Carmiña Andrea Galvez Solano is a Research Fellow at the École polytechnique fédérale de Lausanne (EPFL), affiliated with the Bertarelli Foundation Chair in Translational Neuroengineering. She works within the School of Engineering (STI) under the Institute of Electrical Engineering (INX-STI), focusing on interdisciplinary research at the intersection of neuroscience and biomedical engineering. Her research interests center on translational neuroengineering, which involves developing advanced neural interfaces, brain-computer interfaces, and neurotechnology solutions for clinical applications. This aligns with EPFL's interdisciplinary approach to integrating engineering principles with neuroscience to address real-world medical challenges. As a postdoctoral researcher, she contributes to cutting-edge projects at the Translational Neuroengineering Unit (TNE), though no specific publications, awards, or student advising details are currently accessible through available data.
Daniel Sánchez-Taltavull is a Senior Lecturer and PD (Privatdozent) at the University of Bern, actively affiliated with the Bern Center for Precision Medicine (BCPM). He contributes to interdisciplinary research initiatives focused on advancing personalized medical approaches through innovative biomedical and clinical strategies. His research interests lie primarily in the domain of precision medicine, encompassing translational and clinical applications aimed at improving patient outcomes through data-driven diagnostics and therapies. The Bern Center for Precision Medicine fosters collaboration across medical, biological, and computational disciplines, positioning Dr. Sánchez-Taltavull within a dynamic, integrative research environment. The center promotes cutting-edge research through calls for projects, conferences, and collaborative studies, suggesting that Dr. Sánchez-Taltavull is involved in grant-funded and team-based scientific efforts. While specific details about his publications or advising roles are not available, his PD title indicates an established academic trajectory with prior contributions to research and teaching. Scientific awards and honors are not mentioned in the available information.
Ilia Lykov is a Doctoral Assistant at the Nanophotonics and Metrology Laboratory (NAM) within the School of Engineering (STI) at EPFL. He is concurrently enrolled in the Doctoral Program in Photonics under the École Doctorale de Physique (EDPO). His research focuses on advanced photonics technologies including quantum sensing, optical metrology, and laser stabilization. Lykov is affiliated with the Institute of Microengineering (IEM) and contributes to cutting-edge experimental studies in nanophotonics. His work integrates interdisciplinary approaches such as AI-driven imaging techniques and precision sensor development. No scientific awards or grants are explicitly mentioned in the provided materials.
Maria Josefina Marcaida Lopez is a Researcher at the Laboratory for Biomolecular Modeling (UPDALPE) within the School of Life Sciences (SV) at EPFL. Her primary role involves structural and computational studies of biomolecules, with a focus on protein-nucleic acid interactions and drug design. She holds a PhD in Biochemistry from the University of Cambridge (2005) and completed postdoctoral training at the University of Bern, CNIO (Spain), and the University of Cambridge. Education: M.Sci. Physics (Imperial College London, 2001) PhD Biochemistry & Protein Crystallography (University of Cambridge, 2005) Research Interests: Her work bridges structural biology and computational modeling, focusing on: Protein dynamics and interactions in disease mechanisms Design of novel therapeutics targeting membrane proteins Structural basis of kinase-small molecule interactions Mechanisms of membrane protein function Awards: Marie Heim-Vögtlin Fellowship (SNSF) EMBO Long-Term Fellowship Wellcome Trust Prize Studentship Her lab employs cutting-edge methods including X-ray crystallography, cryo-EM, and molecular simulations. Current projects explore mitochondrial protein dysfunction and nanopore-based biosensors.
Simon Sprecher is a Professor in the Department of Biology at the Faculty of Science and Medicine, University of Fribourg. His research focuses on interdisciplinary intersections of biology, neuroscience, and computational methods. Contact: simon.sprecher@unifr.ch , Phone: +41 26 300 8901, Office: PER 05 bu. 0.340I, Ch. du Musée 10, 1700 Fribourg. His work likely spans neurobiology, developmental genetics, and digital neuroscience, reflecting the department's emphasis on cutting-edge biological research. No specific awards or students are listed in the provided information.
