جستجوی استاد راهنمای دانشگاهی

Xiusi Chenمشاهده پروفایل

پژوهشگر ارشد

• Large Language Models
• Natural Language Processing
• AI for Science
• +۵ مورد دیگر

Xiusi Chen is a Postdoctoral Research Fellow in the Blender Lab at the University of Illinois Urbana-Champaign (UIUC), working under Prof. Heng Ji. His research focuses on improving reasoning, alignment, and decision-making capabilities of Large Language Models (LLMs). Previously, he completed his Ph.D. in Computer Science at UCLA under Prof. Wei Wang, and earned M.S. and B.S. degrees in Computer Science from Peking University under Prof. Jun Gao. His educational background includes: Ph.D. in Computer Science, University of California, Los Angeles (UCLA), advised by Prof. Wei Wang M.S. in Computer Science, Peking University, advised by Prof. Jun Gao B.S. in Computer Science, Peking University, advised by Prof. Jun Gao Dr. Chen's research program targets three interconnected areas: advancing Large Language Models (particularly in low-resource reasoning and alignment), developing NLP applications for AI in Science and recommendation systems, and modeling complex decision-making processes in sports domains. His work bridges theoretical foundations with practical implementations, resulting in numerous publications in top-tier conferences including ACL, ICML, ICLR, and KDD. Analysis of his recent publications reveals a strong focus on making LLMs more efficient, reliable, and capable of complex reasoning tasks across diverse domains. His significant academic contributions include: 2023 Best Poster Award (Honorable Mention) at SDM 2023 2023 SIAM Student Travel Award 2021 and 2022 SIGIR Student Travel Grants from ACM SIGIR Multiple academic scholarships from Peking University Co-creation of the widely adopted Amazon Reviews'23 dataset (500k+ HuggingFace downloads) Dr. Chen actively serves the research community as Workshop Organizer for KDD 2025, Program Committee member for major conferences (KDD, WSDM, ICML, NeurIPS, ICLR, AAAI), and journal reviewer. He maintains a strong commitment to mentoring, offering dedicated time for students (especially from underrepresented groups) to discuss research and career development. Starting Fall 2025, he will be seeking academic positions to continue his research on language agents and decision-making systems. Currently based in the Siebel Center for Computer Science, Dr. Chen collaborates with the Blender Lab team on advancing NLP and LLM capabilities. His work has practical impact through widely adopted resources like the Amazon Reviews'23 dataset and theoretical contributions through his publications on reasoning frameworks and alignment techniques.

• Computer Science Education
• Learning Technologies
• Virtual Reality in Education
• +۵ مورد دیگر

Nadine Bergner is a Professor in the Teaching and Research Area of Learning Technologies (Informatik 9) at the Faculty of Computer Science, Dresden University of Technology (TU Dresden). Her work focuses on innovative approaches to computer science education across various educational levels, from primary schools to university settings. She leads research on learning technologies, VR applications in education, and teacher training in computer science. Prof. Bergner's research spans multiple dimensions of computer science education. She has developed and evaluated numerous educational approaches including VR serious games, physical computing with Arduino, and specialized learning environments like the InfoSphere student lab. Her work emphasizes making computer science accessible and engaging for diverse learners, including young children, senior citizens, and pre-service teachers. She has made significant contributions to understanding how students form mental models of computer science concepts and how these can be effectively developed through targeted educational interventions. Her recent publications reveal a strong focus on emerging technologies in education, particularly virtual reality applications for computer science learning. She has been exploring how different interaction modalities in VR affect learning outcomes, presence, and enjoyment. Another major thread in her recent work involves machine learning education, where she has developed concept inventories and game-based learning approaches to make complex ML concepts accessible to learners. She has also been actively researching how to integrate computer science and AI competencies into teacher education across various disciplines. Prof. Bergner has made substantial contributions to the development of educational materials and frameworks for computer science education. Her work includes creating resources for programming education ("Apps programmieren für Dummies Junior"), designing concept inventories for machine learning assessment, and developing comprehensive approaches to building computational thinking skills from early childhood through higher education. She has been instrumental in shaping computer science education policy through initiatives like the Dagstuhl Declaration on education in the digital networked world. Her research often involves collaborative projects with schools and teachers, focusing on practical implementation and evaluation of computer science education approaches. She has been particularly active in developing teacher training programs and materials to support the integration of digital competencies into school curricula. Her work with the InfoSphere student lab has provided valuable insights into how extracurricular learning environments can shape students' perceptions of computer science.

