جستجوی استاد راهنمای دانشگاهی

Andreas Henriciمشاهده پروفایل

پژوهشگر

• NMR spectroscopy
• Dynamical systems
• Mathematical analysis
• +۴ مورد دیگر

Andreas Henrici is a research-focused academic at the Zurich University of Applied Sciences (ZHAW), School of Engineering, within the Applied Complex Systems Science research centre. His core activities revolve around NMR spectroscopy, dynamical systems theory, and the development of machine-learning methods for automated spectral analysis. Education & professional development: Certificate of Completion, ZHAW Life Sciences and Facility Management, 02/2019 Doctorate (Dr.) – exact discipline and institution not specified in the source Research interests: Henrici combines analytical mathematics with practical spectroscopy. Early work concentrated on stability and symmetry analyses of nonlinear lattices (Toda lattice). More recently he leverages deep-learning architectures (CNNs, DETR-style networks) to deconvolute and classify 1D/2D-NMR data, pushing automation in metabolomics and fragment-based drug discovery. Bayesian inference, image-processing techniques, and trustworthy AI are recurring themes. Recent publication trends (2022-2025): Over 15 peer-reviewed articles and conference posters illustrate a clear shift toward AI-driven NMR: deconvolution networks, automated multiplet segmentation, spin-system identification, and uncertainty-aware classification. Collaborative projects yield open data, open code, and cross-disciplinary authorship with chemists, computer scientists, and industry partners. Editorial & organisational service: Guest editor for Frontiers in Artificial Intelligence volumes summarising European COST conferences on AI in Industry & Finance (2022, 2023) Project leader for the European conference series AI in Industry and Finance (completed) Current projects & funding: Smart Acquisition for Ultra-High field NMR Spectroscopy – project leader (ongoing) NMR-based drug discovery – co-project leader (ongoing) Several completed COST and ZHAW-internal grants on machine-learning for spectroscopy and mathematics-for-industry Labs & teams: Henrici is embedded in the ZHAW Applied Complex Systems Science focus area, working closely with the NMR, metabolomics, and data-science groups. Shared facilities include high-field NMR spectrometers and GPU clusters for deep-learning experiments.

Karl Reiner Lermerمشاهده پروفایل

پژوهشگر

• Safety-Critical Systems
• Software Engineering
• Systems Engineering
• +۱ مورد دیگر

Dr. Karl Reiner Lermer is a researcher at the Zurich University of Applied Sciences, affiliated with the School of Engineering. His work focuses on safety-critical systems and software reliability, with significant contributions to formal accident analysis and dynamic flowgraph modeling. His research projects include: Formal Analysis of Accidents Application of STPA (Systems-Theoretic Process Analysis) to digital control and reactor protection technology Software reliability and Dynamic Flowgraph Modeling These projects highlight his expertise in ensuring safety and robustness in complex technical systems.

• Medical Imaging
• Artificial Intelligence
• Blockchain Technology
• +۲ مورد دیگر

Dr. Lukas Lichtensteiger is a Researcher at the Zurich University of Applied Sciences (ZHAW), affiliated with the School of Engineering's Medical Complex Systems group. His work bridges engineering, AI, and medical technology, focusing on innovative solutions for healthcare and sustainability challenges. Research Focus Lichtensteiger's research spans medical imaging AI, blockchain applications, and complex systems engineering. Key areas include: AI-powered medical imaging for cancer therapy and artifact mitigation Blockchain-based solutions for decentralized finance and voting systems Complexity management in industrial and medical operations Publications Overview Recent works (2019-2023) demonstrate a strong focus on deep learning applications in medical physics (CT image enhancement, deformable registration) and blockchain technology (Fairtrade finance, e-voting). Earlier research addressed space science and morphological control systems. Projects Led SpaceVote (blockchain voting) and sensor tech for robotics projects Co-directed AI applications in cancer therapy and medical data training Contributed to blockchain solutions for agroforestry and supply chain finance

