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George MetcalfeView profile

Professor

• Proof Theory
• Non-Classical Logics
• Ordered Algebraic Structures
• +3 more

Prof. Dr. George Metcalfe is a Professor and Managing Director of the Mathematical Institute (MAI) at the University of Bern. His research focuses on proof theory, non-classical logics, and ordered algebraic structures, with particular emphasis on algebraic semantics and decidability questions. He holds an office at Sidlerstrasse 5, Bern, and can be contacted via george.metcalfe@unibe.ch. His work bridges logic and algebra, exploring topics such as residuated lattices, fuzzy logics, and modal logics. Recent contributions include advancements in equational theories, interpolation properties, and decision procedures for algebraic structures. His research often intersects with computational logic and automated reasoning. Publications span foundational studies of algebraic systems and their logical counterparts, with a focus on substructural logics, lattice-ordered groups, and temporal models. His work frequently addresses decidability, completeness, and computational aspects of abstract algebraic frameworks. Metcalfe has organized international conferences such as the Advances in Modal Logic and Logic, Algebra, and Truth Degrees events. His research demonstrates interdisciplinary rigor, connecting formal logic with algebraic methods to solve complex theoretical problems.

• Portfolio Management
• Risk Management
• Machine Learning
• +7 more

Marc Weibel is a Senior Lecturer in the Center for Financial Data Science and Econometrics at the School of Management and Law, Zurich University of Applied Sciences (ZHAW), a position he has held continuously since August 2021. Previously, he served as Senior Lecturer in Financial Mathematics at ZHAW from January 2010 to July 2017 and concurrently as Chief Investment Officer at ENISO Partners AG from September 2017 to November 2022. He maintains active professional memberships in the Bachelier Society and European Finance Association, with an ORCID identifier (0000-0002-0819-9224) for scholarly attribution. His academic credentials include a PhD in Mathematics / Financial Mathematics from the University of Technology Sydney (2016-2019), an Advanced Certificate in Portfolio and Risk Management from Symmys (2012), a Master of Advanced Studies in Economics and Finance from the University of Geneva (2002-2004), and a Master in Economics from the University of Neuchâtel (1997-2001). Weibel's research focuses on the intersection of quantitative finance and data science, with primary emphasis on Portfolio Management, Risk Management, Machine Learning, and ESG Investing. His work integrates advanced mathematical techniques with practical financial applications, particularly in scenario-based optimization and alternative data utilization. He has published extensively on ESG factor integration, portfolio risk control, and financial data quality, often leveraging R and Python programming for empirical analysis. Analysis of his 2022-2024 publications reveals a pronounced shift toward sustainable finance, featuring multiple studies on ESG data validation, climate risk tools, and factor-tilt investment strategies. His scholarly output demonstrates consistent innovation in optimization algorithms (ADMM, model predictive control) and machine learning applications (NLP for greenwashing detection, reinforcement learning for SMEs), bridging theoretical finance with Swiss market implementation challenges. Marc Weibel has led significant applied research projects including the Adaptive AI-Driven Platform for P2P Lending Decisions and Liquid Instruments-Based Replication of Financial Indices. His collaborative work spans ESG-compliant product development, climate commitment tracking, and NLP-based analysis of corporate communication. Project roles reflect deep engagement with Swiss financial institutions through the Risk- and Finance-Lab. As a core team member of ZHAW's Risk- and Finance-Lab, he contributes to industry-academia partnerships focused on real-time financial decision systems. His project portfolio emphasizes practical solutions for Swiss asset owners, including ESG product customization and reinforcement learning frameworks for SME risk management.