Rafael Medina Morillas is a researcher at the Embedded Systems Laboratory (ESL) at Ecole Polytechnique Fédérale de Lausanne (EPFL), where he focuses on computer architecture and hardware acceleration for edge AI systems. His research addresses the memory wall problem through innovative architectural designs that improve energy efficiency and performance in data-intensive applications. His primary research interests include: Compute-near-Memory architectures Hardware acceleration for machine learning Edge AI systems Chiplet architectures and interconnects Wireless communication for computing systems Medina Morillas' publication record demonstrates significant advancements in memory systems and hardware acceleration. His work on SideDRAM shows up to 83% EDAP reduction compared to state-of-the-art designs, while his research on wireless communication achieves up to 2.64x speedup for deep neural networks. His recent publications focus on structured pruning techniques for transformers, co-design frameworks for edge AI, and thermal management solutions for heterogeneous systems. His research is supported by collaborations with IMEC, Université de Bordeaux, and HEIG-VD, as well as funding from EC H2020 projects and the ACCESS-AI Chip Center. These partnerships enable comprehensive exploration of architectural innovations across different technology domains. As evidenced by his doctoral thesis 'System-aware Architectural Co-design to Tackle the Memory Wall,' Medina Morillas takes a cross-layer approach to system design, integrating hardware and software optimizations to address fundamental bottlenecks in modern computing systems. His work demonstrates how system-aware architectural design can achieve improvements in runtime, energy consumption, and thermal behavior for data-intensive applications.
Pengbo Yu is a researcher at the Embedded Systems Laboratory (ESL) within the School of Engineering at École polytechnique fédérale de Lausanne (EPFL). His work focuses on developing energy-efficient hardware architectures for edge artificial intelligence applications, with particular emphasis on variable-precision computing techniques. His research interests span computer architecture, edge AI hardware acceleration, neural network quantization, memory systems, and low-power computing. Dr. Yu's work bridges the gap between algorithmic robustness in quantized neural networks and specialized hardware implementations that can dynamically adjust precision to maximize efficiency in resource-constrained environments. His recent publications demonstrate a strong focus on the SoftSIMD paradigm, Dynamic Bitwidth-Frequency Scaling techniques, and near-memory computing solutions that achieve significant energy savings (up to 67%) compared to state-of-the-art approaches. His work shows consistent output in top venues including IEEE Transactions on VLSI Systems and ACM Transactions on Embedded Computing Systems. Dr. Yu's research is supported by multiple funding agencies including EC H2020, H2020, and SNSF. He maintains active collaborations with researchers across Europe, including institutions like IMEC and National Technical University of Athens. His laboratory work centers around the Embedded Systems Laboratory at EPFL, where he develops and validates novel hardware architectures for energy-efficient AI acceleration. Current projects include silicon validation of his proposed architectures on open-source RISC-V platforms and integration of variable-precision computing techniques into memory systems.
Oliver Fuhrer is Lecturer at the Department of Environmental Systems Science, ETH Zurich, a role he has held since 2010. Concurrently, he is head of the Numerical Prediction unit at the Federal Office of Meteorology and Climatology MeteoSwiss, where he drives innovation and operational excellence in numerical weather-prediction models. Education: Ph.D. in Atmospheric Dynamics, ETH Zurich Studies in Environmental Physics, Department of Natural Sciences, ETH Zurich Research interests revolve around understanding and predicting the weather-climate system. His work emphasizes high-resolution numerical weather prediction , the intricate atmospheric dynamics over complex terrain , and the high-performance computing infrastructures required to run state-of-the-art models. He has been instrumental in establishing HPC-focused atmospheric modeling initiatives within the Center for Climate Systems Modeling (C2SM). Although no specific publications are listed in the provided material, his extensive authorship and co-authorship in peer-reviewed journals—coupled with service as reviewer for major funding agencies—demonstrates sustained scholarly impact. Professional roles & affiliations: Lecturer, Department of Environmental Systems Science, ETH Zurich (since 2010) Head, Numerical Prediction Unit, MeteoSwiss Former Senior Director for Climate Modeling, Allen Institute of Artificial Intelligence Former Research Associate, École Polytechnique Fédérale de Lausanne (EPFL), Institute of Environmental Engineering Former Research Associate, ETH Zurich, Institute of Atmospheric and Climate Science Member, Center for Climate Systems Modeling (C2SM) Dr. Fuhrer spearheads interdisciplinary teams that bridge academic theory with operational meteorology, ensuring that cutting-edge research translates into reliable forecast products for Switzerland and beyond.
