جست‌وجوی استاد و پژوهشگر

Attila Hidegمشاهده پروفایل

مدرس ارشد

• Robotics
• Multi-robot Systems
• Distributed Algorithms
• +۳ مورد دیگر

Attila Hideg is a Senior Lecturer at the Department of Automation and Applied Informatics, Budapest University of Technology and Economics (College of Engineering). His research focuses on multi-robot systems, distributed algorithms, and sensor networks. Contact E-mail: Hideg.Attila@aut.bme.hu Office: Q.B229, Magyar Tudósok krt. 2, Budapest 1117, Hungary Phone: +36 (1) 463-4225 Research Highlights Hideg's work centers around optimizing coordination in multi-robot systems, including asynchronous algorithms for robot swarms, uniform dispersal of low-cost flying robots, and sensor fusion techniques for indoor mapping. He has developed simulation frameworks like RobotCore and explored energy-efficient navigation in obstacle-rich environments. Recent Publications (2024-2016) Indoor Mapping with ICP Algorithms (2024) Multi-robot Simulation Frameworks (2022, 2018) Swarm coordination and dispersal algorithms (2022, 2021, 2019, 2017, 2016) Distributed sensor data collection (2016) Optimization of timetabling genetic operators (2015)

Etienne Vougaمشاهده پروفایل

دانشیار

• Physical simulation
• Geometry processing
• Discrete differential geometry
• +۴ مورد دیگر

Etienne Vouga is an Associate Professor in the Department of Computer Science and the Institute for Computational Engineering and Sciences (ICES) at the University of Texas at Austin. His interdisciplinary research spans physical simulation, geometry processing, and computer graphics, with applications ranging from special effects in films like The Hobbit and Tangled to Artec's Shapify 3D portrait service. Education: PhD from Columbia Computer Graphics Group Postdoctoral research at Harvard SEAS Professor Vouga's research focuses on physical simulation of thin, elastic materials like cloth, hair, and paper, as they deform and collide. He has made significant contributions to discrete differential geometry, developing algorithms that better understand how geometric properties affect physical behavior of deformable objects. His work bridges computer graphics, computational mechanics, and scientific computing, with applications in special effects, 3D printing, architectural design, and biological modeling. He has pioneered approaches in inverse problems where desired outcomes drive the design process rather than simply simulating physical phenomena. Award Highlights: Best Paper Award at GECCO (2017) for Evolutionary Decomposition for 3D Printing Professor Vouga teaches Computer Graphics: Honors (CS 378H/CS 384G) and Physical Simulation (CS 395T) graduate courses every spring semester. He also serves as head coach of UT's competitive programming teams. His research group has developed several important software tools including Discrete Shell Code for shell simulation and Asynchronous Contact Mechanics Code for robust collision handling. While he is not actively expanding his research group significantly, he remains open to working with exceptional graduate students whose research interests align closely with his work in physical simulation and geometry processing.

Leyte Winfieldمشاهده پروفایل

استاد

• Medicinal Chemistry
• Organic Chemistry
• Chemical Education
• +۳ مورد دیگر

Leyte Winfield serves as Division Chair for the Natural Sciences and Mathematics and Professor of Chemistry and Biochemistry at Spelman College, where she also directs the Cosmetic Science Program and co-directs the Center of Excellence for Minority Women in STEM. Her leadership spans academic administration, research innovation, and national STEM diversity initiatives. Educational background includes: Post-Graduate Certificate in Academic Leadership, The Chicago School (2014) Post-Doctoral Fellowship in Medicinal Chemistry, Florida A&M University (2004) PhD in Organic Chemistry, University of New Orleans (2003) BS in Chemistry, Dillard University (1997) Dr. Winfield's research integrates synthetic organic chemistry with transformative educational practices. Her medicinal chemistry work focuses on anti-proliferative compounds targeting cancer pathways, while her chemical education scholarship pioneers culturally responsive pedagogy and systemic interventions for underrepresented groups. Recent publications reveal a strategic shift toward diversity, equity, and inclusion frameworks in chemistry education, examining social presence in digital learning, identity-affirming laboratory experiences, and community-based capacity building at minority-serving institutions. Her work consistently centers Black women's experiences in STEM through initiatives like the Black Beauty STEMinist Project. Major scientific recognitions include: Cottrell Scholar designation American Association for Cancer Research recognition Council for Undergraduate Research recognition As principal investigator, she has secured significant funding from the National Science Foundation (HRD-1332575, 1912385, 1626002, 2315607) and National Institutes of Health (P20MD008719-01) to develop blended learning models, peer mentorship systems, and cohort-building strategies that increase retention in STEM majors. Her advising philosophy emphasizes learner agency development through self-regulated learning frameworks. Dr. Winfield leads the Black Beauty STEMinist Project in partnership with L'Oréal, Estée Lauder, and PATTERN Beauty, creating digital archives that document Black women's contributions to cosmetic science while developing pipeline programs for future industry leaders.

