جست‌وجوی استاد و پژوهشگر

Jingyi Wangمشاهده پروفایل

استادیار

• Software Engineering for AI
• Formal Methods
• Security
• +۴ مورد دیگر

Jingyi Wang is an Assistant Professor at Zhejiang University (ZJU), China, leading the IS2 (Intelligent System Security) Lab. He holds a US-equivalent tenure-track position and has established himself as a prominent researcher in software engineering for AI and formal methods applied to security. His educational background includes: Bachelor's degree from Xi'an Jiaotong University (2013) PhD from Singapore University of Technology and Design (2018) Research Fellow at National University of Singapore (2019-2020) Wang's research focuses on developing principled methodologies for building trustworthy AI models and secure systems. His work spans testing, verification and repair of AI models/systems, AI safety and security, and formal reasoning of security. He has developed innovative approaches for neural network testing, verification, and repair, with particular emphasis on explainability, fairness, and robustness. His publication record shows a clear progression from foundational work on concolic testing (2018) to increasingly sophisticated methods for evaluating and improving AI systems, with recent focus on large language models and decentralized identity systems. His research bridges formal methods with practical software engineering challenges in AI security. His notable achievements include: Two ACM SIGSOFT Distinguished Paper Awards (ICSE 2018 and 2020) ACM SIGSOFT Research Highlights Best Paper Award Runner-up at IEEE TDSC 2024 Wang actively contributes to the research community as Program Committee member for top conferences including CCS, ICSE, ISSTA, ASE, WWW, and AAAI. He serves as PC Co-chair for ICFEM 2025, Large Model Safety Workshop 2025, and SAC-SVT 2026. His leadership in the IS2 Lab demonstrates his commitment to advancing intelligent system security through rigorous research.

• High-Performance Computing
• Parallel Computing
• Power Management
• +۳ مورد دیگر

Barry Rountree is a researcher affiliated with Lawrence Livermore National Laboratory (LLNL), specializing in High-Performance Computing (HPC), Power Management, and Parallel Computing. His work focuses on optimizing energy efficiency, fault tolerance, and performance in large-scale supercomputing environments. He has contributed extensively to the development of tools and frameworks for power-aware scheduling, hardware overprovisioning, and visualization performance optimization. Key research interests include HPC system design, processor manufacturing variability, and energy-efficient algorithms. Rountree has collaborated with institutions like NERSC and Intel on projects involving exascale computing challenges and resource management strategies. His publications span conferences such as SC, IPDPS, and ICS, emphasizing practical solutions for scalable and sustainable HPC systems. Notable contributions include the SpackNVD vulnerability audit tool, the msr-genie framework for processor register navigation, and adaptive power management strategies for visualization applications. His work highlights interdisciplinary approaches to addressing computational challenges in science and engineering domains.

• Signal Processing
• Machine Learning
• Acoustic Communication Systems
• +۴ مورد دیگر

Rainer Martin is a Professor of Information Technology and Communication Acoustics at Ruhr-Universität Bochum, where he has been affiliated since 2003. He served as Dean of the Faculty of Electrical Engineering and Information Sciences from 2007 to 2009. He holds a Dipl.-Ing. and Dr.-Ing. from RWTH Aachen University and an M.S.E.E. from Georgia Institute of Technology. His research focuses on signal processing, machine learning, and acoustic systems for voice communication, hearing instruments, and human-machine interfaces. Key areas include speech enhancement, noise reduction, binaural processing, cochlear implant optimization, and acoustic sensor networks. His work integrates deep learning with traditional signal processing for real-world applications. Recent publications emphasize neural networks for noise control, hearing aid algorithms, radar interference mitigation, and auditory perception modeling. Trends show strong convergence of machine learning with acoustic engineering, particularly in low-power embedded systems and healthcare applications. Awards: Fellow of the IEEE He leads projects on acoustic sensor networks, automotive radar, and hearing technology, collaborating with industry partners. His lab develops algorithms for hearing aids, cochlear implants, and robust communication systems, with patents spanning noise reduction, echo control, and speech enhancement.

