جست‌وجوی استاد و پژوهشگر

Markus Püschelمشاهده پروفایل

استاد

• Program Generation
• Fourier Analysis
• Signal Processing
• +۶ مورد دیگر

Markus Püschel is a Professor of Computer Science at ETH Zurich, leading the Advanced Computing Laboratory. He previously served as Head of the Department of Computer Science at ETH from 2013 to 2016. Before joining ETH in 2010, he was a Professor at Carnegie Mellon University (CMU) and retains adjunct status there. He holds a PhD in Computer Science (1998) and a Mathematics Diploma (1995) from the University of Karlsruhe. His research focuses on program generation for performance, Fourier analysis, signal processing, machine learning, and compiler optimization. He pioneered the SPIRAL system for generating optimized signal processing libraries and has contributed to algebraic signal processing theory. His work bridges mathematical foundations with practical high-performance computing, emphasizing automated code generation and domain-specific languages. Research trends in his articles include causal inference on directed acyclic graphs, quantized neural network inference, and efficient compiler techniques. His work on graph signal processing and causal analysis has led to novel methods in time-series data and DAG learning. Awards: IEEE Fellow (2020), Golden Owl Teaching Award (2015), NSF Discovery Grant (2008), and multiple best paper awards. Grants/Projects: Co-PI for Making Program Analysis Fast (SNF), SPIRAL GPU projects, and collaborations with industry partners like Intel and AMD. He advises over 40 PhD and master’s students, many of whom contribute to impactful projects in compilers, machine learning, and signal processing. His lab also co-founded the Swiss Data Science Center.

• Formal Verification
• Model Checking
• SAT/SMT Methods
• +۴ مورد دیگر

Natasha Sharygina is a Full Professor of Informatics at the University of Lugano (USI) in Switzerland. She leads the USI Formal Verification and Security group, focusing on improving software and hardware verification through formal methods like model checking and SAT/SMT techniques. Her research emphasizes applying these methods to computer security, electronic design, and program analysis. Education: PhD in Informatics from The University of Texas at Austin (2002). Research Interests: Her work spans formal verification, model checking, SMT-based solvers, and security analysis. She develops theoretical frameworks and practical tools for verifying large-scale systems, with applications in safety-critical and distributed computing environments. Funding & Awards: Her research has been supported by grants from the Swiss National Science Foundation, EU STReP/COST projects, Hasler Foundation, and TASSO Career Award. She has been recognized with the ACM Recognition of Service Award and CMU Technical Excellence Awards. Grants & Projects: Key initiatives include 'Beyond Symbolic Model Checking through Deep Modelling' (2019–2023), EU-funded 'Rich-Model Toolkit', and Swiss TASSO Career Award (2005–2010). She has led efforts in parallel SMT solving and runtime verification. Labs & Teams: Director of the USI Formal Verification and Security Lab, which develops tools like Golem (CHC solver) and OpenSMT (SMT solver). Collaborates globally on projects like SAFARI and FunFrog for program verification.

Jeanine Reutemannمشاهده پروفایل

مدرس

• Science Communication
• Educational Media
• Digital Education
• +۳ مورد دیگر

Dr. Jeanine Reutemann serves as a Lecturer at the Department of Environmental Systems Science, ETH Zurich, where she leads the Media & Methods Lab within the Unit for Teaching and Learning (UTL). Her role encompasses producing co-designed audiovisual media for ETH lecturers, advancing digital media competencies across the institution, and exploring innovative media technologies for future teaching through flagship projects. Her research centers on the science-society interface , specializing in translating complex scientific concepts through audiovisual media. Key interests include the epistemological potential of visual language in education, sustainable production of science videos, mixed reality applications, and combating misinformation. She investigates how media design shapes public understanding of science and enhances learning experiences in higher education, with particular focus on deepfakes, truth verification, and co-design methodologies. Analysis of her publication trajectory (2016-2024) reveals an evolution from foundational studies on MOOC video styles to current work on sustainable educational media and mixed reality. Her research consistently bridges theory and practice, emphasizing ethical considerations, societal impact, and the transformative role of audiovisual media in science communication. Recent publications highlight growing attention to environmental sustainability in media production and AI's implications for scientific content generation. Dr. Reutemann actively contributes to interdisciplinary projects funded by the Swiss National Science Foundation (SNF), including the r4d programme. She has collaborated with Oxford University, WSL, WWF/COOP, and others to produce science documentaries addressing global challenges such as inequality, sustainability, and peacebuilding, including the full-length documentary 'Inequality and Conflict - Beyond us and Them'. She heads the Media & Methods Lab, a dynamic team that partners with ETH lecturers to co-create educational media, designs continuous professional development programs in digital media competencies, and pioneers new media technologies through projects like the Science Filmmaking Hackathon (producing AI-themed animations) and mixed reality character prototypes for campus navigation. Current initiatives include developing audiovisual essays with the gta archive and science communication videos leveraging internet meme culture for environmental science students.

