جستجوی استاد راهنمای دانشگاهی

• Finance
• Economics
• Experimental Finance
• +۴ مورد دیگر

Michael Razen is a Researcher at the Department of Economics within the Faculty of Economics at the University of Innsbruck , Austria. His work bridges finance, economics, and behavioral research, with a focus on reproducibility, risk preferences, and tax compliance. His research interests include: Experimental Finance (e.g., choice architecture, monetary incentives) Behavioral Economics (e.g., financial literacy, cognitive biases) Quantitative Finance (e.g., non-standard errors, liquidity studies) Tax Policy (e.g., transparency effects on consumer and firm behavior) Recent publications highlight collaborations with institutions like Stockholm School of Economics , Vrije Universiteit Amsterdam , and Goethe University Frankfurt . His work appears in journals such as the Journal of Finance and European Accounting Review , emphasizing reproducibility, behavioral finance, and policy impacts. Key trends in his publications: 2019–2024 : Focus on data reproducibility , tax transparency , and behavioral finance using multi-analyst studies and experimental economics . Collaborative Networks : Frequent co-authorship with institutions across Europe (e.g., University of Innsbruck , HEC Paris ) and Asia (e.g., Singapore Management University ).

Marc Langheinrichمشاهده پروفایل

استاد

• Privacy
• Security
• Ubiquitous Computing
• +۷ مورد دیگر

Marc Langheinrich is a Full Professor and Dean at the Faculty of Computer Science, Università della Svizzera italiana (USI), where he also leads the Research Group for Ubiquitous Computing. His academic journey includes a PhD from ETH Zurich and prior roles at NEC Research and the University of Washington. He is affiliated with the Institute of Information Systems (SYS) at USI. Education: PhD (Dr. sc.) in Computer Science, ETH Zurich, Switzerland (2005) Master’s degree (Dipl.-Inf.) in Computer Science, University of Bielefeld, Germany (1997) Marc Langheinrich's research centers on privacy, security, and usability in ubiquitous and pervasive computing environments. His work explores how communication protocols, user interfaces, and system designs can protect personal data while enabling seamless interactions with smart devices. Key interests include lifelogging, memory augmentation, IoT privacy, and ethical design frameworks. He investigates technical and human factors in privacy-aware systems, often integrating insights from human-computer interaction and social computing. His recent publications demonstrate a strong focus on privacy-preserving machine learning (e.g., federated learning), mobility modeling, affective computing, and dataset development (e.g., LAUREATE). The research spans theoretical frameworks and practical implementations, often involving wearable sensing, multimodal data, and real-world user studies. Scientific Awards: Best Paper Award at DIS '18 for Roaming Objects: Encoding Digital Histories of Use into Shared Objects and Tools Best Paper Honorable Mention at MUM '16 for Design and evaluation of a wearable AR system for sharing personalized content on ski resort maps Marc Langheinrich has supervised numerous PhD and Master’s students, including Anton Fedosov, Evangelos Niforatos, and Matias Laporte. He has led multiple funded research projects in privacy, IoT, and human-computer interaction. He serves as Editor-in-Chief of IEEE Pervasive Magazine and on the steering committee of the IoT Conference Series, reflecting his leadership in the academic community. He leads the Research Group for Ubiquitous Computing at USI, which focuses on privacy-aware systems, digital memory augmentation, and interactive public displays. The group develops technologies that enhance user control over personal data while enabling novel applications in smart environments.

Gianni Buserمشاهده پروفایل

پژوهشگر

• Quantum Optics
• Quantum Information Science
• Atomic Physics
• +۵ مورد دیگر

Dr. Gianni Buser is a Researcher at the University of Basel's Department of Physics, affiliated with the Quantum Optics Lab under Prof. Philipp Treutlein. He holds a PhD (2021) and Master’s degree (2016) from the University of Basel, specializing in quantum atom optics and atomic vapor-based quantum technologies. His research focuses on developing scalable quantum memories and optical storage systems using atomic vapor cells, with applications in quantum communication and quantum networking. Key contributions include advancements in microfabricated vapor cells, diode laser control techniques, and single-photon storage protocols. Buser’s work bridges quantum optics with optomechanical systems, exploring hybrid atom-light interfaces for next-generation quantum technologies. Teaching includes courses such as Physik IV (Quantum Optics), Physik II, and introductory computational quantum mechanics. His experimental techniques span laser manipulation, hyperfine state engineering, and optomechanical coupling. No scientific awards are explicitly listed for Buser, though his group has received recognition for related work. His research is supported by collaborations in quantum atom optics, optomechanical systems, and semiconductor-atomic interfaces.

