جست‌وجوی استاد و پژوهشگر

Aygul Zagidullinaمشاهده پروفایل

مدرس ارشد

• Data Science
• Machine Learning
• Artificial Intelligence
• +۵ مورد دیگر

Aygul Zagidullina is a Senior Lecturer and Researcher at the Lucerne University of Applied Sciences and Arts, specifically affiliated with the Lucerne School of Computer Science and Information Technology. She serves as Head of Applied Data Intelligence in Continuing and Executive Education, contributes to teaching and research in Data Science, Machine Learning, and Artificial Intelligence, and co-organizes academic initiatives like Women in AI and the Women in Data Science (WiDS) conference in Zürich. Ph.D. in Quantitative Methods (specialization: High-Dimensional Covariance Matrix Estimation) Diploma in Applied Mathematics (B.Sc. + M.Sc.) Postgraduate Machine Intelligence Program in Computer Science Certificate in Didactics for Higher Education Her research focuses on data-driven solutions at the intersection of Statistics, Computer Science, and Finance, with applications in portfolio optimization, NLP bias mitigation, and image quality assessment. She emphasizes the societal impact of AI and its integration into industry workflows. Recent projects include hydropower digital twins, AI for procurement documentation, and LLM training via user feedback. She authored a Springer textbook on High-Dimensional Covariance Matrix Estimation in 2021 and has co-authored peer-reviewed articles in the Journal of Financial Econometrics (2021, 2024). Her work spans theoretical rigor and practical implementation across finance, energy, and healthcare domains. Aygul contributes to academic leadership through roles such as Module Responsible in AI Competition (Kaggle Challenge), Co-Head of the CAS Machine Learning and Data Science for Medicine and Health programs, and Thesis Supervisor in AI & ML. She collaborates with industry partners (e.g., Paretolabs, Konplan) and leads research at the AI Robotics Research Lab.

Jean-Louis Arcandمشاهده پروفایل

استاد

• Development Economics
• Global Health
• Agricultural Economics
• +۷ مورد دیگر

Jean-Louis Arcand is a Professor of International Economics at the Graduate Institute of International and Development Studies in Geneva since 2008. He previously served as Director of the Centre for Finance and Development (2012-2016) and Chair of Development Studies (2009-2012). A Founding Fellow of the European Union Development Network (EUDN) and Senior Fellow at FERDI , his work bridges development economics, global health, and policy evaluation. PhD in Economics from MIT Former academic roles at University of Montréal and CERDI His research focuses on the microeconomics of development , particularly impact evaluation of social programs in West Africa and the Maghreb. Key areas include HIV/AIDS prevention , food security , linguistic economics , and economic history . Recent publications analyze topics such as disequilibrium dynamics , tax compliance , and racial discrimination in labor markets. His work spans empirical and theoretical approaches across disciplines like health economics , agricultural development , and public policy . Scientific awards: Founding Fellow, EUDN Senior Fellow, FERDI Jean-Louis Arcand has served as a consultant for the World Bank , FAO , UNDP , and national governments. He leads multi-year impact evaluations in Angola, Burkina Faso, Burundi, Cameroon, The Gambia, Mali, Morocco, and Senegal, focusing on peer mentoring for HIV/AIDS and rural producer organization capacity-building.

• Artificial Intelligence (AI) in Industry
• Machine Learning
• Natural Language Processing (LLMs)
• +۴ مورد دیگر

Prof. Dr. Esther Gelle is a Lecturer in Digital System Design at the FHNW Institute of Business Engineering, part of the FHNW School of Engineering and Environment at the University of Applied Sciences Northwestern Switzerland. Her work focuses on AI applications in industry, machine learning, natural language processing (LLMs), constraint satisfaction problems, and digital business process modeling. She has contributed to advancements in industrial automation systems, IT asset management, and configuration frameworks. Her research spans over two decades, with notable contributions in constraint satisfaction problem solving, industrial standard adaptation (e.g., IEC 61346), and autonomous IT management. She collaborates with industry partners to bridge theoretical concepts with practical applications. Her publications emphasize optimization techniques, system modeling, and automated configuration in engineering contexts. Her articles consistently explore themes like constraint-based problem solving, industrial process control, and the integration of AI into technical systems. While no awards are explicitly listed, her extensive publication record reflects sustained academic and industrial impact. She currently holds no listed students or grants but actively engages in research teams focused on automation and digital transformation. Her affiliation with the Institute of Business Engineering positions her at the intersection of technical systems and business processes, emphasizing practical solutions for modern industrial challenges. She is based at the FHNW Campus Brugg-Windisch, contributing to both educational and applied research initiatives.