Frank Lichtenbergمشاهده پروفایل

پژوهشگر

• Oxide Synthesis
• Superconductors
• Multiferroics
• +۵ مورد دیگر

Dr. Frank Lichtenberg serves as a Researcher at ETH Zurich's Department of Materials within Prof. Nicola Spaldin's division, where he has operated an oxide synthesis laboratory since 2011. His work focuses on crystal growth of complex oxides using the floating zone method and investigating their physical properties for applications in superconductivity and multiferroics. 1983-1989: Physics studies at University of Heidelberg 1989-1992: PhD research at IBM Zurich Research Laboratory under Dr. Georg Bednorz, awarded by University of Zurich in 1991 1992-1997: Research scientist at VARTA battery company (nickel metal hydride technology) 1997-2007: Research scientist at University of Augsburg's Institute of Physics 2007-2010: Independent research and development of novam-research.com Since 2015: Consulting for Quantum Power Munich GmbH Lichtenberg's research centers on the synthesis and characterization of perovskite-related oxides, particularly Carpy-Galy phases (AnBnO3n+2) that exhibit unique combinations of ferroelectricity, magnetism, and metallic conductivity. His investigations target materials that are simultaneously (anti)ferroelectric and (anti)ferromagnetic, with emphasis on quasi-one-dimensional systems like SrNbO3.4 where conduction electrons exist within ferroelectric environments. His work has contributed to understanding high-temperature ferroelectrics (e.g., Sr4Nb4O14 with Tc=1615K) and potential superconducting mechanisms in layered oxides. Recent publications (2020-2025) demonstrate advanced methodologies in crystal growth and characterization, including custom instrumentation for floating zone furnaces, electron diffraction studies of non-centrosymmetric structures, and investigations of photoinduced metal-insulator transitions. His research shows consistent focus on structure-property relationships in complex oxides, with particular attention to charge density waves, quantum confinement effects, and magnetic ordering in layered systems. As a research scientist, Lichtenberg has contributed to collaborative projects within Spaldin's group at ETH Zurich and previously with Nobel laureate J. Georg Bednorz at IBM. His work spans fundamental materials discovery to applied technologies, including patents for nickel-metal-hydride batteries during his industrial tenure at VARTA. He maintains active involvement in both experimental methodology development and theoretical interpretation of oxide properties. Lichtenberg operates a specialized oxide synthesis laboratory at ETH Zurich equipped with a Cyberstar mirror furnace for floating zone crystal growth. His facility supports comprehensive materials characterization through powder x-ray diffraction, electron diffraction, SQUID magnetometry, piezoresponse force microscopy, and thermogravimetric analysis. This integrated approach enables systematic investigation of structure-property relationships in newly synthesized oxide compounds.

Samy Bengioمشاهده پروفایل

استاد

• Machine Learning
• Neural Networks
• Speech Processing
• +۳ مورد دیگر

Samy Bengio is a Full Professor at the Ecole Polytechnique Fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences. He holds multiple roles including Full Professor in the IC Deanship and Lecturer positions in both SSC - Teaching and SIN - Teaching departments, with his office located at INR 140. His academic career spans over three decades with significant contributions to machine learning and artificial intelligence. Dr. Bengio received his PhD in Computer Science from the University of Montreal in 1993. Following his doctoral studies, he completed three postdoctoral years at CNET (the research center of France Telecom) and INRS-Telecommunications in Montreal. He subsequently worked as a researcher at CIRANO, an academic research center in economics and finance, and served as a research director at Microcell Labs, the research center of a Canadian telecommunications company. Since 1999, he has been a senior researcher and head of the Machine Learning group at IDIAP. His research interests encompass a broad spectrum of machine learning topics including learning algorithms, automatic speech processing, person authentication, multimodal processing, sequence processing, neural networks, support vector machines, hidden Markov models, and Gaussian mixtures. His work often bridges theoretical foundations with practical applications across various domains. Analysis of his recent publications (2023-2025) reveals a strong focus on fundamental questions about the reasoning capabilities of neural networks, particularly transformers. His research examines out-of-distribution generalization, the limits of logical reasoning in AI systems, and novel approaches to improve model reasoning through techniques like chain-of-sketch and reversal thinking. A significant portion of his recent work investigates the mathematical foundations of why certain architectures succeed or fail at specific reasoning tasks. Outstanding Paper Award at ICML 2023 Dr. Bengio has supervised several doctoral students including Grangier David, Keller Mikaela, Paiement Jean-François, and Poh Norman Hoon Thian. His research group at IDIAP has received substantial funding for projects exploring the theoretical foundations of machine learning and their practical applications in speech recognition, authentication systems, and reasoning models. The group has developed the Torch learning algorithm library, which has been influential in the machine learning community. As head of the Machine Learning group at IDIAP, Dr. Bengio leads a multidisciplinary team of researchers investigating the fundamental principles of learning algorithms and their applications across various domains including speech processing, computer vision, and natural language understanding. His team collaborates extensively with both academic and industrial partners to advance the state of the art in machine learning.

