co-organized numerous workshops on specialized topics including sign language recognition, vision transformers, and foundation models for 3D humans, fostering community building in these emerging research areas.

Nima AlanView profile

Physician Scientist

• Spinal Surgery
• Neurosurgery
• Minimally Invasive Surgery
• +7 more

Dr. Nima Alan, MD is a neurosurgeon at the University of California, San Francisco (UCSF) Spine Center. He specializes in treating complex spinal conditions including herniated discs, spinal stenosis, scoliosis, spinal tumors, and traumatic injuries using both traditional and minimally invasive surgical techniques. His research focuses on improving clinical outcomes in spinal surgery. Medical Degree: Case Western Reserve University School of Medicine (2015) Residency: Neurosurgery at University of Pittsburgh Medical Center (2016-2022) Fellowship: Complex Spine Surgery at Barrow Neurological Institute (2023) Dr. Alan's research spans multiple areas of spinal surgery including biomechanical modeling, outcomes analysis, and technological innovation. He holds particular expertise in evaluating preoperative muscle quality, surgical positioning implications, and cost-effectiveness of spinal procedures. His recent publications (2024-2025) demonstrate a focus on clinical validation of musculoskeletal modeling, comparative effectiveness of interbody fusion techniques, AI applications in surgical planning, and age-related outcomes in spinal deformity correction. Key studies examine complication prevention in elderly patients, cost-efficiency metrics, and patient satisfaction determinants. North American Spine Society Research Award Society of Lateral Access Surgery Research Recognition Joint Section on Spine and Peripheral Nerve Disorders (AANS/CNS) Award

• Power Systems
• Electromechanical Systems
• Neural Networks in Power Engineering
• +2 more

Shylo Serhiy Ivanovych serves as a Senior Lecturer and head of the educational department at Zaporizhzhia Polytechnic National University's Electrical Engineering Faculty, Department of Electrical Machines. Holding a Candidate of Technical Sciences degree (PhD equivalent), he has been actively contributing to academia since 2004 after completing his Master's in Electromechanics at the same institution. His research spans Power Systems Engineering , Neural Network Applications in transformer diagnostics and medical imaging, and Air Traffic Control Systems . Notable collaborations include IEEE publications on university ecosystem development and predictive modeling for power oil-filled transformers. His work demonstrates strong interdisciplinary connections between electrical engineering, artificial intelligence, and transportation safety systems. Scientific contributions include: Neural network synthesis for medical diagnostics and CAD integration Information modeling for air traffic management Renewable energy integration models High-voltage equipment analysis As an educator, he teaches advanced courses including High Voltage Electrical Devices, Electromechanical Systems Modeling, and Power Electronics, while maintaining active research through ORCID, Scopus, and Web of Science profiles. His technical expertise bridges theoretical research with industrial applications in energy systems.

