جستجوی استاد راهنمای دانشگاهی

Peter A. Flach is Professor of Artificial Intelligence at the Intelligent Systems Laboratory, School of Computer Science, University of Bristol, where he has been faculty since 1997 and was promoted to Professor in 2003. He currently directs the UKRI AI Centre for Doctoral Training in Practice-Oriented Artificial Intelligence and serves as Vice-President of the European Association for Data Science (EuADS), having previously served as its President. His research centers on rigorous evaluation and improvement of machine learning systems, with seminal contributions to classifier calibration (including Beta Calibration and Precision-Recall-Gain curves), explainable AI frameworks, and data science methodology. He pioneered the extension of CRISP-DM to data science trajectories and developed Explainability Fact Sheets for systematic assessment of XAI approaches. His work bridges theoretical foundations with practical deployment in real-world systems. Analysis of his recent publications reveals a dominant focus on interpretable and reliable machine learning, with strong emphasis on performance evaluation metrics, model calibration techniques, and human-centered explainability. His research increasingly addresses healthcare applications through projects like SPHERE and clinical decision support systems, while maintaining core contributions to fundamental ML theory. His scientific recognition includes prestigious fellowships: Fellow of the European Lab for Learning and Intelligent Systems (ELLIS) Fellow of the European Association for Artificial Intelligence (EurAI) Professor Flach has secured major research funding including UKRI Centre for Doctoral Training grants and EU network funding (TAILOR). He leads extensive collaborations across Engineering, Population Health Science, and international institutions (Monash University, Polytechnic University of Valencia), plus over 20 industry partners in the Practice-Oriented AI CDT including LV= and QinetiQ. His work with the SPHERE project demonstrates successful translation of AI research into residential healthcare settings. He leads the Intelligent Systems Laboratory at Bristol, which develops influential open-source tools including the FAT Forensics Python toolbox for algorithmic fairness and the Explainability Fact Sheets framework. His lab maintains strong connections with the European AI community through ELLIS and EurAI, positioning Bristol as a hub for human-centered and methodologically rigorous AI research.

• Machine Learning
• Artificial Intelligence
• Explainable AI (XAI)
• +۳ مورد دیگر

Dr. Vakil Takhaveev is a Lecturer at ETH Zurich's Department of Health Sciences and Technology, within the Institute of Food, Nutrition and Health. His research focuses on DNA damage mechanisms, aging, cancer, and neurodegeneration, with particular emphasis on developing novel DNA-damage-sequencing methods like click-code-seq and TRABI-Seq . He investigates anticancer drug action (e.g., trabectedin), aging clocks using DNA oxidation profiling, and stress-induced carcinogenesis. His work integrates multi-omics approaches and advanced sequencing techniques. Research Directions: Novel DNA-Damage-Sequencing Methods: Developed click-code-seq and TRABI-Seq for genomic mapping of DNA lesions and repair dynamics. Anticancer Drug Action: Explored mechanisms of trabectedin and other chemotherapeutics, linking DNA repair vulnerabilities to therapy resistance. Aging Clocks: Created DNA oxidation-based biomarkers for biological aging using genome-wide profiling in human and mouse models. Stress-Induced Pathologies: Studies metabolic and DNA damage links to early tumorigenesis and neurodegeneration. Awards & Recognition: 2025 Public Award Winner in PIs of Tomorrow competition 2024 ETH Zurich Career Seed Award Best presentation awards (Swiss Chemical Society, American Chemical Society) Grants & Collaborations: Impetus grants for aging clock development Swiss Chemical Society and American Chemical Society fellowships Labs & Teams: Leads research on DNA damage and aging mechanisms at ETH Zurich, collaborating with international groups in oncology and toxicology.