Hristo Georgiev Papazovمشاهده پروفایل

پژوهشگر

• Machine Learning Theory
• Deep Learning
• Optimization Algorithms
• +۳ مورد دیگر

Hristo Georgiev Papazov is a Doctoral Assistant at the Theory of Machine Learning (TML) Laboratory under the Institute of Information and Communication Systems (IINFCOM) at EPFL. His primary affiliation is within the School of Computer and Communication Sciences (IC) at the prestigious École Polytechnique Fédérale de Lausanne. Additionally, he is enrolled in the Doctoral Program in Computer Science (EDIC) within the School of Engineering (ETU). His research interests span theoretical computer science, machine learning fundamentals, and applied deep learning in healthcare contexts. Notable focuses include algorithmic analysis of neural networks, optimization dynamics, and clinical text classification systems using SNOMED CT standards. His work also intersects with mathematical analysis, particularly in extending classical complex analysis techniques to elliptic frameworks. Papazov has contributed to publications addressing momentum-based training in linear networks, dimensionality effects in online algorithms, and interdisciplinary applications of machine learning in medical coding. His current position involves both research in the TML lab and doctoral studies, reflecting a dual commitment to advancing theoretical understanding and practical applications in computer science.

Anne-Florence Bitbolمشاهده پروفایل

استادیار

• Protein Evolution
• Statistical Physics of Biological Systems
• Computational Biology
• +۲ مورد دیگر

Anne-Florence Bitbol is a Tenure Track Assistant Professor at EPFL's Institute of Bioengineering, where she leads research at the intersection of statistical physics and biological evolution. Education: PhD in Physics, Université Paris-Cité (2012) MSc in Fundamental Physics, École Normale Supérieure (2009) BSc in Physics, École Normale Supérieure de Lyon (2007) Her group develops quantitative models to understand protein evolution, microbial adaptation, and sequence-function relationships. Current projects investigate how spatial structure impacts evolutionary dynamics and develop machine learning methods for protein sequence analysis. Recipient of the IUPAP Young Scientist Prize in Biological Physics (2023) and EPFL's Best Teacher Award (2023). Research combines theoretical approaches with data-driven methods to reveal fundamental principles in biological systems. Recent publications include advances in protein language modeling, evolutionary rescue mechanisms, and CRISPR-Cas system dynamics. Teaches graduate courses in genomics and computational biology methods.

• Computer Science Education
• Programming Pedagogy
• Visual Programming
• +۳ مورد دیگر

Dr. Sverrir Thorgeirsson is a Professor of Computer Science at ETH Zürich, affiliated with the Department of Computer Science under the School of Computer and Communication Sciences. His work focuses on innovative educational technologies and pedagogical frameworks to enhance programming education. His research interests include visual programming languages (e.g., Algot), cognitive aspects of learning (e.g., cognitive load measurement via EEG), and strategies to improve abstraction skills and software testing comprehension in students. He emphasizes bridging the syntax-semantics gap in programming through hands-on, interactive tools. Recent publications highlight his contributions to visual programming environments, failure-based learning, and the design of pedagogical frameworks. He actively explores how cognitive science principles can optimize educational outcomes in introductory and advanced CS courses. No scientific awards were explicitly listed. His advising and grants sections remain under development, pending additional data.

Maciej Bestaمشاهده پروفایل

پژوهشگر

• Sparse Graph Computations
• Large Language Models
• Graph Neural Networks
• +۷ مورد دیگر