Juraj BenićView profile

Assistant Professor

• Control theory
• Fluid power systems
• Internet of Things (IoT)
• +7 more

Assistant Professor Juraj Benić is a control engineer at the School of Applied Mathematics and Informatics, Josip Juraj Strossmayer University of Osijek, Croatia . His interdisciplinary work bridges control theory, fluid power systems, IoT, and data-driven maintenance , with applications ranging from forestry vehicles to unmanned aerial systems. Education PhD in Control Theory and Mechanical Engineering, 2022 – University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture MSc in Control Theory and Mechanical Engineering, 2017 – University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture BSc in Control Theory and Mechanical Engineering, 2015 – University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture Research Interests Prof. Benić’s core research areas include: Energy-efficient direct-driven hydraulic (DDH) systems for mobile machinery Hybrid-electric powertrains for forestry skidders and multirotor UAVs IoT-enabled predictive maintenance using convolutional neural networks and vibration analysis Fuzzy-logic and ontology-based controllers for electro-hydraulic systems Human-robot interaction and context-aware robotics Computational linguistics and digital corpora of Croatian dialects Publication Trends Since 2018 he has produced more than 25 peer-reviewed works. The 2023-2024 journal articles focus on hybrid UAV propulsion and comparative energy efficiency of hydraulic systems , while earlier works delve into fuzzy control ontologies , predictive maintenance via IIoT and fuel-saving hybrid skidders . Interspersed linguistic contributions showcase his versatility in digital dialectology. Scientific Awards & Recognition While explicit awards are not listed, he has delivered invited lectures (University of Maribor, 2021) and participated in study visits (South Kazakhstan State University, March 2024), indicating growing international recognition. Supervision & Collaboration He collaborates closely with colleagues from the University of Zagreb and University of Osijek, co-authoring with researchers such as D. Pavković, Ž. Šitum, M. Cipek, and D. Brezak. Student supervision is implied through experimental rigs and project descriptions, although specific advisee names are not provided. Laboratory & Field Infrastructure Research is supported by fully instrumented hydraulic test benches, a retrofitted deep-drilling rig, IoT accelerometer networks, and field-measurement campaigns on commercial skidders equipped with telematics (WIGO-E) for long-term fuel and energy-data logging.

• Translation Studies
• Literary Translation
• Ottoman Turkish Translation History
• +7 more

Professor Ayşe Banu Karadağ is a distinguished academic at Yildiz Technical University, where she serves as Professor in the Faculty of Arts & Science, Department of Western Languages and Literature. She currently holds the position of Head of Department (since 2024) and is an Applied Research Center Board Member (since 2019). Previously, she served as Vice Rector of Yildiz Technical University (2020-2021). Her educational background includes a Doctorate from Istanbul University (2000-2003) in the Department of Western Languages and Literatures, a Postgraduate degree from Bogazici University (1995-1997) in Translation and Interpreting, and an Undergraduate degree from the same institution (1990-1995) in the same field. She possesses advanced proficiency in both French and English (C1 Advanced). Prof. Karadağ's research spans Translation Studies with particular focus on Ottoman Turkish translation history, literary translation, retranslation phenomena, crime fiction translation, and gender studies in translation. Her work examines how translation functions as a cultural mediator, particularly in historical contexts of the Ottoman Empire and early Turkish Republic. She investigates paratextual elements, intralingual translation processes, and the role of translation in nation-building and cultural identity formation. Analysis of her recent publications reveals consistent engagement with historical translation practices, particularly examining how Western literary works were adapted into Ottoman Turkish and later Turkish contexts. Her work demonstrates special interest in crime fiction translation, women translators in Turkish history, and the intersection of law and translation in Ottoman modernization. She frequently employs descriptive translation studies methodology while incorporating insights from cultural studies, gender studies, and historical linguistics. Prof. Karadağ has supervised 22 theses at doctoral and master's levels, mentoring students researching diverse topics within translation studies including crime fiction translation, retranslation phenomena, and historical translation practices. She serves as Editor of transLogos Translation Studies Journal (since 2018), contributing significantly to scholarly discourse in the field. Her scholarly activities extend to numerous conference presentations and editorial work, demonstrating sustained commitment to advancing translation studies both in Turkey and internationally. She has contributed to various publications examining the complex relationship between translation, cultural identity, and historical transformation in Turkish-Ottoman contexts.

• Behavioral Science
• Psychology
• Neuroscience
• +12 more

Antonio José Ibáñez Molina is a Professor in the Department of Psychology at the University of Jaén. His research focuses on the intersection of neuroscience, behavioral science, and complex systems, utilizing EEG technology to study cognitive disorders, emotional states, and neural dynamics. Key research areas: Behavioral Science Methodology, Complex Systems, Schizophrenia, Mindfulness, Fractal Analysis His recent publications highlight trends in EEG complexity analysis, fractal patterns in psychiatric disorders like schizophrenia, and the development of computational tools for neuroscience research. Articles also explore neural correlates of consciousness, language switching in bilinguals, and motor symptom evaluation in psychosis. As part of the "Complex Systems and Organisms" research group, he contributes to understanding neural connectivity and computational modeling in mental health disorders.