Christoph KochView profile

Professor

• Database Theory
• Query Optimization
• Data Management Systems
• +4 more

Christoph Koch is a Full Professor of Computer Science at École Polytechnique Fédérale de Lausanne (EPFL), leading the Data Analysis Theory and Applications Laboratory (DATA). His academic journey includes previous roles as Associate Professor at Cornell University (2007-2010) and Saarland University (2005-2007), with academic foundations from TU Vienna (PhD 2001, Habilitation 2004) and research at CERN. Education: PhD in Artificial Intelligence (TU Vienna & CERN, 2001), Habilitation (TU Vienna, 2004) Appointments: EPFL (2010-present), Cornell University (2007-2010), Saarland University (2005-2007), TU Vienna (2003-2005) His research focuses on database theory and systems , with recent work spanning query optimization , transaction processing , and parallel data management . His publications address topics like robustness under SQL isolation levels , quantifier elimination for query optimization , and Datalog extensions . Articles trend toward high-dimensional data cubes , transactional concurrency , and embedded DSLs for performance-critical systems . Scientific accolades include: Best Paper Awards: PODS (2002) ICALP (2005) SIGMOD (2011) VLDB (2014) GPCE (2017) ERC Consolidator Grant (2011) Google Research Award (2009) ACM SIGLOG Alonzo Church Award (2021) He has advised numerous PhD students including Immanuel Trummer (now at Cornell), Milos Nikolic (Edinburgh), and Lionel Parreaux (HKUST). His lab contributes to query engine architectures , parallel processing systems , and quantum computing applications in database optimization.

• Nanoscale Science
• Quantum Technology
• Scanning Tunneling Microscopy
• +7 more

Klaus Kern is Full Professor of Physics at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Basic Sciences, Institute of Physics, and the Laboratory of Nanoscale Science (LSEN). He concurrently serves as Director and Scientific Member at the Max-Planck-Institute for Solid State Research in Stuttgart and holds an honorary professorship at the University of Konstanz, Germany. His research is centered at the intersection of physics, chemistry, and biology, focusing on atomic-scale phenomena. PhD in Chemistry, University of Bonn Chemistry Degree, University of Bonn Honorary Doctorate, University of Aalborg Professor Kern’s research lies at the forefront of nanoscale science and quantum technology. His work emphasizes the development and application of advanced scanning tunneling microscopy techniques to probe and manipulate matter at atomic and molecular scales. Key interests include quantum phenomena in nanosystems, single-molecule electronics, surface self-assembly, and quantum spin networks. His interdisciplinary approach bridges condensed matter physics, physical chemistry, and materials science, enabling breakthroughs in imaging, sensing, and control at the quantum limit. The recent publications highlight a consistent trajectory in quantum nanoscience, particularly in probing electron dynamics, single-molecule vibrations, photon statistics, and spin manipulation using scanning tunneling microscopy. Themes include quantum control, nanoscale imaging, and quantum light-matter interactions, reflecting his leadership in pushing the boundaries of experimental nanophysics and quantum measurement. Scientific honors include: Gottfried-Wilhelm-Leibniz Prize (2008) Van't Hoff Prize (2016) Kern has supervised over 100 PhD students and 60 postdoctoral fellows, many of whom now lead academic groups worldwide. He has authored nearly 700 publications with approximately 60,000 citations, underscoring his significant impact. His work is supported by long-standing affiliations with EPFL and the Max Planck Society, where he leads cutting-edge research initiatives in quantum and nanoscale science. Kern has also contributed to advisory committees for universities and scientific institutions globally. He leads the Laboratory of Nanoscale Science (LSEN) at EPFL and the Nanoscale Science Department at the Max-Planck-Institute for Solid State Research, fostering collaborative, interdisciplinary research in quantum materials, molecular electronics, and nanoscale imaging.

Mati Ullah ShahView profile

Lecturer

• Earthquake Engineering
• Structural Dynamics
• Civil Engineering
• +1 more

Mati Ullah Shah holds concurrent appointments at EPFL: Doctoral Assistant at the Earthquake Engineering and Structural Dynamics Laboratory (EESD) Doctoral Student in Civil and Environmental Engineering (EDCE) Lecturer in the ENAC Teaching Service (SSIE) His research centers on seismic resilience and structural behavior under dynamic loads within Civil Engineering. Affiliated with the Institute of Civil Engineering (IIC), he operates at the intersection of experimental earthquake engineering and computational structural analysis. Shah contributes to teaching through SSIE-ENS units while advancing his doctoral work at EESD's GC B2 484 facility. His role bridges academic instruction and laboratory research in structural dynamics.