Alexandre De Masiمشاهده پروفایل

پژوهشگر

• Mobile Computing
• Quality of Experience (QoE)
• Healthcare Technology
• +۳ مورد دیگر

Alexandre De Masi is a Researcher at the Research Institute for Statistics and Information Science, University of Geneva. He holds a Ph.D. from the Centre Universitaire d'Informatique (University Computer Science Center). His research focuses on mobile computing, quality of experience (QoE), healthcare technology, and social robotics. He has contributed to interdisciplinary projects like the GUARDIAN ecosystem, a social robotics platform for assisted living. His work integrates wearable devices, predictive models, and living lab methodologies to enhance healthcare and user experience. Key areas include smartphone application behavior analysis, usability of social robots in homecare, and longitudinal data collection in human studies. He teaches 'Introduction to Programming' in executive programs. His recent studies explore AI-driven dialogue systems for clinical caregivers and the impact of physical activity on sleep using small data. Publications span conferences like ACM Multimedia Systems and Mobile and Ubiquitous Multimedia (MUM), with a focus on mobile QoE, IoT, and healthcare robotics. His research bridges technical innovation with real-world applications in health and daily life.

Marko MLIKOTAمشاهده پروفایل

استادیار

• Time Series Econometrics
• Empirical Macroeconomics
• Economic Networks
• +۳ مورد دیگر

Marko Mlikota is an Assistant Professor in the Economics Department at the Graduate Institute of International and Development Studies (IHEID) in Geneva. He holds a Ph.D. from the University of Pennsylvania and is affiliated with the Centre for Finance and Development. His research focuses on time series econometrics and empirical macroeconomics, particularly the interplay between economic dynamics and networks (e.g., supply chain linkages, trade/capital flow connections). He teaches core econometrics courses (Econometrics I, II, and Topics in Econometrics) and elective courses like Advanced Quantitative Methods. Thematic expertise includes central banks, monetary policies, and currency dynamics, with geographical focus on Europe and Eastern Europe. He supervises the BCC Programme on capacity building for central banks. His recent work explores structural vector autoregressions (SVARs) with binding constraints, network-based economic dynamics, and dominant currency replacement mechanisms. Articles span computational methods (Monte Carlo techniques) to applied macroeconomic policy analysis.

Frank Kagan Gürkaynakمشاهده پروفایل

پژوهشگر

• Energy-Efficient Microelectronics
• Cryptographic Hardware Security
• Digital Integrated Circuit Design
• +۴ مورد دیگر

Frank Kagan Gürkaynak is Director of the Microelectronics Design Center (DZ) and a Researcher at ETH Zurich's Department of Information Technology and Electrical Engineering (D-ITET). He leads the PULP open-source hardware project and works closely with Prof. Luca Benini in the Integrated Systems Laboratory (IIS). His academic journey includes BSc/MSc from Istanbul Technical University and a PhD from ETH Zurich. Roles: Microelectronics Design Center Director, Senior Scientist in IIS, VLSI course lecturer Research focuses on energy-efficient digital circuits, cryptographic hardware security, and open-source processor architectures. Key projects include EU-funded initiatives like European Processor Initiative (EPI), Convolve, and NeuroSoC, along with SNSF grants Tiny Trainer and PEDESITE. Active in teaching VLSI design, embedded systems, and essential engineering skills. Publications emphasize secure cryptographic accelerators, low-power processor clusters, and GALS system design methodologies. Contributions include energy-efficient ASICs for IoT to HPC domains and pioneering work in side-channel attack-resistant hardware.

• Computational Thinking
• Algorithmic Assessment
• Educational Technology
• +۳ مورد دیگر

Giorgia Adorni is a Researcher with a Ph.D. at the Department of Innovative Technologies (DTI) within the University of Applied Sciences and Arts of Southern Switzerland (SUPSI). She specializes in computational thinking education, algorithmic assessment, and AI-driven educational tools. Her work focuses on developing frameworks for computational thinking problem design, multi-interface learning platforms, and intelligent tutoring systems using Bayesian networks and reinforcement learning. Affiliations: Institute of Information Systems and Networking (ISIN) Her research interests include the intersection of technology and education, particularly in measuring and enhancing algorithmic thinking skills. She contributes to projects like the Virtual CAT platform for gesture-based algorithm assessment and frameworks like FADE-CTP to guide educational activity design. Recent work explores hybrid reinforcement learning approaches to solve complex educational tasks optimally.