• Game Theory
• Control Theory
• Cybersecurity
• +۵ مورد دیگر

Kim Hammar is a postdoctoral researcher at KTH Royal Institute of Technology, with affiliations at the University of Melbourne (2025-2028) and Imperial College London. He works under Prof. Tansu Alpcan and Prof. Emil Lupu, focusing on the intersection of game theory, control theory, and large-scale systems for networking and security applications. Previously, he completed his Ph.D. at KTH under Prof. Rolf Stadler and Prof. Pontus Johnson. His research spans cybersecurity, networked systems, and adaptive control mechanisms. Key contributions include applying optimal stopping reinforcement learning conjectural online learning causal modeling to intrusion response and network security. His 2025-2024 publications highlight advancements in automated security through game-theoretic and control-theoretic approaches, with a focus on dynamic environments. Kim received the VR International Postdoctoral Fellowship in 2025. He has served as an assistant for Computer Networks (EP111U) Computer Systems (EP121U) at KTH.

• Program Verification
• Proof Engineering
• Formal Methods
• +۴ مورد دیگر

Karl Palmskog is a Lecturer at KTH Royal Institute of Technology in the Division of Theoretical Computer Science and the STEP research group. His work focuses on program verification and proof engineering, with particular emphasis on developing techniques and tools based on proof assistants for constructing functionally correct and secure software systems. Palmskog received his Ph.D. in Computer Science in 2014 from KTH, advised by Mads Dam, and his M.Sc. in Computer Science and Engineering from KTH in 2007. Prior to his current position, he was a postdoc at The University of Texas at Austin and University of Illinois at Urbana-Champaign. His research interests span programming languages, software engineering, and formal verification, with a particular focus on developing techniques and tools based on proof assistants. He is an avid user of the Coq proof assistant for both proving and programming, often complemented by OCaml, and also utilizes HOL4 and other ML family dialects. His work bridges theoretical foundations with practical applications, particularly in the domains of blockchain systems, distributed systems, and automotive software verification. Analysis of his recent publications reveals a strong focus on Coq-based verification, with significant contributions to proof engineering tools and methodologies. His work includes developing tools for regression proving, change impact analysis, mutation testing for Coq projects, and lemma name suggestion using deep learning. There's also a growing trend toward applying formal methods to real-world systems like blockchain protocols and automotive software. Palmskog has been involved in several research projects, including Coq-community Proof Engineering and Distributed Components. His past projects include Trustfull (SSF), Model-based Event Driven Scalable Programming for the Mobile Cloud (NSF), Highly Adaptable and Trustworthy Software (EU FP7), and 4WARD Future Internet (EU FP7). As an educator, Palmskog has served as examiner, course responsible, teacher, and assistant for various courses including Algorithms, Data Structures and Complexity; Degree Projects; Game Theory; Parallel and Distributed Computing; and Programming Paradigms. His work on Chip, a Coq formalization of change impact analysis, demonstrates his commitment to creating practical, certified tools that bridge formal methods with software engineering practice.

Thorsten Hensمشاهده پروفایل

استاد

• Behavioral Finance
• Evolutionary Finance
• Sustainable Finance
• +۵ مورد دیگر

Thorsten Hens is a Swiss Finance Institute Professor of Financial Economics at the University of Zurich and Adjunct Professor at the University of Lucerne and Norwegian School of Economics (NHH). He studied at Bonn and Paris, and previously held academic positions at Bielefeld and Stanford University. His research focuses on Behavioral Finance , Evolutionary Finance , Fintech , and Sustainable Finance . Co-founder of Behavioral Finance Solutions (a UZH-HSG spin-off) and the Swiss Fintech Innovations Association Founder of the UZH Blockchain Center Holds mandates in pension funds, insurance companies, and banks Regular speaker at practitioner conferences His recent publications explore topics such as ESG-CAPM, personality-driven investment styles, evolutionary portfolio dynamics, and experimental retirement decision-making. He has co-authored over ten books and published more than eighty peer-reviewed articles. Thorsten Hens' work bridges academic rigor with practical applications in wealth management , asset management , and financial technology .