• Computer Science
• Information Theory
• Machine Learning
• +3 more

Cemre Çadir is a Doctoral Assistant at the Mathematics of Information Laboratory (MIL), within the School of Computer and Communication Sciences at École Polytechnique Fédérale de Lausanne (EPFL). She is concurrently pursuing her doctoral studies in the Doctoral Program in Computer and Communication Sciences (EDIC). Her academic work is centered on the mathematical foundations of information processing, with research interests spanning computer science, information theory, machine learning, and data science. As a Doctoral Assistant, she contributes to research and academic activities at MIL, a leading laboratory in theoretical and applied aspects of information sciences. The available publications and research outputs could not be determined from the provided text. However, her affiliation with MIL suggests strong engagement in cutting-edge research in intelligent systems and information theory. Scientific Awards: No awards listed in the provided text. Advising and Grants: There is no public information available about advisees or funded research grants associated with Cemre Çadir in the current data. As a doctoral researcher, she may be supported through institutional or project-based funding at EPFL. Labs and Research Teams: She is an active member of the Mathematics of Information Laboratory (MIL) at EPFL, which focuses on the theoretical underpinnings of machine learning, signal processing, optimization, and statistical inference.

• Computer Architecture
• Processor Design
• Hardware Systems
• +3 more

Louis Coulon serves as a Doctoral Assistant (Researcher) at the Processor Architecture Laboratory (LAP) within the Institute of Computer Science, School of Computer and Communication Sciences at the Swiss Federal Institute of Technology in Lausanne (EPFL). Concurrently, he is enrolled as a doctoral student in the Doctoral Program in Computer and Communication Sciences (EDIC). His research centers on advanced computing systems, with primary focus areas: Computer Architecture Processor Design Hardware Systems Parallel Computing Low-Power Design Embedded Systems Based at office INF 132 (Building INF, Station 14, Lausanne), he contributes to LAP's mission of pioneering processor innovation. Coulon's work bridges theoretical computer science and practical hardware implementation, targeting energy-efficient computational solutions for modern computing challenges.

• Signal Processing
• Machine Learning
• Data Science
• +4 more

Adam Hazimeh is a Doctoral Assistant at the Signal Processing Laboratory 4 (LTS4) within the Institute of Electrical Engineering (IEM) at École Polytechnique Fédérale de Lausanne (EPFL), School of Engineering. He is concurrently pursuing his doctoral studies in the Doctoral Program in Computer and Communication Sciences (EDIC). His research focuses on areas within signal processing and data science, with strong connections to machine learning, optimization, and artificial intelligence. The work conducted at LTS4 emphasizes theoretical and applied aspects of information processing, including sparse modeling, high-dimensional statistics, and large-scale optimization. The absence of listed publications or awards suggests he is in the early or mid-stages of his doctoral career. No advising or grant activities are mentioned. He is based in office ELE 121 at EPFL.

• Machine Learning
• Optimization
• Computer Science
• +3 more

Bettina Ursula Messmer is a Doctoral Assistant at the Machine Learning and Optimization Laboratory (MLO) within the School of Computer and Communication Sciences at École Polytechnique Fédérale de Lausanne (EPFL). She is concurrently enrolled in the Doctoral Program in Computer and Communication Sciences under the EDIC doctoral school. Her research focuses on areas related to machine learning and optimization, leveraging advanced computational techniques to solve complex problems in artificial intelligence and data science. Her work is situated in the broader domains of computer science and algorithmic design, contributing to ongoing research in intelligent systems and optimization methodologies. Bettina is actively involved in research and academic activities at EPFL and has no listed scientific awards at this time. She does not currently supervise any students and is not associated with any specific grants or labs beyond the MLO laboratory. The Machine Learning and Optimization Laboratory (MLO) at EPFL is her primary research environment, supporting her doctoral work in algorithm development and intelligent systems.