• DNA Damage and Repair
• Aging Mechanisms
• Cancer Biology
• +۶ مورد دیگر

Hoda Heidari is the K&L Gates Career Development Assistant Professor in Ethics and Computational Technologies at Carnegie Mellon University (CMU), with joint appointments in the Machine Learning Department and the Institute for Software, Systems, and Society. She is affiliated with the Human-Computer Interaction Institute and the Heinz College of Information Systems and Public Policy, and co-leads the university-wide Responsible AI Initiative and K&L Gates Initiative for Ethics and Computational Technologies. Education: PhD in Computer and Information Science (University of Pennsylvania), MSc in Statistics (Wharton School) Her research focuses on the Ethical, Societal, and Policy Implications of AI , particularly fairness and accountability in high-stakes domains. Her work includes evaluating risks/benefits of general-purpose AI, human-AI decision-making systems, and AI governance frameworks. She has received multiple awards, including best paper honors at AIES, FAccT, and SAT-ML. Her research is supported by the NSF Program on Fairness in AI, PwC, CyLab, Meta, and J. P. Morgan. Recent Publications examine generative AI safety, fairness measurement, AI incident documentation, and ethical governance. Her teaching includes courses on Responsible AI, ML Ethics, and Societal Decision-Making, with a focus on preparing students to critically analyze AI's societal impact. Scientific Awards: Best Paper (AIES 2024, FAccT 2021, SAT-ML 2023), Exemplary Track Award (EC 2021) Grants: NSF, PwC, CyLab, Meta, J. P. Morgan She advises doctoral students and postdocs across CMU departments and collaborates with interdisciplinary teams. Her service includes organizing AI safety workshops and advising on NIST guidelines for AI red-teaming.

• Ethical Implications of Artificial Intelligence
• Societal Implications of Artificial Intelligence
• Policy Implications of Artificial Intelligence
• +۴ مورد دیگر

Dr. Seyyed Hamed Hosseini Nasab is a Lecturer at the Department of Health Sciences and Technology at ETH Zürich, affiliated with the Institute for Biomechanics and the Laboratory for Movement Biomechanics. His research focuses on biomechanical analysis of musculoskeletal systems, particularly knee mechanics, implant design, and ligament behavior in total knee arthroplasty. He integrates experimental, computational, and clinical approaches to improve surgical techniques and prosthetic design. Key research interests include knee joint loading, ligament elongation patterns, and the influence of implant conformity on post-surgical outcomes. He has contributed to standardized methods for measuring tibiofemoral implant loads and kinematics, earning the European Society of Biomechanics SM Perren Award in 2022. His publications emphasize computational modeling, in vivo testing, and finite element analysis to address challenges in orthopedic engineering. Recent work explores artificial neural networks for real-time knee contact force estimation and the biomechanical implications of surgical procedures like posterior cruciate ligament substitution.

• Biomechanics
• Orthopedic Engineering
• Sports Biomechanics
• +۳ مورد دیگر

Prof. Diego Moretti is a Lecturer at the Department of Health Sciences and Technology (D-HEST), ETH Zurich. He is affiliated with the Institute of Food, Nutrition, and Health (IFNH), located at Schmelzbergstrasse 7 in Zurich. Education: PhD in Food Science and Engineering, ETH Zurich (2002-2006), Thesis: "Iron fortification of rice: a potential strategy to counteract iron deficiency" Diploma in Food Science and Engineering (Dipl.Lm.Ing. ETH), ETH Zurich (1996-2002) Matura typus C, Liceo Cantonale di Bellinzona (1992-1996) Research Interests: Focus on iron metabolism in deficiency/excess states, strategies for correction (fortification/supplementation), and novel tools to evaluate food-based approaches for iron/zinc deficiencies. Utilizes isotopic techniques and molecular markers of iron status. Labs/Teams: Active at the Laboratory of Human Nutrition within ETH Zurich. Collaborates on projects involving nutritional science and public health interventions.

• Nutrition Science
• Iron Metabolism
• Nutritional Fortification
• +۵ مورد دیگر

Prof. Dr. Julia Vogt is an Assistant Professor at the Department of Computer Science at ETH Zürich, leading the Professur für Medizin. Datenwiss. Her research focuses on medical machine learning, data science, and AI applications in healthcare. She specializes in developing interpretable AI systems for clinical decision support, particularly in pediatric diabetes management, medical imaging analysis, and anomaly detection. Her work bridges translational gaps by emphasizing causal approaches and clinical validation. Her academic role includes teaching courses like the Data Science Lab (263-3300-00L/10L) and Topics in Medical Machine Learning (263-5100-00L). Her lab's research spans predictive modeling for nocturnal hypoglycemia, echocardiogram analysis for pulmonary hypertension detection, and multimodal learning in radiology. She also contributes to national pediatric data initiatives like SwissPedHealth. Key technical areas include concept bottleneck models, stochastic AI frameworks, and generative models for medical signal denoising. Her work often emphasizes model interpretability, fairness, and robustness to distribution shifts. She collaborates on projects involving wearable devices for pediatric monitoring and AI-driven rehabilitation tools for post-stroke gait analysis.

