جستجوی استاد راهنمای دانشگاهی

• Energy systems optimization
• Conceptual process design
• Life cycle assessment
• +۷ مورد دیگر

André Bardow is a Full Professor at the Department of Mechanical and Process Engineering, ETH Zürich. His research focuses on energy systems optimization, life cycle assessment, computer-aided molecular design, and CO2 capture/utilization. Professor (ETH Zürich, 2020–present) Head of Institute of Technical Thermodynamics (RWTH Aachen University, 2010–2020) Visiting Professor (University of California, Santa Barbara, 2015/16) Part-time Director (Forschungszentrum Jülich, 2017–2022) Associate Professor (TU Delft, 2007–2010) Research Interests: His work spans energy and process systems engineering, with emphasis on sustainable technologies. Key areas include: Computer-aided molecular and process design Machine learning for chemical engineering Carbon capture and utilization (CCU) Life cycle assessment (LCA) of industrial processes Thermo-economic modeling of energy systems Multiphase equilibrium analysis Publication Trends: Recent articles focus on integrating machine learning with process design, optimizing CO2 capture in steel production, and advancing electrochemical cooling technologies. Subfields include sustainable plastics, ORC working fluids, and solvent mixture design. Scientific Awards: Fellow of the Royal Chemical Society Recent Innovative Contribution Award (EFCE, 2019) PSE Model-Based Innovation Prize (2018) Covestro Science Award (first recipient) Arnold-Eucken-Award (VDI-GVC) Highly Cited Researcher (Clarivate, 2024) Advising and Grants: Professor Bardow mentors students in process optimization and leads projects like Systemic expansion of territorial CIRCULAR Ecosystems for end-of-life FOAM (Grant 101036854, EC).

Philipp Rehnerمشاهده پروفایل

مدرس

• Classical Density Functional Theory
• Thermodynamic Modeling
• Computer-Aided Molecular Design
• +۵ مورد دیگر

Dr. Philipp Rehner is a Lecturer at the Department of Mechanical and Process Engineering at ETH Zürich. He holds a master’s degree in process engineering from the University of Stuttgart and completed his Ph.D. there under Professor Joachim Gross, focusing on classical density functional theory and interfacial properties of nanodroplets. Since 2021, he has been a postdoctoral researcher and group leader of the Molecular Design Group at ETH Zürich’s Energy and Process Systems Engineering (EPSE) Group. Research Interests: Development and application of classical density functional theory (DFT) for interfacial systems and adsorption modeling Thermodynamic modeling using equations of state (e.g., PC-SAFT, PCP-SAFT) Computer-aided molecular and process design GPU-accelerated computational methods for large-scale simulations Automated parameter prediction for molecular models using machine learning and SMILES representation Key Contributions: Developed the open-source FeOs framework for equations of state and DFT Advanced group-contribution methods for binary interaction parameters in thermodynamic models Pioneered GPU-accelerated DFT calculations for adsorption in porous materials Recognition: Recipient of the Walter Benjamin Fellowship (German Research Foundation) Labs/Teams: Leader of the Molecular Design Group at ETH Zürich’s EPSE Group Collaborator on interdisciplinary projects involving chemical engineering, computational chemistry, and materials science