• Programming Language Theory
• Type Systems
• Scala
• +11 more

Yichen Xu is a Doctoral Assistant at the Programming Methods Laboratory (LAMP1) within the School of Computer and Communication Sciences at École Polytechnique Fédérale de Lausanne (EPFL). He is currently pursuing his Ph.D. in Computer Science under the supervision of Professor Martin Odersky, the creator of Scala. Bachelor of Engineering in Computer Science, Beijing University of Posts and Telecommunications (2018–2022) Doctor of Philosophy in Computer Science, EPFL (2022–present) Yichen's research bridges programming language theory and machine learning. His primary focus lies in advancing Scala's type system, particularly through work on Capture Calculus and Generalized Algebraic Data Types (GADTs), aiming to achieve safe and efficient effect tracking. He has also made significant contributions to graph representation learning, especially in contrastive learning frameworks for graphs. His work spans both theoretical foundations and practical implementations in compilers and open-source libraries. His recent publications reveal a strong trend in formal methods for programming languages and self-supervised learning on graphs. Key themes include data race prevention via flexible type systems, formalization of inference rules in type calculi, and empirical studies on contrastive learning with adaptive augmentation and structure-aware mining. These works have been published in venues such as IWACO, NeurIPS, WWW, and Scala Symposium. First Prize in NSCSCC 2020 competition (EasterMIPS CPU project) Yichen has been actively involved in mentoring and collaborative research, contributing to major projects like CodeGeeX and the Scala 3 compiler (dotty). He has worked closely with researchers including Prof. Shu Wu, Prof. Zhilin Yang, Dr. Aleksander Boruch-Gruszecki, and Yanqiao Zhu. His open-source contributions include tools like PyGCL, fscala2c, and meow, reflecting a strong commitment to practical software development and community engagement. He is part of the Programming Methods Laboratory at EPFL and has previously been affiliated with research groups at CRIPAC (CASIA) and IIIS (Tsinghua University), forming a broad collaborative network in programming languages and machine learning.

• Computational Biology
• Quantitative Biology
• Cancer Genomics
• +3 more

Ana Isabel Montejano Montelongo serves as a Doctoral Assistant in the Oricchio Group at the Swiss Institute for Experimental Cancer Research (ISREC), operating under the School of Life Sciences at the Swiss Federal Institute of Technology in Lausanne (EPFL). She is concurrently enrolled in the Doctoral Program in Computational and Quantitative Biology, reflecting her dual role as both researcher and doctoral candidate. Her research spans computational biology and quantitative approaches to cancer mechanisms, with concentrated expertise in cancer genomics, epigenetic regulation, and molecular oncology. She applies high-throughput sequencing data analysis and computational modeling to investigate genomic instability and epigenetic alterations in tumor development, leveraging interdisciplinary methodologies at the intersection of biology and data science. No scientific awards or student advisees are documented in the available records, consistent with her status as an active doctoral researcher.

Ekansh SareenView profile

Research Fellow

• Medical Image Processing
• Biomedical Engineering
• Signal Processing
• +7 more

Ekansh Sareen is a Doctoral Assistant at the Medical Image Processing Laboratory (MIPLAB) within the School of Engineering at École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. He is concurrently enrolled in the Doctoral Program in Electrical Engineering (EDEE) under the Doctoral School (EDOC), reflecting his dual role as a researcher and PhD candidate. His work is based at Campus Biotech in Geneva, where MIPLAB conducts cutting-edge research in biomedical imaging and computational methods for healthcare applications. His research interests lie at the intersection of engineering and medicine, with a focus on medical image processing , signal processing , and machine learning . These areas are central to developing automated tools for disease detection, image segmentation, and diagnostic support systems. Given his affiliation with MIPLAB, his work likely involves deep learning models applied to MRI, CT, or ultrasound data, contributing to advancements in precision medicine and digital health. While no publications are listed in the provided text, the research output from MIPLAB typically spans computer vision, artificial intelligence in healthcare, and biomedical signal analysis. The lab’s work often emphasizes translational research, aiming to bridge the gap between algorithmic innovation and clinical utility. Future trends in his research may include explainable AI, federated learning for medical data, and integration with electronic health records. Scientific Awards: No awards mentioned. As a Doctoral Assistant, Ekansh is involved in research and potentially teaching or mentoring, though no advisees are listed. He does not appear to lead independent grants, but likely contributes to larger collaborative projects within EPFL or with clinical partners. MIPLAB is part of a broader ecosystem of health technology innovation at EPFL, collaborating with hospitals and industry partners to develop real-world medical solutions. The laboratory environment fosters interdisciplinary collaboration, combining expertise from electrical engineering, computer science, and clinical medicine. Ekansh’s position places him at the forefront of academic research in medical AI, with opportunities to publish in top-tier journals and present at international conferences. His career trajectory is aligned with academic or industrial research in biomedical engineering and AI-driven healthcare technologies.