• Distributed Computing
• Network Algorithms
• Programmable Matter
• +۳ مورد دیگر

Professor Andrea Richa is a President's Professor at Arizona State University (ASU) since 2022, with a dual appointment as Professor of Computer Science and Engineering in the School for Computing and Augmented Intelligence (SCAI). She serves as Honors Faculty at Barrett, the Honors College, and holds Associate Faculty positions at the Biodesign Center for Biocomputing, Security and Society, Global Security Initiative, and Biomimicry Center at ASU. Education PhD in Computer Science from Carnegie Mellon University (1998) MS in Computer Science from Carnegie Mellon University (1995) BS in Computer Science from Federal University of Rio de Janeiro, Brazil (1989) Her research focuses on distributed and network algorithms, particularly programmable matter through self-organizing particle systems (SOPS). Key areas include bio-inspired distributed algorithms, wireless network modeling, self-stabilizing overlay networks, and approximation algorithms. She leads the Self-organizing Particle Systems Lab ( sops.engineering.asu.edu ). Recent publications highlight her work in programmable matter (2025), anonymous network synchronization (2025), and energy-constrained systems (2023), demonstrating interdisciplinary applications in robotics, environmental monitoring, and biological systems. Scientific Awards NSF CAREER Award (2000-2006) 2017 SCAI Best Senior Researcher Award 2024 Fulton Undergraduate Research Mentor Award 2021 Faculty Women Association Mentor Award She has received major grants including a DoD MURI (2019-2025) and multiple NSF awards for research on self-organizing particle systems, wireless communication models, and distributed algorithms. She has delivered 59+ invited/keynote presentations globally since 1997.

• Information Systems
• Digital Innovation
• Knowledge Management
• +۳ مورد دیگر

Poulymenakou Angeliki is a Professor at the Department of Management Science and Technology (DMT) within the School of Business Administration at Athens University of Economics and Business (AUEB). Her elective courses focus on Business Process Management and Digital Platforms, Networks and Innovation . She holds a degree in Mathematics from the University of Athens, an M.Sc., and Ph.D. in Information Systems from the London School of Economics and Political Science. Degree in Mathematics, University of Athens M.Sc. in Information Systems, London School of Economics Ph.D. in Information Systems, London School of Economics Her research spans multiple domains, including digital learning environments, information systems in globalization contexts, e-voting trust dynamics, and socio-technical structures in virtual worlds. She has extensively studied e-learning adoption, usability frameworks, and privacy-oriented requirements engineering. Recent publications examine sense of presence in digital education , trust in e-voting systems , and design guidelines for asynchronous e-learning . Her work integrates organizational theory with technology studies, focusing on collaboration mechanisms, knowledge management, and ICT policy. She has contributed to understanding technology adaptation in project teams, critical success factors for e-learning, and the role of information systems in inter-firm networks. Her research methodology combines qualitative and quantitative approaches, often employing stakeholder analysis and practice-based perspectives. Key collaborations include work with S. Klein and M. Lytras, and her research has been published in conferences like IFIP and journals related to organizational information systems. Current projects likely continue her focus on digital transformation in education and business contexts.

• Machine Learning
• Game Theory
• Eco-ML
• +۴ مورد دیگر

Vianney Perchet is a Professor at CREST (Centre de recherche en économie et statistique) , affiliated with ENSAE since October 2019. His research bridges Machine Learning , Game Theory , and Economics , focusing on theoretical and applied problems in algorithm convergence, recommender systems, and multi-agent decision-making. He also holds a part-time principal researcher role at the Criteo AI Lab in Paris. His research interests span pure and applied domains, including Reinforcement Learning , Social Learning , Online Matching , Bandit Algorithms , and Auction Theory . He actively advises 5 PhD students and has mentored 4 who have successfully defended their theses. Recent publications highlight his work on Learning-Augmented Algorithms , Regret Minimization , and Fair Resource Allocation , appearing at top conferences like NeurIPS , ICML , and AISTATS . His projects often integrate game theory , online learning , and optimization frameworks.