René Fahrمشاهده پروفایل

استاد

• Corporate Governance
• Business Ethics
• Sustainable Management
• +۵ مورد دیگر

Prof. Dr. René Fahr is a Professor in the Department of Management at Paderborn University's Faculty of Business Administration and Economics, specializing in Corporate Governance and Behavioral Economics. He leads the Chair of Corporate Governance and co-directs the Behavioral Economic Engineering & Responsible Management research area at the Heinz Nixdorf Institute. His work focuses on ethical corporate decision-making, sustainable governance, and human-machine interaction, leveraging experimental methods in the BaER-Lab experimental economics laboratory. Research Interests: - Compliance and Ethical Decision-Making - Sustainable Corporate Governance - Behavioral Ethics - Experimental Economics - Human-Machine Collaboration in Industrial Systems Collaborations include industry partners like Weidmüller, PwC, and dSPACE, as well as academic partnerships such as with Queensland University of Technology. He co-founded the annual Business Ethics Forum to bridge academic and theological perspectives on business ethics. Fahr’s research outputs span over 50 publications in journals like Regional Science and Urban Economics and Customer & Service Systems . Teaching includes foundational and advanced courses on Corporate Governance, emphasizing practical applications through real-world case studies and lab experiments. He oversees student research projects and advises on master's theses in behavioral economics and corporate responsibility. Labs/Teams: Lead of the BaER-Lab and the Behavioral Economic Engineering group at the Heinz Nixdorf Institute.

Oana Gogaمشاهده پروفایل

پژوهشگر

• AI and Society
• Security and Privacy
• Online Advertising
• +۳ مورد دیگر

Oana Goga is a Research Director at Inria, affiliated with the CEDAR team and Laboratoire d'Informatique de l'École Polytechnique (LIX). She holds a Ph.D. from Pierre et Marie Curie University. Her research focuses on AI and Society, addressing risks in online platforms, privacy, disinformation, and child protection. She leads interdisciplinary projects with economists, legal scholars, and social scientists. Awards & Grants: CNRS Bronze Medal (2024) Lovelace-Babbage Award (2023) ERC Starting Grant (2022) Andreas Pfitzmann Best Student Paper Award (2024) Advising & Tools: Guides Ph.D. students and postdocs on projects like CheckMyNews and AdAnalyst . Developed tools for auditing political ads and measuring platform risks. Labs & Collaborations: Active in the Inria CEDAR team and collaborates internationally on EU initiatives like the European Panel for Disinformation Monitoring .

• Artificial Intelligence
• Machine Learning
• Cybersecurity
• +۳ مورد دیگر

Md. Ismail Hossain is an active academic researcher with a focus on Artificial Intelligence , Machine Learning , and Cybersecurity . His work spans both theoretical and applied domains, including Neural Network Pruning , Electric Vehicle Charging Systems , and Security Analysis of emerging technologies. Key Research Themes : Neural network optimization, deepfake detection, and energy systems integration Recent Trends : Articles from 2022-2025 show increasing focus on AI model efficiency and security frameworks

Tobias Guggemosمشاهده پروفایل

استاد

• Controlling in digital business models
• Customer value analyses
• Cost accounting in service companies

Prof. Dr. Tobias Guggemos is a Professor of General Business Administration, specializing in Internal Accounting, at Fulda University of Applied Sciences since 2021. His academic career spans roles as an external lecturer at multiple universities (2016–present) and a research assistant at the Technical University of Dortmund (2010–2014). He earned his doctorate in 2014 with a dissertation on 'Customer Success Calculations as an Instrument of Customer Value Analysis in the Industrial Goods Sector.' Teaching Areas: Management Accounting, Controlling, Business Analytics Academic Affiliation: Fulda University of Applied Sciences; previously associated with Technical University of Dortmund and Steinbeis Network His research focuses on Controlling in digital business models , Customer value analyses , and Cost accounting in service companies . Recent publications highlight the intersection of Controlling and Data Science, digital transformation in corporate governance (e.g., CSRD implementation), and sustainability assessment using decision-theoretic models like the Analytic Hierarchy Process. His work bridges theoretical frameworks with practical applications in industries such as logistics (Deutsche Post DHL) and consulting (KPMG, PwC). Key trends in his publications include: Empirical analysis of data science integration in Controlling Challenges in regulatory compliance (CSRD) and business process adaptation Quantitative methods for sustainability and customer value optimization In his professional career (2014–2021), he held roles such as Head of Finance Master Data at Deutsche Post DHL Group and project manager in the Steinbeis Network, focusing on automated reporting and consulting. His CV reflects strong ties between academic research and industry practice. He can be contacted at tobias.guggemos@w.hs-fulda.de and is based in Room 33, Building 23, Leipziger Straße 123, Fulda, Germany.