Maciej Besta is a leading researcher at ETH Zurich's Institute for Computing Platforms, where he heads research initiatives at the Scalable Parallel Computing Lab (SPCL) and contributes to the ETH Future Computing Laboratory (EFCL). Working under the mentorship of Professor Torsten Hoefler, he has established himself as a prominent figure in high-performance computing, graph processing, and large language models. Position: Researcher at Institute for Computing Platforms, ETH Zurich Research Leadership: Head of Sparse Graph Computations and Large Language Models Research at SPCL Collaboration: Leads project management for SPCL's contributions to ETH Future Computing Laboratory Besta's research spans multiple abstraction levels, from hardware and network topologies to middleware, algorithms, and programming models. His primary focus areas include graph-enhanced language models, graph neural networks, graph databases, and sparse models, with applications across various computational settings. He approaches these problems through rigorous performance modeling and formal reasoning, emphasizing both scalability and practical implementation. His recent publications reveal a clear trend toward integrating graph structures with language models and AI systems. Besta has pioneered work on graph databases, knowledge graphs of thoughts, and higher-order graph neural networks, while maintaining his strong foundation in high-performance computing and network topology design. His research bridges traditional HPC with cutting-edge AI, creating novel approaches for efficient large-scale computation. IEEE TCSC Award for Excellence in Scalable Computing (Early Career, 2023) Multiple Best Paper Awards at Supercomputing conferences (2022, 2023) ACM SIGHPC Doctoral Dissertation Award (2022) ETH Medal for outstanding doctoral thesis (2021) Fellow of The Explorers Club (2022) Besta actively mentors ETH Zurich students through semester projects, Bachelor's, and Master's theses, focusing on graph processing and related computer science challenges. His mentorship extends beyond technical guidance, incorporating lessons from his extensive polar and mountaineering expeditions that emphasize mental resilience, efficient risk management, and leadership. He has supervised numerous student projects that have resulted in high-impact publications at top-tier conferences. As a core member of the Scalable Parallel Computing Lab, Besta collaborates with researchers across ETH Zurich and international institutions. His unique approach integrates insights from extreme environment expeditions into research methodology, creating a distinctive framework for tackling complex computational problems. The lab's work under his leadership spans theoretical modeling, practical implementation, and real-world deployment of high-performance systems.

• Computer Science
• Software Engineering
• Formal Verification
• +۳ مورد دیگر

Dr. Malte Schwerhoff is a Lecturer at the Department of Computer Science at ETH Zürich. His teaching responsibilities include courses such as Introduction to Programming , Software Engineering , and Preparatory Course in Computer Science . His research focuses on formal verification, automated reasoning, and symbolic execution techniques, with a particular emphasis on security protocols, programming languages, and compiler design. His work bridges theoretical computer science with practical applications in software engineering and cybersecurity. Research contributions span modular verification methodologies, permission-based reasoning frameworks, and the development of tools like Viper for static analysis. His studies address challenges in ensuring correctness and security in software systems through formal methods. Notably, his work on symbolic execution profiling and generalized magic wand support has advanced automated program verification techniques. While no awards or grants are explicitly listed in the provided texts, his active publication record reflects ongoing engagement with cutting-edge topics in computer science. Advising and lab affiliations are not detailed here, but his involvement in teaching and research underscores his role as an educator and scholar in computational theory and practice.

Johannes Hostertمشاهده پروفایل

پژوهشگر

• Program Verification
• Separation Logic
• Type Theory
• +۵ مورد دیگر

Johannes Hostert is a Researcher at the Department of Computer Science (D-INFK) , ETH Zurich, since October 2023. He works under the guidance of his advisor Ralf Jung in the PLF lab . His research focuses on program verification, separation logic, type theory, and formal methods in Rust programming. Bachelor’s and Master’s degrees from Saarland University Advisor: Ralf Jung Research Trends include formal verification of programming languages, especially Rust and OCaml/C interoperability, mechanised logic in Coq, and aliasing models like Tree Borrows. His work bridges compiler optimization with memory safety guarantees. Scientific Awards : Distinguished Paper Award for Tree Borrows (2025) Labs & Collaborations : PLF lab at ETH Zurich, working with team members like Neven and Derek on projects such as Tree Borrows and MiniRust formalization.

• Programming Languages
• Formal Verification
• Software Engineering
• +۳ مورد دیگر

Prof. Ralf Jung is an Assistant Professor at ETH Zürich's Department of Computer Science, leading the Programming Language Foundations Lab under the Institute for Programming Languages and Systems. His work focuses on formal verification of programming languages, particularly Rust and Iris. Previously, he earned his PhD at Saarland University and MPI-SWS, advised by Derek Dreyer, followed by a postdoc at MIT CSAIL's PDOS group. Research Interests: Formal foundations of Rust, including tools like Miri for detecting undefined behavior and MiniRust for precise specification. Iris logical framework for modular verification of programming languages at scale. Concurrent and distributed systems verification using separation logic. Advising & Labs: He leads the Programming Language Foundations Lab and is hiring postdocs. His work integrates theoretical rigor with practical tooling for real-world language verification challenges. Labs/Teams: Programming Language Foundations Lab at ETH Zürich, collaborating with the Rust language team and global research community.