• Plant Systematics
• Biotechnology
• Molecular Biology
• +2 more

Dr. Mevlüde Alev ATEŞ is an Assistant Professor in the Department of Agricultural Biotechnology at Ahi Evran University's Faculty of Agriculture. She holds a PhD in Biology from Middle East Technical University (2017) and specializes in Plant Systematics, Molecular Biology, and Plant Biotechnology. Her research employs molecular techniques to study plant phylogenetics, genetic diversity in Turkish flora, and conservation of endemic species. Education: PhD in Biology, Middle East Technical University (2011–2017) MSc in Biology, Middle East Technical University (2007–2011) BA in Mathematics and Science Education, Gazi University (2002–2007) Research Focus: Her work integrates molecular phylogenetics, DNA barcoding, and biotechnology to address taxonomic ambiguities in genera like Astragalus , Gundelia , and Fabaceae crops. She explores applications in agricultural biotechnology, including genetic characterization of Turkish crops and stress physiology. Publication Trends: Her 15 most recent articles (2020–2025) emphasize molecular systematics of endemic Turkish plants, discovery of new species, and genetic resource conservation. Common themes include ITS2/rDNA analysis, RAPD markers, and phylogenomics, frequently published in journals like Plants and Turkish Journal of Botany . Awards: TÜBİTAK UBYT Publication Incentive Award (2024, 2022×2) İKSAD Science Award (2022) TÜBA Honorable Mention for book translation (2015) Projects & Advising: She leads projects on molecular phylogenetics of Vicia and Astragalus , radiation effects on plants, and in vitro propagation of endemics. She advises Master's students on topics like genetic characterization of walnuts and molecular analysis of Vicia species. Administrative Roles: Vice Dean (2024–present) and Erasmus Coordinator (2018–present) at Ahi Evran University.

Lea BoßmannView profile

Professor

• Mathematical Physics
• Quantum Many-Body Systems
• Interacting Bose Gases
• +7 more

Lea Boßmann is Professor of Analysis at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), appointed in 2024. Previously she held a Junior Professorship at Johannes Gutenberg University Mainz and post-doctoral positions at LMU Munich and IST Austria. Education 2016–2019: Dr. rer. nat., University of Tübingen (PhD thesis: Effective dynamics of interacting bosons ) 2010–2016: B.Sc. & M.Sc. in Physics and Theoretical-Mathematical Physics, LMU Munich Research Interests Her research lies in mathematical physics, concentrating on the rigorous analysis of quantum many-body systems. She is particularly interested in deriving effective evolution equations for complex bosonic systems in the mean-field and large-particle limits, handling singular interactions, dimension reduction, and higher-order perturbative corrections beyond the classical Bogoliubov approximation. Key themes include: Effective descriptions of interacting Bose gases Mean-field limits and nonlinear Schrödinger equations Asymptotic analysis and Edgeworth expansions Dimensional reduction for strongly confined systems Stochastic perspectives on quantum many-body dynamics Scientific Contributions Across more than a dozen peer-reviewed articles since 2018, Boßmann has systematically refined the mathematical understanding of weakly interacting Bose gases, providing rigorous justification of effective equations such as the Gross–Pitaevskii and one-dimensional nonlinear Schrödinger equations, quantifying higher-order corrections, and analyzing spectral and dynamical properties of low-energy excitations. Teaching & Supervision At FAU she lectures in Analysis and runs advanced seminars on function theory and mathematical physics. During the academic year 2025 she will offer: Summer 2025: Function theory, Real Functions seminar, Mathematical Physics seminar Winter 2024/25: Analysis for teaching degree students, Mathematical Physics seminar Contact & Location Room 02.385, Cauerstraße 11, 91058 Erlangen, Germany Phone: +49 9131 85-67120 E-mail: lea.bossmann@fau.de