Priscilla Turelliمشاهده پروفایل

مدرس

• Virology
• Immunology
• Molecular Biology
• +۵ مورد دیگر

Priscilla Turelli is a Lecturer at EPFL's EDMS (Doctoral School of Life Sciences) and a Senior Scientist in the Federal School of Life Sciences. Her primary affiliation is with the Laboratory of Virology and Structural Immunology under the SV-IN unit, and she also collaborates with the Antanasijevic Group. She holds positions in both research and teaching roles, including faculty representation for P3-related scientific activities. Education: PhD in Cellular Biology (1997) - Université de la Méditerranée Master in Cellular Biology (1992) - Université de la Méditerranée Scientific Baccalaureate (1987) - France Research Focus: Her work spans virology, immunology, and epigenetics with a focus on: - KRAB zinc finger proteins' role in cancer and gene regulation - SARS-CoV-2 antibody development and viral mechanisms - Transposable elements' impact on human development and disease Key Research Trends in Publications: Recent work emphasizes structural virology (e.g., ACE2/SARS-CoV-2 interactions), epigenetic control via KRAB-ZFPs, and translational research in antiviral therapeutics. Her lab pioneered the discovery of KRAB-ZFPs' dual role in tumor suppression and immune defense mechanisms. Awards: 2023: Innosuisse Business Concept Training 2004: Bristol-Myers Squibb AIDS Award 1997-1999: Human Frontier Science Program Fellowship Grants & Teams: Leads interdisciplinary projects at EPFL's SV-IN lab and collaborates with industry partners (e.g., Innosuisse). Current projects include: - Development of broad-spectrum SARS-CoV-2 antibodies - KRAB-ZFP-driven cancer immunotherapies - Machine learning applications in protein design Labs/Teams: Core member of the Antanasijevic Lab (UPANTANASIJEVIC unit), coordinating multidisciplinary teams in structural immunology and viral pathogenesis.

Nicolás Vila Blancoمشاهده پروفایل

استادیار

• Medical Image Processing
• Deep Learning
• Biomedical Engineering
• +۴ مورد دیگر

Nicolás Vila Blanco is an Assistant Professor at the University of Santiago de Compostela, primarily affiliated with the Information Technologies Research Center (CiTiUS). His work bridges Medical Image Processing and Deep Learning through software development and algorithm optimization. Education includes: PhD in Information Technology Research (Universities of Santiago de Compostela and Coruña) M.Sc. in Data Science and Computer Engineering (University of Granada) B.Sc. in Computer Science (University of Vigo) Research focuses on applying Artificial Intelligence to biomedical challenges, particularly in dental imaging and cardiac diagnostics . Key contributions include: Developing IDALib (Image Data Augmentation Library) Creating DenTiUS Deep Plaque software for dental plaque analysis Designing PrimerEvalPy for microbiome primer evaluation Building gVARVI for heart rate response analysis Recent publications demonstrate expertise in: Clinical software development Deep learning architectures (U-Net, Few-Shot Learning) Medical imaging applications Biomedical data processing AI in dental diagnostics Microbiome sequencing techniques

Johannes Schillingمشاهده پروفایل

پژوهشگر

• AI-driven thermodynamic property prediction
• Carbon capture and storage
• Life cycle assessment
• +۳ مورد دیگر

Dr. Johannes Schilling is a Researcher affiliated with the Professorship for Energy and Process Systems Engineering at ETH Zürich. He holds a PhD in Mechanical Engineering from RWTH Aachen University (2020), where he focused on integrated thermo-economic design of processes and molecules. Since 2020, he has led research teams in molecular design, carbon capture, and AI-driven thermodynamic property prediction at ETH Zürich under Prof. André Bardow. His work emphasizes bridging academia and industry through innovations like the PrISMa platform for sorbent-based carbon capture screening. Education: Bachelor's/Master's in Mechanical Engineering (2009–2014), RWTH Aachen University PhD in Technical Thermodynamics (2015–2020), RWTH Aachen University Postdoc (2020–present), ETH Zürich Research Interests: AI-driven prediction of physical properties (e.g., SMILES-based models) Carbon capture, utilization, and storage (CCUS) Integrated design of molecules and processes Life cycle assessment (LCA) for sustainable chemical systems Grants & Recognition: NCCR Turbo Grant (2023) for AI-driven chemical property prediction Key Projects: Leader of the PrISMa platform for holistic carbon capture material screening and co-developer of the SPT-PC-SAFT model for thermodynamic property prediction. His work spans AI integration into traditional thermodynamics and sustainable process design. Labs/Teams: Heads research teams focused on molecular design, carbon technologies, and high-throughput material screening at ETH Zürich's Energy and Process Systems Engineering Group.