• Hospitality Management
• Crisis Communications
• Sustainability
• +۵ مورد دیگر

Laura Zizka is a Professor at the EHL Hospitality Business School , part of the HES-SO University of Applied Sciences and Arts Western Switzerland. Her research focuses on crisis communication, sustainability in hospitality, and the evolution of higher education during crises. She holds a BSc in Hospitality Management from EHL and has led multiple interdisciplinary projects, including a 2019-2020 study on destination image funded by HES-SO Rectorat. Her work bridges academic research with practical industry applications, emphasizing resilience, digital transformation, and environmental responsibility. Education: BSc HES-SO in Hospitality Management from EHL Hospitality Business School. Research Interests: Crisis communication strategies in hospitality, sustainability literacy in STEM and hospitality programs, digital learning in higher education, and the role of imagery in destination branding. She has pioneered studies on pandemic-era teaching methods and the integration of trauma-informed pedagogy in faculty development. Grants and Projects: Principal investigator on a CHF 99,000 project (2019-2020) exploring pictorial content’s impact on destination image and tourist intentions. Collaborated on studies analyzing Swiss hotel crisis communication during the pandemic and Egyptian tourism resilience. Professional Contributions: Authored over 50 peer-reviewed articles and book chapters, with a focus on transforming academic practices to meet 21st-century challenges. Co-developed models for blended learning, E-PEB (Extraordinary Pro-Environmental Behavior), and trauma-informed educational strategies. Active in faculty development initiatives, emphasizing digital tools and pedagogical innovation. Notable Achievements: Her work on digital education post-pandemic has shaped institutional policies, while her research on CSR communication in airlines and food waste mitigation has influenced industry practices. She is a frequent speaker at global conferences, addressing topics like Gen AI in academia and sustainability in STEM.

Markus Püschelمشاهده پروفایل

استاد

• Program Generation
• Fourier Analysis
• Signal Processing
• +۶ مورد دیگر

Markus Püschel is a Professor of Computer Science at ETH Zurich, leading the Advanced Computing Laboratory. He previously served as Head of the Department of Computer Science at ETH from 2013 to 2016. Before joining ETH in 2010, he was a Professor at Carnegie Mellon University (CMU) and retains adjunct status there. He holds a PhD in Computer Science (1998) and a Mathematics Diploma (1995) from the University of Karlsruhe. His research focuses on program generation for performance, Fourier analysis, signal processing, machine learning, and compiler optimization. He pioneered the SPIRAL system for generating optimized signal processing libraries and has contributed to algebraic signal processing theory. His work bridges mathematical foundations with practical high-performance computing, emphasizing automated code generation and domain-specific languages. Research trends in his articles include causal inference on directed acyclic graphs, quantized neural network inference, and efficient compiler techniques. His work on graph signal processing and causal analysis has led to novel methods in time-series data and DAG learning. Awards: IEEE Fellow (2020), Golden Owl Teaching Award (2015), NSF Discovery Grant (2008), and multiple best paper awards. Grants/Projects: Co-PI for Making Program Analysis Fast (SNF), SPIRAL GPU projects, and collaborations with industry partners like Intel and AMD. He advises over 40 PhD and master’s students, many of whom contribute to impactful projects in compilers, machine learning, and signal processing. His lab also co-founded the Swiss Data Science Center.

Bruno Maurerمشاهده پروفایل

استاد

• Sociolinguistics
• Didactics of Foreign Languages
• French as a Second Language
• +۵ مورد دیگر