• Medical Machine Learning
• Data Science
• Artificial Intelligence in Healthcare
• +۳ مورد دیگر

Michael Siegrist is a Full Professor of Consumer Behavior at ETH Zurich's Department of Health Sciences and Technology. His research focuses on risk perception, risk communication, acceptance of new technologies, and decision making under uncertainty, with particular emphasis on food and consumer behavior. He has established himself as a leading researcher in understanding how people perceive risks related to food, chemicals, and emerging technologies. Dr. Siegrist earned his education at the University of Zurich, where he studied psychology, economics, and mass communication. He completed his dissertation in 1994 and his Habilitation in 2001 at the Faculty of Arts. Between 1998-2000, he was a visiting researcher at Western Washington University, funded by the Swiss National Science Foundation. He began teaching and research activities at ETH Zurich in 2004 and became a Full Professor there in 2007. His research interests span risk perception and communication, with particular focus on food safety, disgust sensitivity, naturalness perception, and sustainability. His work examines how consumers evaluate risks related to food technologies, chemicals, and environmental issues. He has published extensively on topics including cultured meat acceptance, food labeling, household chemical safety, and the psychological factors influencing consumer decisions under uncertainty. His research often employs cross-cultural approaches, comparing consumer perceptions across different countries and demographic groups. Dr. Siegrist's publications reveal a strong trend toward understanding the psychological mechanisms behind consumer acceptance of novel food technologies, particularly alternative proteins. His recent work increasingly focuses on sustainability issues in food consumption, examining how consumers perceive environmental impacts of food choices and respond to policy measures aimed at promoting sustainable eating habits. He has made significant contributions to understanding how naturalness claims, disgust sensitivity, and cultural factors shape food preferences and risk perceptions. As an active researcher, Dr. Siegrist collaborates with numerous colleagues across disciplines, including veterinary science, nutrition, and agricultural technology. His work spans both theoretical contributions to risk perception frameworks and practical applications for food industry and policy development.

• Risk perception
• Risk communication
• Acceptance of new technologies
• +۷ مورد دیگر

Christoph Stadtfeld is Associate Professor of Social Networks at ETH Zurich's Department of Humanities, Social and Political Sciences and co-director of the ETH Social Networks Lab. His research examines social network dynamics, focusing on tie formation processes, network effects on individuals, and advanced statistical methodologies for longitudinal network analysis. Education: PhD from Karlsruhe Institute of Technology (2011) Postdoctoral researcher and Marie-Curie fellow at University of Groningen, University of Lugano, and MIT Media Lab (2011-2014) His work bridges sociology, statistics, and computer science to address fundamental questions about how social structures evolve and influence behavior. Key interests include relational event modeling, co-evolution of networks and attributes, and applications in mental health, political polarization, and scientific collaboration. He develops innovative methods for analyzing dynamic networks using cutting-edge computational approaches. Recent publications reveal strong emphasis on methodological rigor in temporal network analysis, with significant contributions to relational event modeling and dynamic network actor frameworks. His work increasingly addresses societal challenges including political polarization, mental health impacts of social isolation, and innovation dynamics in healthcare. Scientific awards: Raymond Boudon Award of the European Academy of Sociology (2017) Freeman Award of the International Network for Social Network Analysis (2021) As co-director of the ETH Social Networks Lab, Stadtfeld leads interdisciplinary research teams developing novel network methodologies. His work has been supported by prestigious fellowships including Marie-Curie funding, and he actively mentors graduate students in network science methodology and applications across diverse domains. The ETH Social Networks Lab serves as a hub for advancing network theory and methodology, with ongoing projects examining student networks during crises, scientific collaboration dynamics, and innovation ecosystems through the lens of network science.

• Social Network Analysis
• Dynamics of Social Networks
• Statistical Methods for Network Data
• +۲ مورد دیگر

Dr. Giulia Celentano is a Senior Scientific Assistant and Humanitarian Research Fellow at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering (D-BAUG), affiliated with the Institute of Construction and Infrastructure Management (IBI). She holds a PhD in Sustainable Construction from ETH Zurich and has academic roles including lecturer in courses at D-BAUG and D-ARCH, as well as visiting professorships at Politecnico di Milano and ETSAM in Madrid. Her research focuses on humanitarian engineering, post-disaster reconstruction, and sustainable construction in conflict-affected and informal urban settings. She leads projects with organizations like the ICRC, UN-HABITAT, and UNHCR, emphasizing field-based, impact-oriented strategies. Education includes a Bachelor's and Master's in Architecture from Politecnico di Milano, a short course in Shelter and Settlements from IFRC/Oxford Brookes, and guest research at MIT ReAct. Current initiatives include coordinating the MOOC on Regenerative Materials (launching 2025) and developing tools like the ETH-ICRC Sustainable Construction Tool. Her work spans case studies in the MENA region, Sub-Saharan Africa, and Southeast Asia, addressing challenges in informal settlements and resilient health infrastructure.