Vijay Kumarمشاهده پروفایل

استاد

• Robotics
• Autonomous Systems
• Bio-inspired Algorithms
• +۲ مورد دیگر

Vijay Kumar is the Nemirovsky Family Dean of Penn Engineering with professorial appointments in Mechanical Engineering and Applied Mechanics, Computer and Information Science, and Electrical and Systems Engineering at the University of Pennsylvania. He leads research on autonomous ground/aerial robots and bio-inspired swarm algorithms at the GRASP Laboratory, where he previously served as director (1998–2004). His work spans robotics, cyberphysical systems, and AI applications in disaster response and construction. Education: B.Tech from Indian Institute of Technology Kanpur, Ph.D. from Ohio State University (1987) Research focuses on robot swarms , autonomous navigation , and bio-inspired collective behaviors . Recent publications explore connectivity optimization, semantic SLAM, and stochastic traffic modeling using robot swarms and neural networks. Applications include GPS-denied environments and decentralized edge AI infrastructure. Scientific Awards: IEEE/ASME Fellow, NAE/APS/AAAS member Entrepreneurship: Co-founded Exyn Technologies, advisor to Treeswift, board member of WeRobotics and O2Micro Labs/teams include the GRASP Laboratory and collaborations with industry partners like Rivian and Amazon. Grant activities involve AI for medicine, intelligent assistive robotics, and digital twin infrastructure.

Masatoshi Hamanakaمشاهده پروفایل

پژوهشگر ارشد

• Music Information Technology
• Biomedical Applications
• Unmanned Aircraft Systems

Masatoshi Hamanaka is a Research Fellow at RIKEN 's Center for Advanced Intelligence Project, leading the Music Information Intelligence team. His work bridges interdisciplinary domains including music technology, biomedical applications, and robotics. Ph.D. from University of Tsukuba (2003) Research Interests focus on computational music analysis, with recent work applying transformer models to automate time-span tree analysis from the Generative Theory of Tonal Music. His interests extend to biomedical applications and unmanned aircraft systems, reflecting a multidisciplinary approach to AI and signal processing. Scientific Contributions include breakthroughs in melodic morphing automation and deep learning methodologies for music structure analysis. His 2023 work introduces a total-order priority system for time-span tree branches, enabling automated reductions in musical sequences. Journal of New Music Research Distinguished Paper Award (2005) SIGGRAPH2019 Emerging Technologies Laval Virtual Revolution Research Jury Prize (2019) IJCAI-19 Most Entertaining Video Award (2019)

Thomas Möllenhoffمشاهده پروفایل

پژوهشگر

• Machine Learning
• Bayesian Inference
• Image Processing
• +۳ مورد دیگر

Dr. Thomas Möllenhoff is a post-doctoral researcher at RIKEN AIP's Approximate Bayesian Inference Team. He earned his PhD in Informatics from the Technical University of Munich in 2020, where he focused on nonconvex optimization methods for image processing and computer vision. Education: PhD in Informatics (Technical University of Munich, 2020) His research bridges Bayesian principles with deep learning advancements. Recent work involves Sharpness-aware minimization (SAM) and uncertainty estimation in neural networks. He received recognition for his contributions to computer vision (CVPR 2016) and Bayesian deep learning (NeurIPS 2021 challenge). Scientific Awards: Best Paper Honorable Mention at CVPR 2016 First-place at NeurIPS 2021 Challenge on Approximate Inference in Bayesian Deep Learning

Gianluca Cerutiمشاهده پروفایل

پژوهشگر

• Machine Learning
• Neural Networks
• Computational Efficiency
• +۲ مورد دیگر

Dr. Gianluca Ceruti is a researcher affiliated with the Center for Intelligent Systems (CIS) at École Polytechnique Fédérale de Lausanne (EPFL). His work focuses on computational efficiency in neural networks through dynamical low-rank approximation methods. He has collaborated with institutions including the Karlsruhe Institute of Technology (KIT), Gran Sasso Science Institute (GSSI), and University of Innsbruck. Research Interests: Low-rank optimization for neural networks Reducing computational/memory footprint of AI models Numerical integration techniques for machine learning His 2023 presentation at EPFL CIS-RIKEN AIP series introduced the DLRT algorithm , which adaptively modifies neural network weight matrix ranks during training to preserve accuracy while lowering resource requirements. This aligns with CIS research pillars like AI for medicine and decentralized edge AI infrastructure.