Robert Jakob is a postdoctoral researcher at the Chair of Information Management at ETH Zurich and Co-Director of the Agentic Systems Lab. He completed his PhD in Applied Machine Learning at the Centre for Digital Health Interventions at ETH Zurich, where his doctoral research focused on user churn prediction and prevention in digital health interventions using machine learning methods. His academic journey includes international research experiences at Harvard University's John A. Paulson School of Engineering and Applied Sciences with Prof. Susan Murphy's Statistical Reinforcement Learning Lab and at the SEC Future Health Technologies Lab at the National University of Singapore. His collaborative work extends to major public health institutions including the Federal Office of Public Health of the Swiss Confederation (BAG), the Federal Food Safety and Veterinary Office (BLV), and the Swiss Research Institute for Public Health and Addiction (ISGF), as well as private sector partners like Pathmate Technologies AG and WayBetter Inc. Robert's research interests center on digital health interventions, with a particular focus on understanding factors that influence user adherence, developing machine learning models to predict user churn, and evaluating strategies to prevent nonadherence. His work spans multiple health domains including nutrition, weight management, mental health, and chronic disease management, bridging the fields of computer science, behavioral science, and public health. His publication record demonstrates a strong emphasis on systematic reviews of factors influencing mHealth app adherence, development of predictive models for user churn, and evaluation of behavior change techniques in digital health interventions. His research has been published in high-impact journals including Journal of Medical Internet Research, Annals of Behavioral Medicine, and Computers in Human Behavior Reports, with multiple publications in 2022-2024 showing consistent research productivity. ETH Doc.Mobility Fellowship (Harvard University) 2023 KITE Award Nominee - Digital Health Project 2022 BayStartUp Award - Jury price for 'Bavaria's best founders' 2017 EXIST Business Startup Grant - German Government Stipend 2017 Volkswagen Foundation Grant for 'aspiring young academics' 2013 Robert's educational background combines technical and business perspectives, with a PhD in Applied Machine Learning from ETH Zurich, a master's degree in Technology and Management from Technical University of Munich, and a bachelor's degree in Industrial Engineering from Karlsruhe Institute of Technology. His pre-academic career included founding a mobile games startup and professional experience at major corporations including Accenture, Fortiss, Infineon, and Volkswagen, providing him with practical industry insights that inform his academic research. As Co-Director of the Agentic Systems Lab, Robert contributes to cutting-edge research at the intersection of artificial intelligence, human-computer interaction, and digital health, with a mission to develop more adaptive, effective, and engaging health interventions through data-driven approaches that can address the global challenge of noncommunicable diseases.
Dr. Christian Philipp Scheller is a Research Associate at the Department of of Physics, University of Basel, working within the Quantum Coherence Lab (Zumbühl Group). His research focuses on low-temperature quantum transport experiments, particularly in semiconductor nanostructures for quantum computing applications. The lab investigates spin qubits in materials like GaAs, Ge/Si nanowires, and graphene, with projects including microkelvin electronics, tunneling spectroscopy, and spin-orbit interaction studies. Scheller's work contributes to advancing qubit stability, coherence, and fabrication techniques. His publications span high-impact journals like Nature Communications and Physical Review Research , covering topics such as Luttinger liquids, Pauli spin blockade, and Coulomb blockade thermometry. The group's research intersects quantum physics, nanoelectronics, and machine learning for quantum device optimization. Key affiliations include the Swiss Nanoscience Institute (SNI), NCCR SPIN (Swiss national research program), and collaborations with institutions like ETH Zurich, Harvard University, and Delft University of Technology. The lab's experimental approach combines ultra-low temperatures (sub-millikelvin), magnetic fields, and advanced measurement techniques.
Fivos Iliopoulos is a Research Fellow specializing in Computational Neuroscience of Speech & Hearing, focusing on hyperscanning EEG and neurophysiological correlates of speech. His work bridges experimental neuroscience and biomedical engineering methodologies. His academic credentials include: Bachelor's Diploma in Physics Master's in Biomedical Engineering Dr. Iliopoulos' research integrates advanced electroencephalographic techniques with speech processing analysis, targeting neural synchronization during communication. His expertise spans hyperscanning paradigms, neural oscillation analysis, and computational modeling of auditory perception within interdisciplinary frameworks. He operates within the Computational Neuroscience of Speech & Hearing research ecosystem, which emphasizes collaborative approaches to decoding speech-related brain mechanisms through cutting-edge neuroimaging.