• Computational Chemistry
• Molecular Simulation
• Materials Science
• +2 more

Anastasia Blokhina is a Doctoral Assistant at the Laboratory of Molecular Simulation (LSMO) at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Basic Sciences and the Institute of Chemical Sciences and Engineering. She is based at the EPFL Valais Wallis campus in Sion, Switzerland, and is concurrently pursuing her doctoral studies in the Doctoral Program in Chemistry and Chemical Engineering (EDCH). Her research is centered in the domain of computational and theoretical chemistry , with a focus on molecular simulation techniques applied to chemical and materials systems. As a member of LSMO, her work likely involves modeling molecular structures, dynamics, and interactions to understand and predict material properties. While specific publications and research outputs are not listed in the available data, her position indicates active involvement in research projects within the laboratory. Anastasia is currently active and holds a full-time research and doctoral training role. There is no indication of part-time status, retirement, or former staff designation.

Timothée FerrariView profile

Researcher

• Biotechnology
• Bioengineering
• Systems Biology
• +2 more

Timothée Ferrari is a Researcher and Doctoral Assistant at the Institute of Bioengineering within the School of Life Sciences at École Polytechnique Fédérale de Lausanne (EPFL), concurrently pursuing doctoral studies in the Biotechnology and Bioengineering program. His institutional affiliations span both academic staff roles and student enrollment under EPFL's structured hierarchy. His research focuses on Biotechnology and Bioengineering with specialized expertise in Systems Biology, Genomics, and Gene Regulation, directly aligning with the experimental frameworks of the Deplancke Laboratory. These interests drive investigations into genomic regulatory mechanisms and bioengineering applications within high-throughput experimental systems. As an integral member of the Deplancke Group, he operates within the Institute of Bioengineering's collaborative ecosystem, contributing to interdisciplinary projects that bridge molecular biology and computational genomics. His work supports the laboratory's mission to decode transcriptional regulation through cutting-edge methodologies.

Angelika GebhartView profile

Researcher

• Biotechnology
• Bioengineering
• Genomics
• +3 more

Angelika Gebhart is a Doctoral Assistant and PhD student at École polytechnique fédérale de Lausanne (EPFL), affiliated with the School of Life Sciences (SV), Institute of Bioengineering (IBI-SV), and the Deplancke Group (UPDEPLA). She is concurrently enrolled in the Doctoral Program in Biotechnology and Bioengineering (EDBB) under the EDOC school. Her research is conducted within a leading bioengineering and genomics research environment, focusing on gene regulation and systems biology. The Deplancke Lab employs cutting-edge genomic and computational approaches to understand transcriptional regulation in health and disease. Angelika is actively contributing to research in biotechnology and bioengineering through her doctoral work. While no publications or awards are listed in the provided information, her position within a prominent research group indicates active engagement in high-impact scientific inquiry. Institution: École polytechnique fédérale de Lausanne (EPFL) School: School of Life Sciences (SV) Department: Institute of Bioengineering (IBI-SV) Research Unit: UPDEPLA (Deplancke Group) Academic Status: Doctoral Assistant and PhD Student Doctoral Program: Biotechnology and Bioengineering (EDBB) As a doctoral researcher, she is likely involved in securing or contributing to research grants and may mentor junior lab members in the future. No formal advisees are listed at this stage. The Deplancke Lab at EPFL is a dynamic research environment focused on functional genomics, regulatory genomics, and integrative systems biology, providing a strong foundation for her scientific development.