Jessica Goldbergمشاهده پروفایل

دانشیار

• Development Economics
• Rural Labor Markets
• Financial Inclusion
• +۴ مورد دیگر

Dr. Jessica Goldberg is an Associate Professor of Economics at the University of Maryland, College Park. She directs the Promoting Achievement and Diversity in Economics (PADE) program and is actively engaged in development economics research. Her work focuses on rural labor markets, financial inclusion, and the influence of social networks on economic decisions. She collaborates with institutions such as the Abdul Latif Jameel Poverty Action Lab (JPAL), the Bureau for Research and Economic Analysis of Development (BREAD), and the National Bureau of Economic Research (NBER). Dr. Goldberg serves as Co-Editor for the Journal of Human Resources and Associate Editor for the Review of Economics and Statistics and Journal of Development Economics . Her research spans field experiments on credit and savings in Uganda and Zambia, women's mobile money participation in Bangladesh, and social networks in disease outreach in India. Recent experiments include digital agricultural extension services in India (2025) and gender-transformative approaches to entrepreneurship. Scientific Awards & Affiliations: National Bureau of Economic Research (NBER) Faculty Research Fellow Abdul Latif Jameel Poverty Action Lab (JPAL) Faculty Affiliate Bureau for Research and Economic Analysis of Development (BREAD) Faculty Affiliate Co-Editor, Journal of Human Resources Associate Editor, Review of Economics and Statistics Associate Editor, Journal of Development Economics Dr. Goldberg has conducted numerous field experiments on financial inclusion, TB screening, agricultural savings, and social network dynamics. Her work emphasizes randomized controlled trials (RCTs) and policy implications for poverty alleviation. She teaches courses like Econ 416 (Theory of Economic Development) and Econ 417 (Estimating Policy and Program Impact).

• Law and Economics
• Comparative Property Law
• Empirical Legal Studies
• +۳ مورد دیگر

Yun-chien Chang is the Jack G. Clarke Professor in East Asian Law at Cornell Law School , where he also serves as Director of the Clarke Program in East Asian Law & Culture. His work bridges law and economics , comparative property law , and empirical legal studies , with a focus on property theory, corporate governance, and judicial behavior. Research Themes : Property law efficiency and convergence/divergence between civil and common law systems Economic analysis of eminent domain, adverse possession, and takings compensation Empirical studies of judicial decision-making, settlement patterns, and legal aid participation Machine learning applications in comparative legal analysis Publication Trends : Recent work (2021-2025) emphasizes legal origins theory , judicial ideology , and behavioral economics in law Foundational papers (2010-2016) explore property customs , constitutional mechanisms , and economic modeling of legal institutions

Ayan Chakrabortyمشاهده پروفایل

پژوهشگر ارشد

• High-Performance Computing
• Hardware-Software Co-design
• Electronic Design Automation
• +۵ مورد دیگر

Ayan Chakraborty is a Research Fellow at the École Polytechnique Fédérale de Lausanne (EPFL) , affiliated with the School of Computer and Communication Sciences and the Department of Computer Science . He works at the Parallel Systems Architecture Laboratory (PARSA) and is part of the doctoral program in computer and communication sciences. Bachelor of Technology in Electronics & Electrical Communications Engineering (E&ECE) from IIT Kharagpur, 2022 Minor in Computer Science & Engineering (CSE) at IIT Kharagpur Ayan’s research focuses on building high-performance scalable computing systems for future server workloads using a hardware-software co-design approach. His prior work includes developing Electronic Design Automation (EDA) tools for analog circuit verification and exploring High-Level Synthesis (HLS) for accelerators via functional programming. He also has industrial experience in formal verification at NVIDIA. He serves as President of the EPFL PhDs of I&C (EPIC) association and is based at EPFL’s INJ 215 office.

• Data Science
• Big Data
• Natural Language Query Processing
• +۴ مورد دیگر

Prof. Dr. Kurt Stockinger is a Professor of Computer Science at ZHAW School of Engineering and holds a doctorate at the University of Zurich . He serves as Head of the MAS Data Science program and co-leads the ZHAW Datalab . His research focuses on Intelligent Information Systems , bridging information systems, natural language processing, and machine learning. Affiliated with the University of Zurich, he contributes to Quantum Machine Learning and Open Data Exploration initiatives. Stockinger's educational background includes a PhD in Computer Science (University of Vienna & CERN), a Master in Business Informatics (University of Vienna), and a CAS in Didactics & Methodology (ZHAW). He has taught courses in Quantum Computing , Big Data for Natural Sciences , and Data Science programs at ZHAW and University of Zurich. His research spans Data Science , Big Data , Natural Language Query Processing , Knowledge Graphs , and Quantum Machine Learning . Recent publications focus on quantum autoencoders , hybrid quantum neural networks , and prompt engineering for knowledge graph question answering. He has developed frameworks like ScienceBenchmark for real-world NL-to-SQL evaluation and NQuest for natural language query exploration. Scientific awards include the Best Paper Award at 7th Swiss Conference on Data Science (2020) He leads major projects such as DataGEMS (Data Discovery Platform, Horizon Europe) Digital Health Zurich (Clinical Innovation Lab) INODE4StatBot.swiss (NL-to-SQL Translation) GraphQueryML (Graph Database Optimization) ScienceBenchmark (NL-to-SQL Evaluation) Stockinger's work intersects with computer vision , biomedical data , and industrial applications , demonstrated through collaborations with institutions like Lawrence Berkeley National Laboratory, CERN, and University of Washington. He has contributed to establishing QuantumBasel and ZHAW Datalab as research hubs.