Chao Liمشاهده پروفایل

پژوهشگر

• Tensor Network
• Machine Learning
• Combinatorial Optimization
• +۳ مورد دیگر

Dr. Chao Li is an indefinite-term research scientist at the RIKEN Center for Advanced Intelligence Project (AIP) since 2021, focusing on tensor network learning and its applications in machine learning. His work involves modeling tensor network structure search (TN-SS) as a combinatorial optimization problem, with contributions to algorithms like TNGA and TNLS. He earned his Ph.D. and bachelor’s degrees from Harbin Engineering University in 2017 and 2006, respectively. Dr. Li’s research spans tensor networks, machine learning, and optimization. He has presented at leading conferences like ICML and regularly serves as a senior reviewer for top-tier machine learning venues such as ICML, NeurIPS, and AAAI. The 2022 presentation on TN-SS highlights his work in advancing tensor network methodologies for machine learning tasks, leveraging optimization techniques and exploring applications in neural networks and computational mathematics. Dr. Li is affiliated with the EPFL Center for Intelligent Systems (CIS) through collaborative events with RIKEN AIP, though no specific labs or teams are detailed in the provided text.

• Computer Networks
• Network Architecture
• Distributed Systems
• +۲ مورد دیگر

Catalina Paz Alvarez Inostroza is a Doctoral Assistant and PhD student at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Network Architecture Laboratory (LNAL) in the School of Computer and Communication Sciences (IC). She is actively engaged in both research and academic training within the Doctoral Program in Computer and Communication Sciences (EDIC). Her research focuses on computer networks and network architecture , with additional interests in distributed systems and communication protocols. These areas are central to modern computing infrastructure and align closely with the mission of the Network Architecture Laboratory at EPFL. Although no publications are currently listed, her work is expected to contribute to advancements in scalable, efficient, and robust network designs. As a Doctoral Assistant, she supports both research and teaching activities within her department. She has not received any publicly listed scientific awards at this time. Catalina advises no students currently, and there is no mention of grants or external funding. She is part of the Network Architecture Laboratory (LNAL) , a research group focused on next-generation networking solutions, protocol design, and system performance optimization.

• Computer Systems
• Data Centers
• Distributed Systems
• +۳ مورد دیگر

Konstantinos Prasopoulos is a Doctoral Assistant at the Data Center Systems Laboratory (DCSL) within the School of Computer and Communication Sciences at École Polytechnique Fédérale de Lausanne (EPFL). He is concurrently a doctoral student in the Doctoral Program in Computer and Communication Sciences, specializing under EDIC (Computer Science, Communication Systems, and Information Security). His research is centered on data center systems, with a focus on performance, efficiency, and scalability in large-scale computing environments. These interests align with the mission of the DCSL lab at EPFL, which investigates next-generation data center architectures and infrastructure optimization. No recent publications or scientific awards have been listed in the provided information. As a doctoral candidate, he is likely engaged in independent research under faculty supervision, contributing to ongoing projects within the lab. He does not appear to have advised students at this stage. His work is supported through his appointment as a Doctoral Assistant at EPFL, indicating institutional funding or research assistantship. He is part of the DCSL (Data Center Systems Laboratory), a research group focused on advancing the design and operation of modern data centers, including topics like resource management, networking, and energy efficiency.

Mikhail Terekhovمشاهده پروفایل

دانشگاهی

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

Mikhail Terekhov is a Doctoral Assistant at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Computer and Communication Sciences and the Institute of Electrical Engineering. He is part of the CLAIRE research group under the Lab for AI Research led by Caglar Gulcehre, and is concurrently enrolled in the Doctoral Program in Computer and Communication Sciences (EDIC). His research interests lie in the domain of artificial intelligence and machine learning, with a likely focus on deep learning and natural language processing, given the context of his lab and departmental affiliations. No publications were listed in the provided content, so no trend analysis can be performed on article topics. No scientific awards were mentioned in the text. Mikhail Terekhov is actively serving as a Doctoral Assistant at EPFL. There is no mention of advising students or receiving grants in the provided information. He is associated with the Caglar Gulcehre Lab for AI Research at EPFL, which focuses on cutting-edge research in artificial intelligence and deep learning methodologies.