• Soft Matter Physics
• Colloid and Polymer Science
• Light Scattering and Transport in Disordered Media
• +۴ مورد دیگر

Professor Frank Scheffold at the University of Fribourg is a leading expert in the Department of Physics with a focus on soft matter physics , colloid science , and photonics . His work spans from light scattering in complex media to microrheology of colloidal systems. He has contributed extensively to photonic materials and microgel research . Education : Not explicitly stated in provided text Key Collaborations : Luis Froufe-Pérez, Chi Zhang, Augustin Muster, Sofia Magkiriadou Research Trends include: Advanced light transport studies in disordered media Photonic crystals and hyperuniform materials synthesis Super-resolution microscopy of soft matter systems Microrheology of biologically relevant colloids Optical tweezers for colloidal manipulation Recent Publications highlight innovations in photonic materials , microgel characterization , and colloidal dynamics . His work bridges fundamental physics with applied nanotechnology , often involving interdisciplinary collaborations with biomedical researchers.

Max Heermannمشاهده پروفایل

پژوهشگر

• Political Science
• Comparative Politics
• Federalism
• +۳ مورد دیگر

Max Heermann is a researcher specializing in Politics in Multi-Level Systems at ETH Zurich's Department of Humanities, Social and Political Sciences (D-GESS). Based at the IFW D 36.1 office in Zurich, Switzerland, he contributes to understanding political dynamics across interconnected governance tiers. His research examines how political decision-making operates within complex frameworks spanning local, regional, national, and international spheres. This work is particularly relevant for federal systems, European Union governance structures, and global policy networks where authority is distributed across multiple institutional levels. Core Focus: Interactions between different political governance levels Methodology: Comparative institutional analysis Application Areas: Federalism, supranational governance, policy coordination As part of ETH Zurich's renowned social sciences division, Dr. Heermann contributes to research addressing contemporary challenges in political organization and decision-making processes across multi-tiered institutional environments.

Sarah Lohmannمشاهده پروفایل

مدرس

• Science Fiction
• Feminist Utopias
• Climate Fiction (Cli-Fi)
• +۷ مورد دیگر

Dr. Sarah Lohmann is a Lecturer in the Department of Humanities, Social and Political Sciences (D-GESS) at ETH Zurich, Switzerland. She is also a Postdoctoral Fellow and holds a PhD in English Literature from Durham University (2020), a Postgraduate Certificate in Academic Practice (PGCAP), and is a Fellow of the Higher Education Academy (FHEA). Her research and teaching focus on feminist utopian literature, science fiction, climate fiction (Cli-Fi), systems theory, and analytic philosophy as cultural criticism.