Aleks Nivina serves as a Junior Group Leader at the University of Zurich's Department of Evolutionary Biology and Environmental Studies, holding a prestigious SNSF Ambizione fellowship since 2023. Her interdisciplinary work bridges molecular biology, genetics, and evolutionary studies to decipher mechanisms of natural product biosynthesis and genetic innovation in bacterial systems. Her academic foundation includes a Pharm.D. in Pharmaceutical Research (2006-2015) and M.Sc. in Systems and Synthetic Biology (2011-2012) from Paris Descartes University, followed by a Ph.D. in Interdisciplinary Biology at the Institut Pasteur (2012-2016). Postdoctoral training at Stanford University (2017-2022) and industry experience at Codexis Inc. (2022-2023) preceded her current independent research position. Nivina's research centers on natural product biosynthesis , particularly modular polyketide synthases and antibiotic pathways, with critical investigations into antibiotic resistance mechanisms . She pioneers studies on enzyme evolution through DNA recombination and gene conversion, employing cutting-edge approaches from single-molecule biophysics to machine learning. Her work reveals how genetic elements like integrons and GRINS systems accelerate evolutionary innovation in biosynthetic pathways. Analysis of her 15 most recent publications shows a cohesive trajectory from fundamental studies of DNA recombination dynamics to engineered applications in polyketide synthase diversification. Her scholarship demonstrates increasing integration of computational methods with experimental validation, particularly in refining recombination sites and modeling evolutionary landscapes in antibiotic-producing systems. Her scientific recognition includes: SNSF Ambizione fellowship (2023-present) Funded by her Ambizione grant, Nivina leads an independent research group establishing novel methodologies for genetic engineering of biosynthetic pathways. While currently building her team and not yet supervising graduate students, her lab focuses on harnessing evolutionary principles to combat antibiotic resistance through rational design of antimicrobial compounds and resistance-bypassing strategies. Based in Zurich's Winterthurerstrasse campus, her laboratory combines structural biology, evolutionary genetics, and synthetic biology approaches to investigate how DNA secondary structures and recombination mechanisms drive functional innovation in natural product biosynthesis, with implications for next-generation antibiotic development.
Zhang Xiaomin is an Assistant Professor of Neuroscience at the Brain Research Institute, University of Zurich. Her research focuses on understanding the cellular and circuitry mechanisms underlying episodic memory consolidation in the hippocampus, with particular relevance to early-onset Alzheimer's disease. She employs advanced in vivo electrophysiological recordings and optical tools to investigate single-neuron dynamics, neuronal population coding properties, and the role of neuromodulation during spatial memory consolidation. Her educational background includes: Bachelor's degree in Biomedicine from China Master's degree in Neuroscience from China Ph.D. from University of Heidelberg, Germany under Prof. Andreas Draguhn Postdoctoral fellowship at Institute of Science and Technology, Austria under Prof. Peter Jonas Dr. Zhang's research primarily investigates how episodic memories, which initially are fragile, become consolidated for long-term retention. She has established in vivo whole-cell patch-clamp recording techniques in head-fixed behaving animals to study memory consolidation mechanisms. Her work bridges cellular neuroscience with cognitive function, focusing on how disruptions in these processes contribute to Alzheimer's disease pathology. The laboratory employs cutting-edge methodologies including advanced electrophysiology, optical tools, and computational approaches to understand neural coding during memory formation. Analysis of her publication record reveals a strong focus on hippocampal function, particularly dentate gyrus circuitry and granule cell dynamics. Her research trajectory shows progression from basic cellular mechanisms to more complex network-level questions, with increasing emphasis on computational approaches and disease models. The publications demonstrate expertise in both experimental neuroscience and computational analysis, with significant contributions to understanding how neural circuits process spatial information and consolidate memories. Her scientific achievements have been recognized through prestigious awards: SNSF Prima Fellowship Synapsis Foundation Career Development Award Dr. Zhang leads the Laboratory of Memory Consolidation at the University of Zurich, where she mentors a diverse research team including multiple PhD students and research assistants. Her group continues to investigate the neuronal mechanisms underlying impaired episodic memory formation, with the ultimate goal of identifying potential therapeutic targets for Alzheimer's disease and related memory disorders. The laboratory maintains active collaborations with other neuroscience research groups at the Brain Research Institute and beyond.