• Information Systems in Healthcare
• Digital Transformation in Hospitals
• Human-AI Collaboration

Cornelius Born , M.Sc., is a researcher affiliated with KrcmarLab at the Technical University of Munich (TUM) , specifically within the Department of Information Systems and Business Process Management (Informatik 17). His work sits at the intersection of information systems, healthcare, and human-AI collaboration. Education: M.Sc. in Information Systems – Technical University of Munich Visiting Graduate Student – ETH Zurich, Switzerland Exchange Semester – Tsinghua University, Beijing, China B.Sc. in Information Systems – Duale Hochschule Baden-Württemberg, Mannheim Research Interests: Cornelius focuses on Information Systems in Healthcare , investigating how digital technologies transform clinical workflows. He explores Digital Transformation in Hospitals , from electronic health records to advanced analytics, and studies Human-AI Collaboration , ensuring that AI-driven decision support tools integrate seamlessly and ethically into healthcare settings. Project Involvement: He is actively contributing to the ZNAFlow project, which targets data-driven process optimization in healthcare environments. Industry Experience: Prior to his academic role, Cornelius gained practical experience at Roland Berger and EY , providing strategic IT and process consulting to healthcare and public-sector clients. Contact: cornelius.born@tum.de

• Visual Computing
• Computer Vision
• Image and Video Processing
• +۵ مورد دیگر

Martin Eisemann is Professor of Computer Science and Director at the Computer Graphics Lab within the Computer Science Department of the College of Engineering at Technical University of Braunschweig. Previously, he served as full professor for Computer Graphics at TH Köln (2015-2020) where he co-founded and led the Advanced Media Institute. His academic journey includes a Diploma (2006) from University of Koblenz-Landau and PhD (2011) from TU Braunschweig, followed by post-graduate work at TU Delft. His research spans visual computing with emphasis on computer vision, image/video processing, computer graphics, ray tracing, Monte-Carlo simulations, information visualization, and visual analytics. Recent work demonstrates strong focus on neural rendering techniques including neural point clouds, Gaussian splatting, and holography applications, reflecting evolving trends toward AI-integrated graphics pipelines and immersive visualization systems. His publications consistently address real-time performance challenges while advancing visual quality metrics. VMV'16 Best Paper Award EGSR'16 Best Paper Award ACM Multimedia 2015 Best Student Paper Award Graphics Interface 2015 Best Student Paper Award SAP 2025 Best Student Paper Honorable Mention As Dean of Studies (2023-2027) and former Audit Committee member, he actively shapes academic policy. His community service includes program committee roles for SAP, WACV, and Computational Visual Media conferences. Current research includes a planned sabbatical (April-October 2025) focusing on visual computing challenges. The Computer Graphics Lab maintains active collaborations with DLR, Ford, and European institutions through projects spanning planetary visualization, video conferencing security, and ADHD cognitive support tools.

Tiago Mendes Ferreiraمشاهده پروفایل

پژوهشگر ارشد

• Biophysics
• Molecular Dynamics
• Lipid Membranes
• +۲ مورد دیگر

Dr. Tiago Mendes Ferreira is a Research Fellow at the Institute of Physics within the Faculty of Natural Sciences II at Martin Luther University Halle-Wittenberg. His research focuses on biophysics, molecular dynamics, lipid membranes, and solid-state NMR. He utilizes computational and experimental methods to study complex biological systems, contributing to advancements in medical imaging and material science. Research interests include: Molecular dynamics simulations of lipid membranes Solid-state NMR techniques for biomolecular analysis Computational modeling of membrane proteins Biophysical properties of cellular structures Advanced imaging for medical diagnostics His recent publications emphasize deep learning applications in ophthalmology and biomechanics, reflecting interdisciplinary collaborations. Article trends show strong focus on medical AI, universal design in web interfaces, and sports analytics.

• Privacy-preserving machine learning
• Adversarial robustness
• Differential privacy
• +۵ مورد دیگر

Saeed Mahloujifar is a researcher in the Department of Computer Science at Princeton University's School of Engineering and Applied Science. He has established himself as a prominent researcher in machine learning security, privacy, and robustness, with extensive collaborations with leading researchers including Prateek Mittal, Mohammad Mahmoody, and Somesh Jha. His research primarily focuses on security and privacy challenges in machine learning systems. Mahloujifar has made significant contributions to understanding and mitigating membership inference attacks, developing defenses against poisoning and backdoor attacks, advancing differential privacy techniques, and exploring the fundamental limits of robust machine learning. His work bridges theoretical foundations with practical applications, often developing novel algorithms and frameworks that have been widely adopted in the security and privacy communities. The analysis of his recent publications reveals a strong research trajectory centered on privacy-preserving machine learning, with particular emphasis on large language models, differential privacy guarantees, and security vulnerabilities. His work spans theoretical foundations of privacy through practical security mechanisms like watermarking and robustness benchmarking. A notable trend is his increasing focus on large language models and their security implications, alongside continued contributions to foundational privacy theory. Mahloujifar has co-authored over 90 publications since 2017, with a significant acceleration in output since 2020. His work appears consistently in top-tier venues including NeurIPS, ICML, IEEE S&P, and USENIX Security, demonstrating both breadth and depth in his research contributions.