Robert Janjicمشاهده پروفایل

پژوهشگر

• Organizational Design
• Online Communities
• Decision Making in Organizations
• +۳ مورد دیگر

Robert Janjic serves as a Postdoctoral Researcher at the Evidence Based Strategic Management chair within the University of Vienna since March 2025. He is concurrently finalizing his doctoral studies in Business Administration at the same institution, having previously undertaken a visiting PhD student position at Imperial College London in early 2024. His academic credentials include a Master's degree in Business Administration and ongoing PhD research at the University of Vienna, supplemented by international research experience at Imperial College London. This foundation supports his empirical investigations into modern organizational phenomena. Janjic's research program rigorously examines organizational design frameworks, digital community dynamics, and cognitive processes in organizational decision-making. His work specifically investigates how structural configurations and monitoring systems influence exploratory behaviors and innovation outcomes, with particular emphasis on the interplay between hierarchical control mechanisms and subordinate autonomy. He employs quantitative methodologies to analyze search patterns in complex organizational environments, contributing to theoretical advancements in strategic adaptation and knowledge creation processes. His seminal 2023 publication in the Strategic Management Journal established empirical linkages between supervisory monitoring intensity and subordinate search behaviors, revealing nuanced effects on organizational exploration. This research, presented at premier conferences including the Academy of Management and Strategic Management Society, demonstrates consistent methodological rigor in examining organizational control systems through behavioral lenses, with emerging applications in digital platform governance. No scientific awards or honors were documented in the source material. The available information does not specify any formal student advising roles, mentorship activities, or externally funded research grants associated with Dr. Janjic's current position. As an integral member of Prof. Dr. Johannes Luger's Evidence Based Strategic Management research team, Janjic contributes to a collaborative environment focused on data-driven approaches to strategic decision architecture and organizational effectiveness, participating in ongoing projects examining evidence-based frameworks for complex organizational challenges.

• Mechanical properties of materials with complex defect structures
• Dynamical properties of local and extended defects
• Simulation tools for experimental measurement of structural disorder
• +۵ مورد دیگر

Peter Michael Derlet is a senior staff scientist at the Paul Scherrer Institut (PSI) in Switzerland and serves as an Adjunct Professor in the Department of Materials at ETH Zurich. He also holds a position as Visiting Scientist at the Department of Materials Engineering, Bundesanstalt für Materialforschung und -prüfung (BAM) in Berlin, Germany. His research spans multiple areas of condensed matter physics and materials science, with a focus on computational modeling of complex material systems. Derlet's research interests encompass the mechanical properties of materials with complex defect structures, dynamical properties of local and extended defects, development of simulation tools for experimental measurements using neutrons, photons and electrons, classical magnetization dynamics in micro- and meso-scopic magnetic systems, vibrational and configurational dynamics of structural glasses, avalanche statistics using simplified dislocation dynamics, and potential energy landscape exploration algorithms. His work bridges theoretical modeling with experimental validation across diverse material systems. Analysis of his recent publications reveals a strong focus on metallic glasses, magnetic systems, and radiation-damaged materials. His research shows increasing integration of computational modeling with experimental techniques like neutron scattering, with particular attention to topological defects in spin ice systems, structural dynamics in amorphous materials, and magnetic phase transitions. The interdisciplinary nature of his work connects condensed matter physics, materials science, and computational methods. Gilbert Hausmann prize (2021) for Hugo Bocquet's Masters Thesis Derlet actively supervises students at multiple levels, including PhD candidates Hugo Bocquet (2021-), Dominik Schildknecht (2016-2019), Soumya Swayamjyoti (2012-2016), and Araceli Valles Sales (2010-2013), as well as Masters and Bachelor students. He collaborates on SNF-funded PhD projects in Physics/Materials science on 'Magnetism in Correlated Disorder' with Tom Fennell at PSI. His teaching includes Thermodynamics and Phase Transformations and Computational multi-scale modeling of solids at ETHZ. Derlet's work with the Condensed Matter Theory group at PSI involves developing advanced simulation tools to model complex material behaviors, with particular emphasis on connecting microscopic mechanisms to macroscopic properties in disordered and frustrated systems.