Zachary Collierمشاهده پروفایل

استاد مهمان

• Risk Management
• Supply Chain Security
• Systems Engineering
• +۳ مورد دیگر

Zachary Collier is a Visiting Professor at Radford University, where he teaches Operations Management. He holds a Ph.D. in Systems Engineering from the University of Virginia, a Master of Engineering Management from Duke University, and a Bachelor of Science in Mechanical Engineering from Florida State University. His research focuses on Risk Management , Supply Chain Security , and Hardware Security , leveraging interdisciplinary tools from operations research, economics, and systems engineering. Former engineer in accident reconstruction and the US Army Corps of Engineers Fellow of the Center for Risk Management of Engineering Systems at University of Virginia Visiting Scholar at the Center for Hardware and Embedded Systems Security and Trust (CHEST) Recent research explores semiconductor supply chains , zero trust principles , and resilience modeling for hardware systems. He has authored influential publications on topics such as comorbidity data analysis for pandemic response and blockchain risk assessment . Scientific awards include recognition as a Fellow at the University of Virginia and contributions to SAE International standards . Co-authored industry standards for SAE International Publications in NewsWeek, The Hill, and SupplyChainBrain Expertise in decision modeling for emerging risks

• Corporate Management
• Strategic Management
• Organizational Theory
• +۵ مورد دیگر

Anja Tuschke holds the W3 Professorship for Business Administration, especially Corporate Management / Strategic Management, at the Ludwig Maximilian University of Munich within the Faculty of Business Administration . Her work bridges strategic decision-making, organizational dynamics, and corporate governance, with a focus on leadership, boardroom practices, and institutional influences. Teaching: Courses include Strategic Management: Concepts and Cases , Organizational Theory , and Strategy and Leadership . Research: Explores strategic change, corporate misconduct, board networks, executive compensation, and institutional legitimacy. Publications highlight trends in governance, organizational behavior, and strategic adaptation, with recent focus on digital transformation, CEO accountability, and network-driven practices.

• Intelligent Systems and Control
• Cognitive Robotics
• Nano-robotics
• +۹ مورد دیگر

Laxmidhar Behera is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur, specializing in Intelligent Systems and Control. With over two decades of academic experience at IIT Kanpur and international research experience at institutions including Fraunhofer Institute of Autonomous Intelligent Systems in Germany, ETH Zurich, and University of Ulster, he has established himself as a leading researcher in cognitive robotics and intelligent control systems. Dr. Behera's research spans multiple cutting-edge domains including Cognitive Robotics, Nano-robotics, Vision based Control, Soft Computing, Information Retrieval in music and language, Semantic Information Processing, Physics of Complex Systems, Cyber Physical Systems, Formation Control of UAVs, Brain-Computer Interface (BCI), and Sanskrit Computational Linguistics. His interdisciplinary approach bridges traditional control theory with modern computational intelligence techniques, creating innovative solutions for complex real-world problems. His extensive publication record in top-tier journals like IEEE Transactions demonstrates his leadership in areas such as brain-computer interfaces, visual servoing, multi-robot systems, and music information retrieval. Notably, his work on quantum neural networks for EEG filtering and multisatellite formation control has received significant attention in the research community. UKIERI Standard Research Award 2008 Best Paper at International Conf. on Intelligent Sensors and Information Processing (ICISIP-2004) Best Paper at WoSco,02, Int. Conf. High-Performance Computing (HiPC, 2002) AICTE career award for young teacher (1997) Senior Member IEEE Multiple IEEE top accessed articles (2009-2010) As an Associate Editor for Autosoft Journal and Technical Committee Member for Intelligent Control at IEEE Control System Society, Dr. Behera actively contributes to the academic community. His laboratory in the Western Lab - 212A of the Department of Electrical Engineering serves as a hub for research in intelligent systems, where he mentors students and collaborates with researchers worldwide on cutting-edge projects in robotics, control systems, and computational intelligence.

Patricia Martinkovaمشاهده پروفایل

دانشیار

• Psychometrics
• Statistical Modeling
• Educational Measurement
• +۶ مورد دیگر

Patricia Martinkova is an Associate Professor at the Faculty of Education, Charles University , a Senior Researcher leading the Department of Statistical Modelling at the Institute of Computer Science, Czech Academy of Sciences , and an Affiliate Associate Professor at the University of Washington (Statistics and Social Sciences). She is also the founder of the Computational Psychometrics Group and the Center for Educational Measurement and Psychometrics at Charles University. Her research focuses on advanced psychometric models and estimators for granular insights in education, psychology, and health, with emphasis on inter-rater reliability , differential item functioning (DIF) , and reproducible research via tools like ShinyItemAnalysis . She has developed software packages ( difNLR , SIAmodules , SIAtools ) and authored the book Computational Aspects of Psychometric Methods. With R (2023). Recent projects include the 2025–2027 EduCoDe (Czech Science Foundation) and 2024–2028 Digital Technologies and Wellbeing (EU-funded). She has received recognition as a Fulbright Alumna (2013–2015) and organized the IMPS 2024 conference (570+ participants). Teaching includes courses on Statistical Methods in Psychometrics and Item Response Theory , incorporating active learning and R-based tools.