Eve Kerrمشاهده پروفایل

استاد

• Quality Measurement
• Healthcare Value
• Clinical Translational Research
• +۳ مورد دیگر

Eve Kerr is the Kutsche Memorial Chair of Internal Medicine and Professor at the University of Michigan Medical School. She serves as Section Head for the Division of General Medicine and a Senior Research Scientist at the VA Ann Arbor Center for Clinical Management Research (CCMR). Dr. Kerr is also the Founding Director of the Michigan Program on Value Enhancement (MPrOVE). Active faculty member with significant leadership and research roles Email: ekerr@umich.edu Her research focuses on improving healthcare quality and value through: Development of clinical action measures for blood pressure treatment Assessment of low-value care and its reduction Healthcare workforce wellbeing and equity Implementation of evidence-based practices in VA systems Health services research methodology Recent publications highlight her work in behavioral economics interventions, colorectal cancer screening optimization, hypertension management in kidney disease, and equity-focused healthcare redesign. Dr. Kerr's research spans diverse clinical domains including diabetes, surgery, and chronic disease management. Scientific recognition includes: Election to the National Academy of Medicine Master of the American College of Physicians VA Undersecretary for Health Award for Excellence in Health Services Research Society of General Internal Medicine Eisenberg National Award Dr. Kerr mentors through direct advising and leads large-scale implementation projects across healthcare systems.

• Fault-Tolerant Distributed Computing
• Parallel Computing
• Algorithms and Complexity
• +۳ مورد دیگر

Chryssis Georgiou is a Professor and Chair of the Department of Computer Science at the University of Cyprus , where he leads the Research Laboratory for Foundations of Computing Systems and Theoretical Computer Science . He holds a Ph.D. and M.Sc. in Computer Science from the University of Connecticut and a B.Sc. in Mathematics from the University of Cyprus. Ph.D. in Computer Science (2003), University of Connecticut M.Sc. in Computer Science (2002), University of Connecticut B.Sc. in Mathematics (1998), University of Cyprus His research focuses on the Theory and Practice of Fault-Tolerant Distributed and Parallel Computing , with emphasis on algorithms, complexity, and blockchain systems. He has published over 115 refereed articles and co-authored two books on distributed computing. Recent work includes Byzantine-tolerant consensus, dynamic storage for large objects, and blockchain resilience frameworks. His 15 most recent publications span topics in Byzantine Fault Tolerance , Atomic Shared Memory , WSN Optimization , and Distributed Ledger Formalization , with applications in IoT networks, cryptocurrency systems, and GPU-inspired shared memory models. Advising and Projects include coordination of the MA(R)S project (Cyprus Research Foundation), e4Pain (machine learning for pain coping), ESS-BFT (self-stabilizing blockchain infrastructure), and participation in the CoronaSurveys system for pandemic data collection. He has served as project coordinator for the ONISILIOS-funded ESS-BFT and as academic supervisor for industry-linked PhD programs. Labs and Teams include the Research Laboratory for Foundations of Computing Systems at the University of Cyprus, with collaborations across Europe and North America. He chairs the 2026 SIROCCO conference and contributes to editorial boards and program committees for top-tier distributed computing venues.

• Integrated Sensing and Communication
• Wireless Communications
• Signal Processing
• +۶ مورد دیگر

Dr. Fan Jiang serves as an Associate Senior Lecturer at Halmstad University's School of Information Technology, where he leads research at the intersection of wireless communications and localization technologies. His academic profile reflects strong technical expertise in next-generation wireless systems with practical applications in vehicular networks and satellite communications. His research program focuses on integrated sensing and communication (ISAC) frameworks, with particular emphasis on: Massive MIMO and millimeter wave system design Wireless localization/synchronization algorithms Integration of sensing functionalities within communication protocols Applications for vehicular positioning and satellite networks Analysis of his 15 publications from 2022-2024 reveals consistent output in high-impact venues, with growing emphasis on satellite communications and reconfigurable intelligent surfaces. His work demonstrates strong mathematical rigor in channel modeling and algorithm design while addressing practical implementation challenges like synchronization errors and hardware constraints. Dr. Jiang maintains active research collaboration through co-authorship networks and participates in experimental validation efforts, as evidenced by his 2022 field study on 5G mmWave positioning. His technical approach balances theoretical innovation with real-world applicability across multiple wireless domains.