Clara Zempمشاهده پروفایل

استاد

• Biodiversity Conservation
• Ecosystem Restoration
• Forest-Climate Interactions
• +۲ مورد دیگر

Clara Zemp serves as Full Professor and Director of the Conservation Biology Laboratory at the University of Neuchâtel's Faculty of Science since 2021. She co-directs the Interdisciplinary Master's in Biodiversity Conservation and maintains affiliations with the Swiss Biodiversity Forum and Young Swiss Academy. Her research centers on biodiversity conservation under global change, with expertise in oil palm plantation restoration through tree islands, Amazon forest resilience, and forest-climate interactions. Key projects include biodiversity enrichment in Sumatra, Swiss Jura wooded pastures, and climate-logging detection systems. Her publications reveal strong focus on tropical ecosystem restoration, demonstrating how tree islands enhance structural complexity and biodiversity in agricultural landscapes. Recent work emphasizes climate-vegetation feedbacks in the Amazon and practical agroforestry applications. Dissertation Prize from Xavier Bernard Foundation of French Academy of Agriculture (2013) Merian Prize from European Society for Tropical Ecology (2015) She actively promotes science-policy dialogue through the Swiss Young Network for Science Policy (SYNESPOD) and advises multiple international restoration initiatives including TRAILS program in Malaysia and TreeDivNet network. Her teaching covers conservation biology at Bachelor and Master levels.

• Trauma Surgery
• Orthopedics
• Polytrauma Care
• +۳ مورد دیگر

Frank JP Beeres (born 1982) serves as Adjunct Professor for Clinical Medical Sciences at the University of Lucerne's Faculty of Health Sciences and Medicine since June 23, 2023. Concurrently, he works as Chief Physician and Head of the Trauma Team at Lucerne Cantonal Hospital (LUKS) since 2022, within the Department of Orthopedics and Trauma Surgery where he has been employed since 2015. His educational background includes: Medical degree and PhD completion in Leiden, Netherlands Surgical residency specializing in trauma surgery Venia legendi from University of Zurich on "Questioning the Routine in Trauma Surgery" European Specialist Examination in Traumatology (EBSQ) certification Beeres' research focuses on evidence-based trauma surgery innovation, specifically examining polytrauma management protocols and upper extremity injury treatments. His work critically analyzes established surgical routines to optimize clinical outcomes, bridging bench research with frontline emergency care through LUKS' clinical research program. He maintains active involvement in surgical education across national and international platforms. As Trauma Team leader, he directs multidisciplinary emergency response systems for complex trauma cases while advising governmental and professional bodies on trauma care standards. His dual clinical-academic role positions him at the intersection of surgical practice refinement and medical education advancement in European trauma systems.

Oliver Janzerمشاهده پروفایل

استادیار

• Combinatorics
• Extremal Combinatorics
• Graph Theory
• +۱ مورد دیگر

Oliver Janzer serves as a Tenure Track Assistant Professor at the Swiss Federal Institute of Technology Lausanne (EPFL) within the School of Basic Sciences and Department of Mathematics. He holds the specialized Chair of Extremal Combinatorics and maintains dual institutional affiliations through the Institute of Mathematics (ECOM) and Mathematics Teaching Service (SMA-ENS), operating from office MA C1 577 at Station 8, Lausanne. His research centers on extremal combinatorics, investigating structural boundaries of combinatorial systems through graph theory and algebraic methods. This expertise directly informs his advanced teaching in courses like Graph Theory —covering fundamental concepts of modern graph structures—and Algebraic Methods in Combinatorics , where he applies linear algebra and polynomial theory to solve complex combinatorial problems. His work emphasizes theoretical frameworks for determining maximum/minimum configurations in constrained systems.