Artem Tsikiridisمشاهده پروفایل

پژوهشگر

• Machine Learning
• Game Theory
• Market Design
• +۲ مورد دیگر

Artem Tsikiridis is a researcher at the Decision Sciences & Systems group within the Department of Computer Science at the Technical University of Munich. His work focuses on Machine Learning , Game Theory , and Market Design , with applications in Social Choice Theory and Optimization . Contact: Room 01.10.0xx, Boltzmannstr. 3, Munich, Germany | Phone: +49 (0) 89 289 - 17xxx | Email: email@in.tum.de Artem contributes to courses such as Algorithmic Game Theory , Computational Social Choice , and Operations Research , reflecting his expertise in computational methods for decision-making and economic systems. His research aligns with the group’s emphasis on interdisciplinary approaches to optimization, learning, and market design.

Vinh Nguyenمشاهده پروفایل

استادیار

• Advanced Manufacturing
• Industry 4.0
• Human-Robot-Machine Interaction
• +۵ مورد دیگر

Vinh Nguyen is an Assistant Professor in the Department of Mechanical and Aerospace Engineering at Michigan Technological University, where he directs the Michigan Tech Center for AI and coordinates the NIST-PREP program. His research focuses on advanced manufacturing through Industry 4.0, human-robot-machine interaction, and physics-based/data-driven modeling. He has developed solutions for machining, additive manufacturing, metal forming, and robotic assembly to promote smart and sustainable manufacturing. Prior to joining Michigan Tech in 2022, he was a National Research Council Postdoctoral Fellow at NIST (2020–2022). Dr. Nguyen earned his PhD (2020), MS in Mechanical Engineering (2017), and MS in Electrical & Computer Engineering (2017) from Georgia Institute of Technology. He received dual bachelor’s degrees in Electrical and Mechanical Engineering from Rensselaer Polytechnic Institute (2014). His research portfolio spans Advanced Manufacturing Industry 4.0 and 5.0 Human-Robot Interaction Physics-Based/Data-Driven Modeling Industrial Automation based on his lab’s interdisciplinary focus on human-centric, resilient solutions. His recent publications address trends in Machine Learning for Manufacturing Autonomous Vehicle Sensors Hybrid Additive/Subtractive Manufacturing Augmented/Mixed Reality Interfaces Industrial Robot Diagnostics Material-Specific Machining with keywords spanning Robotics, Data Science, and Industrial Engineering.

Martin Schmidtمشاهده پروفایل

استاد

• Mathematical Optimization
• Energy Systems
• Mixed-Integer Nonlinear Optimization
• +۳ مورد دیگر

Martin Schmidt is a Full Professor (W3) for Nonlinear Optimization at the Department of Mathematics, Trier University, since 2019. He has held leadership roles in research training groups and international committees, focusing on mathematical modeling and optimization of energy systems, gas networks, and market equilibria. His work bridges mixed-integer nonlinear optimization , bilevel optimization , and robust methods with applications to real-world energy challenges. Education: PhD in Mathematics (2013), Diplom in Mathematics (2008), both from Leibniz University Hannover. Editorial Roles: Editorial Board member of Journal of Optimization Theory and Applications and Optimization Letters , Associate Editor for OR Spectrum and EURO Journal on Computational Optimization . His research integrates complex physical systems (e.g., gas transmission networks) with game-theoretic models to analyze energy markets. Recent publications emphasize robust optimization , decomposition techniques , and machine learning integration in bilevel frameworks. Awards highlight his contributions to gas market feasibility , linear bilevel optimization , and practical applications in energy systems. Collaborations span institutions like Universidad Zaragoza, Sapienza University, and Forschungszentrum Jülich.

Borja Garcia de Sotoمشاهده پروفایل

دانشیار

• Construction Automation
• Cybersecurity in the AEC Industry
• Artificial Intelligence
• +۵ مورد دیگر