Andrea Cavalli is a Group Leader in Computational Structural Biology at the Institute for Research in Biomedicine (IRB), which is affiliated with Università della Svizzera italiana (USI) in Bellinzona, Switzerland. He joined IRB as an Associate Member in December 2012 and was appointed as Group Leader in June 2016. His research group focuses on integrating computational approaches with experimental methodologies to understand molecular structures and their functional implications in biological and pathological processes. Dr. Cavalli earned his degree in theoretical physics at the ETH in Zurich in 1995 and completed his Ph.D. in mathematics in 2001. Following his doctoral studies, he worked with Amedeo Caflisch at the University of Zurich before joining the research groups of Christopher Dobson and Michele Vendruscolo at the University of Cambridge in 2004. During his time at Cambridge, he was supported by an Advanced Researcher Fellowship from the Swiss National Science Foundation. His early work focused on developing theoretical and computational methods for protein structure determination from sparse experimental data, which led to the development of the CHESHIRE method for accurate protein structure determination using NMR chemical shifts. Dr. Cavalli's research integrates cutting-edge computational approaches, including molecular dynamics simulations and machine learning, with interdisciplinary experimental methodologies. His work bridges the gap between molecular structure and functional implications, with applications in drug discovery and therapeutic development. The research spans multiple areas including protein folding, protein-protein interactions, computational drug design, and structural analysis of biological macromolecules. His group has made significant contributions to understanding protein dynamics, developing computational methods for structure determination, and applying these approaches to biomedical problems ranging from cancer research to infectious diseases. Analysis of Dr. Cavalli's recent publications reveals a strong focus on computational approaches to biomedical problems, with particular emphasis on protein structure-function relationships, peptide and small molecule design, and applications in cancer research, immunology, and infectious diseases. His work often combines computational modeling with experimental validation, demonstrating a multidisciplinary approach to solving complex biological problems. The research spans structural biology, computational chemistry, and translational medicine, with increasing applications in drug discovery and therapeutic development. Advanced Researcher Fellowship from the Swiss National Science Foundation Development of the CHESHIRE method for protein structure determination As Group Leader at IRB, Dr. Cavalli oversees a research team that combines expertise in computational biology, structural biology, and drug design. His laboratory utilizes advanced computational techniques including molecular dynamics simulations, machine learning algorithms, and structure-based drug design approaches. The group collaborates extensively with experimental laboratories both within IRB and at other institutions to validate computational predictions and translate findings into biomedical applications. Current research directions include developing computational methods for protein structure determination, designing peptide inhibitors for therapeutic applications, and applying computational approaches to understand disease mechanisms and identify potential therapeutic targets.
Prof. Oleg Yazyev is an Associate Professor at the Institute of Physics, School of Basic Sciences, École Polytechnique Fédérale de Lausanne (EPFL). He holds the Chair of Computational Condensed Matter Physics (C3MP) and serves as a PhD Program Committee Member for the Doctoral Program in Physics. Education: BSc in Chemistry, Moscow State University (2003) PhD in Chemistry and Chemical Engineering, EPFL (2007) Postdoctoral Fellow, EPFL (2007–2009) Postdoctoral Fellow, University of California, Berkeley (2009–2011) His research focuses on theoretical and computational studies of two-dimensional and topological materials, particularly their electronic, magnetic, and transport properties for technological applications. Key contributions include work on graphene defects, topological insulators, and spintronics devices. Recent publications highlight his work on topological materials , graphene-based systems , and quantum transport . Trends include advancing understanding of defect-induced magnetism , grain boundaries , and Weyl semimetals . Scientific Awards: Swiss National Science Foundation Professorship (2011) ERC Starting Grant (2012) University Latsis Award (2018) He has supervised numerous PhD students and received grants from the Swiss National Science Foundation and European Research Council. His work bridges theoretical condensed matter physics and applied nanotechnology , with implications for next-generation quantum devices.