• Virtual Reality
• Computer Animation
• Crowd Simulation
• +۵ مورد دیگر

Daniel Thalmann is a distinguished Professor at École Polytechnique Fédérale de Lausanne (EPFL), specifically within the School of Computer and Communication Sciences and the Institute of Computer Science. As a current EPFL member, he leads the Virtual Reality Laboratory (VRLAB) and has established himself as a pioneer in virtual reality research with decades of international leadership in the field. His academic contributions span numerous publications, including the influential book "Stepping into Virtual Reality" (2023), which serves as both a textbook and reference for VR applications. Professor Thalmann's research interests encompass a broad spectrum of virtual reality and related technologies, with particular emphasis on computer animation, crowd simulation, virtual humans, and human-computer interaction. His work demonstrates exceptional depth in understanding how virtual environments can be designed to interact naturally with users, simulate complex social scenarios, and extend human capabilities through immersive technologies. He has made significant contributions to the theoretical foundations of VR while maintaining strong practical applications across various domains. The most recent publications reveal a clear progression in Thalmann's research trajectory, moving from core VR technologies toward increasingly sophisticated applications that integrate artificial intelligence, multi-sensory experiences, and real-world problem solving. His work now spans health sciences applications, brain-computer interfaces, sensory systems including smell and taste simulation, and the architectural foundations of the metaverse. This evolution demonstrates both continuity in his core expertise and strategic expansion into emerging application areas where virtual reality can have transformative impact. Through the Virtual Reality Laboratory at EPFL, Professor Thalmann has fostered numerous collaborations across disciplines and institutions, contributing significantly to the global VR research community. His leadership extends to organizing major international conferences including the Computer Graphics International (CGI) and Computer Animation and Social Agents (CASA) events, where he has served as editor and contributor to multiple proceedings volumes. The laboratory continues to advance research in social robotics, virtual humans, and immersive environments, with applications ranging from healthcare to cultural heritage preservation.

• Machine Learning
• Online Learning
• Computational Game Theory
• +۳ مورد دیگر

Andrea Celli is an Assistant Professor in the Department of Computing Sciences at Bocconi University, where he is a member of the theory group and the Bocconi Institute for Data Science and Analytics. He previously spent one year as a postdoctoral researcher with the Core Data Science team at Meta (London). He obtained his Ph.D. in Computer Science from Politecnico di Milano, where he was advised by Nicola Gatti, and was a Visiting Researcher at Carnegie Mellon University working with Tuomas Sandholm. His educational background includes: Ph.D. in Computer Science from Politecnico di Milano, advised by Nicola Gatti Visiting Researcher at Carnegie Mellon University with Tuomas Sandholm Postdoctoral researcher with the Core Data Science team at Meta (London) Andrea Celli's research focuses on problems at the intersection of computer science, machine learning, and economics, with particular interest in computational problems arising from strategic interactions in online settings where learning processes and incentives are fundamentally intertwined. His work spans machine learning theory, online learning algorithms, computational game theory, and algorithmic economics. His research has been published in top venues including NeurIPS, ICML, STOC, and EC, with a best paper award at NeurIPS 2020. Analysis of his recent publications shows a strong focus on online learning algorithms with constraints, bandit problems, game-theoretic aspects of machine learning, and algorithmic game theory. His work often bridges theoretical foundations with practical applications in economics and decision-making systems. Key themes include no-regret learning, Bayesian persuasion, knapsack problems in online settings, and equilibrium computation in extensive-form games. His scientific achievements include: Best paper award at NeurIPS 2020 ERC Starting Grant (2024) for the project PLA-STEER MUR-PRIN grant (2022) Andrea Celli actively mentors students and postdocs, currently supervising Riccardo Poiani, Sarah Sachs, and Martino Bernasconi as postdocs, and Annalisa Barbara, Emanuele Coccia, Davide Drago (now at Bending Spoons), and Antonio Preiti (now at Amazon) as MSc students. His research is supported by competitive grants including an ERC Starting Grant and a MUR-PRIN grant, indicating strong recognition of his work's potential impact. He is also a member of the ELLIS Society, connecting him to a broader European network of excellence in AI research. He is affiliated with the theory group and the Bocconi Institute for Data Science and Analytics at Bocconi University, contributing to a vibrant research environment focused on theoretical foundations of data science and their applications.