• Humanitarian Engineering
• Post-Disaster and Post-Conflict Reconstruction
• Shelter and Settlements
• +۳ مورد دیگر

Fritz Brugger is a Lecturer at the Department of Humanities, Social and Political Sciences at ETH Zürich and serves as the executive director of NADEL (Network for African-Ethiopian Development Linkages). He holds a PhD in Development Studies from the Graduate Institute of International and Development Studies in Geneva. His research focuses on the developmental impacts of natural resource extraction, extractive industries' corporate roles, and governance challenges in Sub-Saharan Africa. Key areas include health impacts of mining, illicit financial flows, and policy interventions in resource-dependent economies. Prior to joining ETH Zürich, Brugger worked at Helvetas for eight years, later becoming a consultant on governance issues in water management, agriculture, and corporate responsibility. He designed an index-based agricultural insurance system and a mobile-tech platform for smallholder farmers' market access. His work spans diverse regions, with a focus on Burkina Faso, Ghana, and Mozambique. His publications emphasize interdisciplinary approaches, such as Q-methodology for policy engagement, and address topics like mercury use in artisanal mining, corporate due diligence, and the energy transition's impact on social licenses. He contributes to global debates on illicit financial flows, tax evasion, and sustainable development goals implementation through multilateral institutions. Brugger's advisory and grant work includes projects on health impact assessments in mining communities, policy coherence in development aid, and the nexus of extractive industries and conflict. He collaborates with NGOs, governments, and private sector entities to bridge research and policy, particularly in fragile contexts.

• Development Economics
• Natural Resource Extraction
• Public Health Policy
• +۳ مورد دیگر

Gautam Gowrisankaran is a Professor of Economics at Columbia University , with affiliations as a Research Associate at the National Bureau of Economic Research (NBER), a Research Fellow at the Centre for Economic and Policy Research (CEPR), and a Professeur affilié at HEC Montréal. His research spans Health Economics , Industrial Organization , and Environmental Economics . Primary Affiliation : Columbia University, Department of Economics Secondary Affiliations : NBER, CEPR, HEC Montréal His work investigates dynamic market behaviors , including hospital pricing under Medicare reforms, energy transitions in regulated markets, and the impact of policy uncertainty on technology adoption. Recent publications focus on renewable energy integration , insurance market dynamics , and environmental regulation enforcement . Key trends in his research include applied microeconomic modeling , policy evaluation , and strategic interactions in markets with high stakes such as healthcare and energy. His methodological approach often combines structural estimation with empirical data analysis . Notable Grants : Doctoral Dissertation Research in Economics (Effect of Certified Nurse Midwife Scope-of-Practice Laws) Gautam actively contributes to academic discourse through collaborations with institutions like the University of Arizona and University of Chicago . His work addresses critical societal challenges, including healthcare affordability, energy sustainability, and regulatory efficiency.

• Health Economics
• Industrial Organization
• Environmental Economics
• +۲ مورد دیگر

Professor Mirko Trajkovski leads the Laboratory of Metabolic Diseases at the Faculty of Medicine, University of Geneva. He completed his PhD at the International Max Planck School in Dresden (2005), followed by postdoctoral research at ETH Zurich, before establishing his lab at University College London (2012) and moving to Geneva (2013). His work focuses on adipose tissue plasticity , gut microbiota , and their roles in obesity , diabetes , and insulin resistance . Swiss National Science Foundation Professor (2014) ERC Starting Grant (2014) & Consolidator Grant (2019) Dr Walter Seipp Prize & Carl Gustav Carus Prize (2005) His lab investigates fat browning mechanisms , microbiota-host communication , and multi-tissue metabolic regulation using in vivo , in vitro , and human cohort approaches. Recent publications emphasize microbiome-based therapies , temperature effects on metabolism , and gut-bone-adipose crosstalk . Current advisees include PhD student Silas Kieser, with past members like Jing Xue, Salvatore Fabbiano, and Claire Chevalier contributing to immuno-metabolism and microbial engineering projects.