Urbain Nzotchaمشاهده پروفایل

پژوهشگر

• Power-to-X
• Techno-economic analyses
• CO2 electroreduction value chains
• +۳ مورد دیگر

Dr.-Ing. Urbain Nzotcha is a Postdoc at the Jülich Research Centre , affiliated with the Institute of Energy Technologies (IET) and the Fundamentals of Electrochemistry (IET-1) department. His research focuses on Power-to-X , Techno-economic analyses , and CO2 electroreduction value chains , with an emphasis on sustainable energy systems and industrial carbon management. Dr. Nzotcha’s work explores the intersection of renewable energy systems , CO2 electroreduction , and techno-economic optimization , particularly in Sub-Saharan Africa and European contexts. His recent publications address challenges in Power-to-X scalability , pumped hydropower storage , and adaptive control for photovoltaic systems , reflecting interdisciplinary expertise in energy engineering and environmental economics. His research trends highlight the integration of electrochemical processes with industrial CO2 utilization , hybrid renewable systems , and sustainable development in African regions . Technological innovations and cross-sectoral analyses are central to his contributions.

• Web Services
• Formal Verification
• Software Security
• +۳ مورد دیگر

Xiang Fu is a researcher in the Department of Computer Science at Hofstra University, with affiliations to institutions including Georgia Southwestern State University, University of California, Santa Barbara, and Massachusetts Institute of Technology. His work spans formal verification of web services, software security, zero-knowledge proofs, and automated testing frameworks. His research interests include: Web Services Formal Verification Software Security Zero-Knowledge Proofs Automated Testing Software Engineering Recent publications focus on zero-knowledge auditing for financial systems, formal verification of web services, and secure software analysis. Notable tools developed include APOGEE for automated grading and WISEngineering for scalable online learning. No explicit scientific awards are documented in the provided data.

Jens Frankenreiterمشاهده پروفایل

دانشیار

• Business Law
• Contract Law
• Comparative Law
• +۵ مورد دیگر

Jens Frankenreiter is an Associate Professor of Law at Washington University in St. Louis, specializing in business law, contract law, and empirical methods. His research explores the intersection of law with globalization, technology, and data-driven approaches, focusing on corporate governance, legal institutions, and data privacy. He co-authored a Corporations casebook with Holger Spamann and leads projects like DECODEM, leveraging NLP for legal data extraction. His work bridges law and technology, analyzing topics such as algorithmic auditing, CCPA compliance, and judicial citation patterns. Current research includes The Other Delaware Effect , examining the impact of Delaware’s fee-shifting ban on corporate governance, and Lawma , exploring NLP applications in legal annotation. Frankenreiter emphasizes empirical methods, using computational tools to study legal systems and their evolution. His analyses address pressing issues like gender disparities in startups, privacy law effectiveness, and regulatory competition. Frankenreiter’s interdisciplinary approach spans legal theory and practice, with notable contributions to journals like the Yale Journal on Regulation and Journal of Empirical Legal Studies . He collaborates with institutions globally, advocating for better corporate governance data and legal innovation. His work highlights the transformative role of technology in legal analysis and policy.

• Blockchain Technology
• Cybersecurity
• Cloud Computing
• +۳ مورد دیگر

Wei-Tek Tsai is a Professor affiliated with Arizona State University's School of Computing, Informatics, and Decision Systems Engineering, and previously with Beihang University and the University of Minnesota. His research focuses on blockchain technology, cybersecurity, cloud computing, and software engineering. He has contributed significantly to areas such as blockchain-based systems, smart contract development, distributed testing methodologies, and crowdsourcing in software development. His work emphasizes practical applications like fraud detection, supply chain supervision, and decentralized financial systems. Research interests include permissioned blockchains, anomaly detection in cryptocurrency transactions, and optimizing consensus mechanisms. He has published extensively in top-tier journals and conferences, including IEEE Transactions and international workshops on software engineering and security. His work bridges theoretical advancements with real-world challenges in distributed systems and cybersecurity.