Borja Garcia de Soto is an Associate Professor at New York University (NYU) and a Global Network Associate Professor in the Department of Civil and Urban Engineering at NYU's Tandon School of Engineering. He directs the S.M.A.R.T. Construction Research Group at NYU Abu Dhabi, focusing on construction automation, cybersecurity in the AEC industry, artificial intelligence, lean construction, and BIM. His research bridges technological innovation with practical construction challenges, emphasizing digital fabrication and smart infrastructure. He holds a PhD in Civil Engineering from ETH Zurich, an MSc in Engineering and Project Management from UC Berkeley, and dual MSc/BSc degrees in Civil Engineering from Florida International University (FIU), graduating cum laude. Research Interests: Construction automation, cybersecurity threats in AEC, AI applications, lean construction methodologies, BIM integration, digital twins, and robotic systems. Publications: Over 50 peer-reviewed works on topics spanning neural networks for construction scheduling, digital fabrication productivity, cybersecurity risk modeling, and BIM-based optimization tools. Awards: Honorary Fellow of ISTeA (2023), ALEC Innovation Day Partner of the Year (2023), SciRoc Competition Winner (2021), ICE Publishing Award (2016), and ETH Zurich Construction & Infrastructure Prize (2015). Editorial Roles: Associate Editor for Automation in Construction , Journal of Construction Robotics , and Smart and Sustainable Built Environment . Professional: Licensed Professional Engineer (California, Florida) with industry experience in structural engineering and project management.

Jürgen Pfefferمشاهده پروفایل

استاد

• Computational Social Science
• Big Data Analysis
• Social Network Analysis
• +۵ مورد دیگر

Jürgen Pfeffer is a Professor of Computational Social Science & Big Data at the Technical University of Munich's School of Social Sciences and Technology, with an additional appointment as Adjunct Professor at Carnegie Mellon University's Institute for Software Research. His interdisciplinary work bridges computer science and social science with a focus on analyzing large-scale socio-technical systems. His research expertise spans computational social science, network analysis, and big data methodologies. Pfeffer's work examines methodological, algorithmic, and theoretical challenges in analyzing dynamic social systems, with current projects focusing on modeling and detecting negative dynamics from social media, particularly online firestorms and hate speech against politically active women. His research combines network science approaches with computational methods to understand complex social phenomena. Pfeffer's publication record demonstrates significant contributions to the field since his 2010 doctorate, with high-impact papers in journals like Science and EPJ Data Science. His work on social media analysis, particularly the influential 2014 Science paper 'Social Media for Large Studies of Behavior' co-authored with Derek Ruths, has shaped methodological approaches in the field. His research shows consistent evolution from foundational network analysis to contemporary applications in political discourse, hate speech detection, and multi-layer network analysis. Hennig, M., Brandes, U., Pfeffer, J., & Mergel, I. (2012). Studying Social Networks. A Guide to Empirical Research Ruths, D., & Pfeffer, J. (2014). Social Media for Large Studies of Behavior Pfeffer, J., Morstatter, F., & Mayer, K. (2018). Tampering with Twitter's Sample API As an advisor and collaborator, Pfeffer has worked extensively with researchers including Raji Ghawi, Mirco Schönfeld, Momin Malik, and Kathleen Carley. His work demonstrates strong connections between theoretical network science and practical applications in social media analysis. His current research continues to address pressing issues in online discourse, with recent work focusing on hate speech classification, lexical change in negative word-of-mouth, and polarization dynamics in social media environments. Pfeffer leads the Pfeffer Lab, which focuses on developing methodological approaches for analyzing complex social systems through computational methods. His work has implications for understanding political legitimacy, social influence, and community dynamics in both online and offline contexts.

Dongmei Zhaoمشاهده پروفایل

استاد

• Wireless Networking
• Network Resource Management
• Mobile Edge Computing
• +۴ مورد دیگر

Dr. Dongmei Zhao is a Professor in the Department of Electrical & Computer Engineering at McMaster University, part of the Faculty of Engineering. She specializes in wireless networking, network resource management, mobile edge computing, mobile computation offloading, and digital twins. Her research clusters focus on Digital & Smart Systems. Dr. Zhao holds a Ph.D. from the University of Waterloo. She teaches courses such as COMPENG 4DK4 (Computer Communication Networks), COMPENG 4DN4 (Advanced Internet Communications), and graduate-level courses like ECE 729 (Resource Management in Wireless Networks). Her research interests span cutting-edge topics including UAV-enabled edge computing, digital twin migration, vehicular networks, and reinforcement learning applications in resource allocation. She actively contributes to advancing 6G networks, security redundancy in autonomous systems, and decentralized manufacturing platforms. Dr. Zhao's recent publications emphasize optimization techniques for dynamic networks, platooning systems, and multi-agent learning frameworks. She has been recognized for her work in vehicular edge computing and digital twin integration, though explicit awards are not listed here. She advises on graduate studies in networking and edge computing, though no specific student names are provided in the text. Her work often intersects with practical challenges in smart infrastructure and autonomous vehicle systems.