• Metabolic Diseases
• Obesity
• Insulin Resistance
• +۵ مورد دیگر

Louis Du Plessis is a Lecturer at ETH Zürich's Department of Biosystems Science and Engineering in Basel, Switzerland. His research focuses on computational evolution with particular emphasis on infectious disease dynamics and genomic analysis. He maintains an active research profile with numerous high-impact publications in top-tier journals. Dr. Du Plessis completed his doctoral studies at ETH Zürich in 2016 with a thesis titled 'Understanding the spread and adaptation of infectious diseases using genomic sequencing data,' building upon his 2011 Master's work on evolutionary rate variation. His current research sits at the intersection of computational biology, epidemiology, and evolutionary genetics. His research interests span computational epidemiology, phylodynamics, viral evolution, and infectious disease modeling. He has made significant contributions to understanding pandemic dynamics, particularly regarding influenza and SARS-CoV-2, using genomic and epidemiological data integration. His methodological work includes developing computational approaches for estimating epidemic dynamics and viral transmission patterns. Analysis of his recent publications reveals a strong focus on how pandemics disrupt normal viral circulation patterns, with particular attention to influenza evolution during the 2009 H1N1 and COVID-19 pandemics. His work often combines phylogenetic analysis with epidemiological modeling to extract maximum information from genomic and case count data. Dr. Du Plessis has received research funding from European Commission projects including 'From Foundations of Phylodynamics to new applications in Cell Biology' (grant 101001077) and 'MOnitoring Outbreak events for Disease surveillance in a data science context' (grant 874850). He is actively involved in developing computational tools for analyzing pathogen genomic data and has contributed to several software packages used in the field. His work has significant implications for public health surveillance and pandemic preparedness.

• Computational Epidemiology
• Phylodynamics
• Viral Evolution
• +۳ مورد دیگر

Dr. Anton Lavrinienko is a Lecturer at the Department of Health Sciences and Technology at ETH Zürich, affiliated with the Biotechnology of Food Systems group. His research focuses on microbiome studies, environmental health, and the impact of pollution and radiation on ecosystems and microbiota. He is based in Zurich, Switzerland, and teaches the course Applied Bioinformatics: Microbiomes (Autumn Semester 2025). His work integrates molecular biology, ecology, and public health to address challenges in food systems and environmental sustainability. Research interests include microbial diversity in polluted environments, radiation effects on wildlife, and the application of genomics to biodiversity conservation. He collaborates on projects such as the European Reference Genome Atlas and studies microbial responses to anthropogenic contamination in urban and natural ecosystems. Dr. Lavrinienko’s studies often involve fieldwork in regions like Chernobyl, investigating how chronic radiation and metal pollution alter microbiota and organismal health. His findings contribute to understanding ecological resilience and human health implications of environmental stressors. He emphasizes open data standards and FAIR principles in microbiome research.

• Microbiology
• Environmental Health
• Biotechnology
• +۴ مورد دیگر

Shih-Chii Liu holds the rank of Privatdozent (Associate Professor) in the Department of Information Technology and Electrical Engineering at ETH Zürich. He is affiliated with the Institute of Neuroinformatics , a joint institute between the University of Zurich and ETH Zurich. His research focuses on neuromorphic engineering, bio-inspired neural hardware, and edge computing systems, emphasizing energy-efficient algorithms and sensor technologies. Key research areas include neuromorphic sensors for real-time data processing, sparsity-aware neural networks, and adaptive computing architectures for edge devices. His work spans applications such as speech enhancement, wearable health monitoring, and bio-inspired keyword spotting systems. He leads the Sensors Research Group, which develops neuromorphic systems integrating novel sensors, spiking neural networks, and low-power hardware accelerators. Recent projects include the DeltaKWS low-power keyword spotting IC, EFLOP computational cost metrics for spiking networks, and NeuroBench benchmarking frameworks for neuromorphic systems. His contributions emphasize bridging biological neural principles with practical engineering solutions for IoT and embedded systems. Liu teaches courses such as Neuromorphic Engineering I and collaborates on cross-disciplinary projects involving neuroprosthetics, smart wearables, and multimodal sensor fusion. His work is characterized by hardware-software co-design approaches to tackle challenges in real-time, low-latency, and energy-constrained computing environments.

• Neuromorphic Engineering
• Neural Networks
• Edge Computing
• +۳ مورد دیگر