Luca Bosettiمشاهده پروفایل

مدرس

• Machine Learning
• Chemical Process Design
• Crystallization Technology
• +۵ مورد دیگر

Luca Bosetti is a Lecturer at the Department of Mechanical and Process Engineering at ETH Zürich , focusing on machine learning applications in chemical engineering and crystallization process design. Key research areas: Machine learning for thermodynamic predictions, sustainable chemical recycling, crystallization technology, and lifecycle assessment. Collaborations: Active partnerships with André Bardow, Marco Mazzotti, Benedikt Winter, and Johanna Lindfeld. Recent projects: Development of ML-CAMPD frameworks for solvent design, CO2 electrolyzer integration, and polyurethane waste recycling. His work combines machine learning with process engineering to address sustainability challenges in the chemical industry, including CO2 utilization , chemical recycling , and energy-efficient separations . Publications span journals like Computers & Chemical Engineering and Crystal Growth & Design , with recent contributions on hybrid crystallization processes , liquid-liquid equilibria , and automated LCA tools . His research has received funding from the CIRCULAR FOAM project (EC grant 101036854) , aiming to expand circular ecosystems for foam waste.

Christophe Dessimozمشاهده پروفایل

استاد

• Computational Biology
• Genomics
• Bioinformatics
• +۵ مورد دیگر

Christophe Dessimoz is a Professor at the University of Lausanne's Department of Ecology and Evolution, affiliated with the Swiss Institute of Bioinformatics (SIB). He holds a joint appointment with University College London (UCL), where part of his lab remains active. His academic journey includes a Master's in Biology (ETH Zurich, 2003) and a PhD in Computer Science (ETH Zurich, 2009). He has held roles at ETH Zurich, EMBL-EBI, and UCL before joining the Center for Integrative Genomics (CIG) as a Swiss National Science Foundation (SNSF) Professor in 2015. His research bridges computational methods and evolutionary biology, focusing on gene and genome evolution, orthology inference, and phylogenetic analysis. Key projects include the Quest for Orthologs consortium and the OMA database. He has developed tools like OMA Standalone, ALF, and Matreex, which aid in genomic analysis and visualization. His work has been recognized with awards such as the SIB Young Bioinformatician Award (2012), Google Faculty Award (2015), and EMBO Young Investigator (2016) status. His lab collaborates across disciplines, addressing questions like the conservation of membrane proteins and the evolutionary origins of eukaryotes. Ongoing projects explore AI ethics in life sciences and federated data querying for biomedical research. Publications highlight advancements in orthology benchmarking, phylogenetic tree inference, and applications of genomic data to medicine and evolutionary biology. His team includes PhD students, postdocs, and visiting researchers, fostering a collaborative environment for computational and experimental work.

• Synthesis and Catalysis
• Stereoselective synthesis
• Functional materials
• +۵ مورد دیگر

Prof. Olimpia Mamula Steiner is an Ordinary Professor at the Haute école d'ingénierie et d'architecture de Fribourg (HEIA-FR), part of the University of Applied Sciences and Arts Western Switzerland (HES-SO). She leads research in synthesis, catalysis, and functional materials development from her office in Fribourg, Switzerland. Her educational background includes: BSc HES-SO in Chemistry from HEIA-FR, specializing in Organometallic Catalysis and Organic Chemistry MSc HES-SO in Life Sciences, focusing on Asymmetric Synthesis Bachelor in Chemistry from the University of Fribourg, with emphasis on Chemistry of d and f metals Prof. Mamula Steiner's research spans multiple chemistry domains with strong focus on stereoselective synthesis, nanoparticle development, and functional materials. Her work bridges fundamental chemical research with practical applications in medical diagnostics, environmental monitoring, and advanced manufacturing. She has pioneered innovative approaches to chiral metal complexes, sensors for hazardous compounds like phosgene, and novel materials for electroluminescent displays, demonstrating exceptional interdisciplinary integration. Her publication record reveals consistent expertise in rhenium anticancer complexes, pinene-based ligand systems, and sensor development. Recent work shows increasing focus on medical applications, particularly in cancer research and diagnostic tools, while maintaining strong foundations in synthetic methodology and materials characterization. The interdisciplinary nature of her research is evident in collaborations spanning chemistry, medicine, engineering, and environmental science. Prof. Mamula Steiner actively mentors students and researchers, having supervised PhD work on pinene-pyridine derivatives and their applications. Her laboratory emphasizes sustainable chemistry approaches, including waste-to-resource conversion and eco-friendly manufacturing processes, reflecting contemporary priorities in green chemistry.