Victor Preciadoمشاهده پروفایل

دانشیار

• Network Science
• Dynamical Systems
• Data Science
• +۳ مورد دیگر

Victor Preciado is an Associate Professor at the University of Pennsylvania, holding appointments in the Departments of Electrical & Systems Engineering and Computer & Information Science . He is affiliated with the Warren Center for Network & Data Sciences , the PRECISE Center , and the Applied Math and Computational Science graduate group . His research bridges Network Science , Dynamical Systems , and Data Science , focusing on modeling, analysis, and control of complex networked systems. Ph.D. in Electrical Engineering and Computer Science from MIT (supervised by Prof. George Verghese) Visiting scholar at UC Berkeley, Santa Fe Institute, and Courant Institute (NYU) Postdoctoral researcher at GRASP Lab (working with Prof. Ali Jadbabaie) His research interests include epidemic modeling and control , socio-technical networks , network controllability , and data-driven optimization . Recent work explores contact-aware robotics and operator learning using attention mechanisms. His publications from 2022–2024 highlight advancements in robust control , epidemic tracking , and hypergraph neural networks , with applications in pandemic management , robotics , and temporal network analysis . Scientific awards include: 2024: IEEE Robotics and Automation Society Best Paper Award finalist (for Stabilization of Complementarity Systems ) 2022: IEEE Control Systems Magazine Best Paper Award (retrospectively for Analysis and Control of Epidemics ) 2017: National Science Foundation CAREER Award 2019: IEEE Transactions on Network Science and Engineering Best Paper Award runner-up He has served as Associate Editor for IEEE Transactions on Network Science and Engineering and IEEE Transactions on Control of Networked Systems , and as Guest Editor for special issues on pandemics and control of epidemics in journals like Annual Reviews in Control and SIAM Journal on Control and Optimization .

Yan Huangمشاهده پروفایل

پژوهشگر

• Distributed Optimization
• Federated Optimization
• Large-Scale Machine Learning
• +۵ مورد دیگر

Yan Huang (黄炎) is a postdoctoral researcher at KTH Royal Institute of Technology, affiliated with the Division of Decision and Control Systems. He earned his Ph.D. in Control Science and Control Engineering from Zhejiang University (2020-2024) under Prof. Jinming Xu and Prof. Jiming Chen, with prior degrees from Southeast University and Anhui University. His work focuses on distributed optimization and machine learning. Ph.D. in Control Science and Control Engineering, Zhejiang University, 2020-2024 M.S. in Control Science and Control Engineering, Southeast University, 2017-2020 B.S. in Automation, Anhui University, 2013-2017 Yan Huang specializes in distributed and federated optimization theory , applying these techniques to large-scale machine learning and networked control systems . His research addresses data heterogeneity, robustness to failures, and computational efficiency in decentralized networks. He has developed flexible frameworks for gradient tracking and personalized optimization. His recent publications emphasize stochastic gradient tracking , variance reduction , and differential privacy in distributed settings. Key topics include adaptive stepsizes , Byzantine-robust algorithms , and computation-communication trade-offs , reflecting his focus on scalable and secure optimization methods. Outstanding Graduate, Zhejiang University, 2024 Outstanding Doctoral Student, Zhejiang University, 2022 and 2023 2nd prize in China Post-graduate Mathematical Contest in Modeling, 2017 Outstanding Graduate, Anhui University, 2017 Huang has taught courses on Principles of Automatic Control , Modern Control Theory , and Distributed Control and Optimization . He has also presented at ICML 2022 and Zhejiang University's academic forum, highlighting his work on decentralized SGD and data heterogeneity.

• Computer Vision
• Signal Processing
• Machine Learning
• +۴ مورد دیگر

Vedran Jovanović serves as a Senior Lecturer at the Department of General Electrical Engineering, Faculty of Electrical Engineering, University of Banja Luka. His academic career centers on interdisciplinary research bridging computer vision, signal processing, and biohybrid engineering systems with practical applications in security, environmental monitoring, and industrial automation. His primary research domains include Computer Vision, Signal Processing, Machine Learning, Biohybrid Systems, Robotics, Sensor Networks, and Land Use Classification. Jovanović has pioneered video analysis techniques for honeybee activity monitoring in explosive detection systems and developed novel algorithms for small object detection in UAV surveillance footage. His work in offshore aquaculture monitoring addresses splash and cage detection challenges through deep learning approaches. Analysis of his recent publications reveals a pronounced focus on applying machine learning to humanitarian and industrial challenges, particularly in biohybrid landmine detection systems and precision robotics calibration. His most impactful work appears in journals such as Sensors, Science of the Total Environment, and Remote Sensing, demonstrating consistent methodological innovation across computer vision and signal processing domains. Dr. Jovanović actively participates in multiple research initiatives including the NATO-funded "Biological Methods (Bees) for Explosive Detection" project (2017-2021, 300,415 BAM) and current national projects such as "Signal Processing using Embedded Computer Systems and Machine Learning" (2025, 9000 BAM) and "Development of STEM Skills and Interests in School Children" (2025, 3000 BAM), where he contributes expertise in machine learning and computer vision systems development. He collaborates extensively within the University of Banja Luka's research ecosystem, particularly with the Signal Processing and Bioengineering groups, focusing on smart sensor technologies for environmental monitoring and industrial applications.