Bruno Maurer is a Full Professor and Director of the School of French as a Foreign Language (FLE) at the University of Lausanne (UNIL), serving since August 2019. His career spans teaching in France and Djibouti, focusing on FLE teacher training and sociolinguistic research in Africa. He holds a doctorate from Montpellier 3 Paul-Valéry University, with expertise in language contact dynamics and didactics. Maurer directed the Agence universitaire de la Francophonie’s Indian Ocean Office and the Dipralang laboratory. His research emphasizes language policies, multilingual education, textbook analysis, and post-terrorist discourse. He currently oversees the TDFLE journal and advocates for equitable language education frameworks in diverse sociocultural contexts. Education: Modern Literature studies at Montpellier 3 Paul-Valéry University, including a teaching qualification (Agrégation). Early career included secondary teaching in France and FLE teacher training in Djibouti, alongside sociolinguistic fieldwork on French-Djiboutian language dynamics. Research Interests: Sociolinguistics of language contact and multilingualism. Didactics of French as a second/foreign language. Educational language policies and curriculum design. Teacher professionalism and institutional challenges in FLE. Linguistic representations and discourse analysis. Leadership and Projects: Director of UNIL’s FLE School, driving pedagogical innovation and program development. Former Director of Dipralang (Montpellier) and the Agence universitaire de la Francophonie’s Indian Ocean Office. Editor of Travaux de didactique du français langue étrangère (TDFLE) . Key contributor to multilingual education initiatives in Africa, including the ELAN-Afrique program. Grants and Collaborations: Research partnerships in Mali, Madagascar, and Djibouti. Consultancy for international organizations on language policy and education equity. Labs/Teams: Leads the FLE School’s research group at UNIL and collaborates with Dipralang in Montpellier on sociolinguistic and didactic studies.

• Wound Care
• Venous Leg Ulcers
• Nursing Education
• +۳ مورد دیگر

Bobbink Paul is a Lecturer at the Haute école de santé - Genève, affiliated with the Faculty of Santé. His research focuses on chronic wound care, particularly venous leg ulcers, patient self-management strategies, and innovative nursing education methodologies. He has led multiple studies exploring pain management in chronic wound patients, the efficacy of nurse-led patient education programs, and the integration of digital tools in wound care education. Key Affiliations: Haute école de santé - Genève (HES-SO), Geneva, Switzerland. Primary Research Areas: Wound care education, compression therapy, and chronic venous insufficiency management. His work emphasizes methodological approaches like constructivist grounded theory and thematic analysis to understand patient experiences. Paul has contributed to developing blended-learning curricula for nursing students and pioneered the use of serious games and e-learning platforms in wound care education. His recent studies address challenges in care transitions for diabetic foot ulcer patients and the impact of hybrid learning on clinical skills. Paul actively participates in international conferences such as EWMA, presenting on topics like compression bandage techniques and the role of AI in wound care. He co-leads the specialized wound healing and care laboratory at HES-SO, bridging research and clinical practice through applied projects.

Jeanine Reutemannمشاهده پروفایل

مدرس

• Science Communication
• Educational Media
• Digital Education
• +۳ مورد دیگر

Dr. Jeanine Reutemann serves as a Lecturer at the Department of Environmental Systems Science, ETH Zurich, where she leads the Media & Methods Lab within the Unit for Teaching and Learning (UTL). Her role encompasses producing co-designed audiovisual media for ETH lecturers, advancing digital media competencies across the institution, and exploring innovative media technologies for future teaching through flagship projects. Her research centers on the science-society interface , specializing in translating complex scientific concepts through audiovisual media. Key interests include the epistemological potential of visual language in education, sustainable production of science videos, mixed reality applications, and combating misinformation. She investigates how media design shapes public understanding of science and enhances learning experiences in higher education, with particular focus on deepfakes, truth verification, and co-design methodologies. Analysis of her publication trajectory (2016-2024) reveals an evolution from foundational studies on MOOC video styles to current work on sustainable educational media and mixed reality. Her research consistently bridges theory and practice, emphasizing ethical considerations, societal impact, and the transformative role of audiovisual media in science communication. Recent publications highlight growing attention to environmental sustainability in media production and AI's implications for scientific content generation. Dr. Reutemann actively contributes to interdisciplinary projects funded by the Swiss National Science Foundation (SNF), including the r4d programme. She has collaborated with Oxford University, WSL, WWF/COOP, and others to produce science documentaries addressing global challenges such as inequality, sustainability, and peacebuilding, including the full-length documentary 'Inequality and Conflict - Beyond us and Them'. She heads the Media & Methods Lab, a dynamic team that partners with ETH lecturers to co-create educational media, designs continuous professional development programs in digital media competencies, and pioneers new media technologies through projects like the Science Filmmaking Hackathon (producing AI-themed animations) and mixed reality character prototypes for campus navigation. Current initiatives include developing audiovisual essays with the gta archive and science communication videos leveraging internet meme culture for environmental science students.