Matthew Wodrichمشاهده پروفایل

پژوهشگر

• Computational Chemistry
• Homogeneous Catalysis
• Organic Reaction Mechanisms
• +۴ مورد دیگر

Matthew Wodrich is a Research and Teaching Associate at the Institute of Chemical Sciences and Engineering (ISIC-GE) and Computational Molecular Design Laboratory (LCMD) under the School of Basic Sciences at Ecole Polytechnique Fédérale de Lausanne (EPFL) . His research focuses on computational chemistry, homogeneous catalysis, and asymmetric synthesis, with significant contributions to reaction mechanism modeling and enantioselectivity prediction. He actively contributes to teaching programs at EPFL's SCGC-ENS division. Key Research Areas: Computational Reaction Modeling, Enantioselectivity Prediction, Volcano Plot Analysis, Metal-Ligand Cooperative Catalysis, Photocatalysis, and Machine Learning in Chemistry. Recent Article Trends: His 2022-2025 work emphasizes computational catalyst optimization , solvent effects in reaction selectivity , and machine learning-driven enantioselectivity analysis , with applications in transition metal catalysis, hypervalent iodine chemistry, and CO 2 reduction.

Jean-Louis Reymondمشاهده پروفایل

استاد

• Chemical Space
• Cheminformatics
• Peptide Chemistry
• +۵ مورد دیگر

Professor Jean-Louis Reymond is a distinguished academic at the University of Bern, currently serving as Dean of the Faculty of Science since 2024. He leads the Reymond Research Group within the Department of Chemistry, Biochemistry and Pharmaceutical Sciences. Previously, he served as Director of the Department of Chemistry and Biochemistry from 2015-2017. His educational background includes diploma studies in Chemistry and Biochemistry at ETH Zürich (1981-1985), a Ph.D. in Natural Products Synthesis at the University of Lausanne (1986-1989), and post-doctoral research on Catalytic Antibodies at Scripps Research Institute (1990-1991). He joined the University of Bern as a Professor in 1997 after serving as Assistant Professor at Scripps Research Institute (1992-1997). Reymond's research centers on The Chemical Space Project, which explores the vast universe of possible chemical compounds with potential medical applications. His work spans three interconnected areas: Peptide Chemistry (design of bioactive peptides including dendrimers and polycyclic structures), Cheminformatics (development of the GDB chemical universe database), and Medicinal Chemistry (computer-aided design of small molecule modulators). His research has significant implications for addressing antimicrobial resistance through novel peptide-based therapeutics. Analysis of his recent publications reveals a strong focus on navigating and exploiting chemical space for drug discovery, particularly in antimicrobial applications. His work combines computational methods with synthetic chemistry to identify novel scaffolds and optimize bioactive compounds. The 2024-2025 publications demonstrate continued innovation in peptide design, chemical space visualization, and applications in drug delivery systems. ERC Advanced Grant (2020) for project SPACE4AMPS (€2.5 million over 5 years) Professor Reymond actively mentors numerous graduate students and leads a vibrant research group that collaborates across disciplines. His research is supported by significant grants including the ERC Advanced Grant and participation in the NCCR TransCure initiative. The Reymond Research Group maintains strong connections with other research units at the University of Bern and international collaborators. The research group operates state-of-the-art facilities for peptide synthesis, cheminformatics analysis, and biological testing. They have developed specialized tools including the GDB chemical space database (www.gdb.unibe.ch) and collaborate with the NCCR TransCure consortium on transporter and ion channel research. Their work on antimicrobial peptides positions them at the forefront of addressing the global antimicrobial resistance crisis.