• Telecommunications
• Visible Light Communication
• Signal Processing
• +۴ مورد دیگر

Boris Malčić is a Senior Lecturer at the Department of Telecommunications within the Faculty of Electrical Engineering at the University of Banja Luka. His research focuses on telecommunications, visible light communication, signal processing, and wireless network optimization. Key research areas include steganography, 5G waveform analysis, and IoT applications. Recent work examines audio signal quality in optical communication and FPGA-based synchronization for wireless systems. Active in international projects like NewFocus CA19111 COST Action , emphasizing next-gen optical wireless technologies. Publications span IEEE conferences and journals, addressing topics from energy-efficient Wi-Fi protocols to localization methods in wireless sensor networks.

Gérard Berryمشاهده پروفایل

استاد

• Computer Science
• Programming Languages
• Formal Verification
• +۳ مورد دیگر

Gérard Berry is a Professor at the Collège de France, holding the permanent Algorithms, Machines, and Languages chair since 2012. He previously held the Computer Sciences and Digital Technologies annual chair in 2007-2008 and 2009-2010. He is a member of the Académie des Sciences , Académie des Technologies , and Academia Europaea . His career spans academia at École des Mines de Paris and Inria, and industry as Chief Scientist at Esterel Technologies. His research focuses on formal verification of programs and circuits , parallel and real-time programming , and synchronous programming languages . He created the Esterel language and its industrial compiler, which became foundational for safety-critical systems in avionics and hardware design. His recent work includes the Hop and HipHop languages for multitier web orchestration. His publications highlight trends in formal methods , real-time systems , and program verification . These works bridge theoretical computer science with practical applications in embedded systems and digital transformation. Scientific Awards: CNRS Gold Medal (2014) Chevalier de la Légion d'Honneur (2012) Great Prize of EADS Foundation (2005) Science and Defense Award (1999) Gérard Berry has supervised 17 PhD theses and contributed to numerous academic collaborations. He co-founded Inria's evaluation committee and served on scientific boards for institutions like Institut Pasteur and IRCAM.

Pauline Poundsمشاهده پروفایل

استاد

• Drone design and aerodynamics
• Bipedal robot locomotion
• Embodied intelligence for robots
• +۵ مورد دیگر

Professor Pauline Pounds is a full Professor at the University of Queensland, jointly affiliated with the School of Electrical Engineering and Computer Science (Faculty of EAIT) and the Research Centre in Creative Arts and Human Flourishing (Faculty of HASS). She leads a broad robotics research portfolio centred on low-cost, high-performance drones, bipedal locomotion, embodied intelligence, disposable UAVs, exoskeletons and novel sensor systems. Education: Bachelor of Engineering – Australian National University Doctor of Philosophy – Australian National University Research interests span five thematic areas: (1) Drone design for extended range, efficiency and payload; (2) Low-cost bipedal robot locomotion; (3) Embodied intelligence enabling robots to exploit electromechanical dynamics without heavy computation; (4) Disposable, biodegradable UAVs for one-way missions; and (5) Human-augmenting exoskeletons for search-rescue and warehouse tasks. Her recent publications reveal concentrated effort in deep-reinforcement-learning-based robot control, tactile whisker sensors, lidar-based place recognition, modular aerial robots and real-world RL deployment—trends that emphasise cheap, robust autonomy and novel sensing. Funding & grants include current CSIRO “Robot-Enabled Autonomous Science” (2019-25), Wellcome Leap “Abdominal Laparoscopic Surgical Models with High-Fidelity Haptics” (2023-24), AuScope “EarthDrone” infrastructure (2023-25), and Advance Queensland / Trusted Autonomous Systems CRC “Integrated Sensors and Control” (2020-24), among others. PhD supervision: She has graduated four doctoral candidates to date (one as principal advisor, three as associate) and is currently available for new research students.