جست‌وجوی استاد و پژوهشگر

Armagan Bayramمشاهده پروفایل

دانشیار

• Operations Research
• Decision Science
• Stochastic Optimization
• +۵ مورد دیگر

Armagan Bayram is an Associate Professor in the Industrial and Manufacturing Systems Engineering Department at the University of Michigan-Dearborn's College of Engineering and Computer Science . Previously a postdoctoral researcher at Northwestern University, she holds a Ph.D. in Management Science from the University of Massachusetts Amherst, alongside M.S. and B.S. in Industrial Engineering from Istanbul Technical University. Education: Ph.D., Management Science, University of Massachusetts Amherst (2014) M.S., Industrial Engineering, Istanbul Technical University (2009) B.S., Industrial Engineering, Istanbul Technical University (2007) Her research focuses on stochastic models for capacity and resource allocation in mobility, healthcare, and logistics systems. Recent work includes urban curb space optimization , omnichannel retail fulfillment , and virtual appointment management in chronic care. Her methodological expertise spans stochastic optimization, dynamic programming, and experimental operations research. Current grants include NSF support for Curb Spaces in Urban Mobility Systems (2022-2024) and Inland Waterway Network Optimization (2024-2027) . Publications appear in top journals like Operations Research , European Journal of Operational Research , and Health Care Management Science . Scientific Accolades NSF Engineering Research Initiation (ERI) Award (2022) UM-Dearborn Distinguished Teaching Award (2020) IISE Healthcare Track Best Student Paper Advisor (2019) INFORMS Finalist for Doing Good with Good OR (2013) Bayram contributes to teaching through courses like Engineering Probability and Statistics and Simulation in Systems Design . She leads the Community Based Operations Research Lab , applying operations management principles to socially impactful projects.

Daniel Müller-Gritschnederمشاهده پروفایل

استاد مدعو

• TinyML
• Embedded Software Development
• Soft Error Resilience
• +۴ مورد دیگر

Daniel Müller-Gritschneder is an Adjunct Teaching Professor (Privatdozent) at the Technical University of Munich (TUM), affiliated with the Chair of Electronic Design Automation. He leads the 'Electronic System Level' research group, focusing on embedded systems, TinyML, virtual prototyping, and hardware resilience. He temporarily served as head of the Chair of Real-Time Systems (2019–2020) and holds a senior membership in IEEE. His research spans: TinyML : Optimizing neural network inference for microcontrollers. Virtual Prototyping : Fast simulation for embedded software development (e.g., ETISS simulator). Runtime Verification : Hardware monitoring for safety-critical systems. Fault Tolerance : Cross-layer resilience against soft errors. Design Automation : NoC synthesis and RISC-V toolchain optimization. His publications emphasize RISC-V-based systems, TinyML deployment, fault injection, and embedded AI. Recent works show trends toward compiler-assisted security, thermal management, and automated design-space exploration for edge devices. Awards: Best Paper Award (SiPS 2019) Habilitation Award (Bund der Freunde der TUM, 2019) 2nd Best Paper (SMACD'15) Best Paper nominations at DAC'07, DATE'10, Analog'10, NOCS'13 He advises researchers in the Electronic System Level group and contributes to EU projects (e.g., Scale4Edge). His lab develops tools like ETISS, MLonMCU, and Seal5 for RISC-V and TinyML ecosystems.

• Digital Humanities
• Art History
• Urban History
• +۱۱ مورد دیگر

Isabella Di Lenardo is a Lecturer and Scientist at the Digital Humanities Institute (DHI) at École Polytechnique Fédérale de Lausanne (EPFL), where she also serves as the coordinator of the EPFL Time Machine Unit and the European Local Time Machines. She holds affiliations across multiple departments, including DHI-GE, SAR-ENS, SHS-ENS, and EDDH-ENS, reflecting her interdisciplinary role in teaching and research. Her educational background includes a PhD in Theories and Art History, with postdoctoral and faculty experience at institutions such as INHA (Paris), EPFL, and IUAV (Venice). Her research spans Digital Humanities, Art History, Urban History, and GIS , with a focus on digital urban reconstruction, historical cadastres, and AI applications in cultural heritage. She employs advanced computational methods including machine learning, 4D modeling, and semantic segmentation to analyze historical maps, cadastral records, and art archives. Her work bridges humanities scholarship with computer science, particularly in reconstructing urban evolution and analyzing visual patterns. The recent publications reveal a consistent trend in AI-powered historical data analysis , especially in processing non-standardized historical documents, reconstructing urban spaces, and developing open-source tools for digital heritage. Her work frequently involves large-scale datasets from Venice, Lausanne, Paris, and Jerusalem, demonstrating a transnational and interdisciplinary approach. She has contributed to significant collaborative projects such as the Venice Time Machine , Parcels of Venice , and Time Machine Organization , often acting as a principal investigator or project leader. Her role involves coordinating diverse teams of researchers, engineers, and cultural institutions. Scientific contributions include: Development of the Morphograph tool for visual pattern recognition in art archives Automatic vectorization and analysis of Napoleonic cadastres Creation of 4D models for historical cities AI-driven text and pattern extraction from historical maps Building discovery engines for digital art history She actively teaches ex cathedra courses in Digital Urban History and Art History at EPFL and internationally. Her work in grants and projects emphasizes open data, reproducibility, and interdisciplinary collaboration. She has led research funded by organizations supporting digital heritage innovation. She is a key member of the Digital Humanities Laboratory at EPFL and the Time Machine Organization , where she fosters collaboration between computer scientists, historians, and cultural institutions. Her work in the Replica Project and ARCHiVe center highlights her leadership in digitizing and making accessible large art historical archives.

Jingrui Heمشاهده پروفایل

استادیار

• Statistical Machine Learning
• Large Scale Data Mining
• Heterogeneous Machine Learning
• +۶ مورد دیگر

Jingrui He is an Assistant Professor in the Computer Science Department at Stevens Institute of Technology, with primary research focuses on statistical machine learning and large-scale data mining. Her work spans theoretical algorithm development and practical applications in diverse domains. University: Stevens Institute of Technology Department: Computer Science Department Academic Rank: Assistant Professor Research interests include: Heterogeneous machine learning techniques Rare category analysis and detection Social network analysis Public safety applications Traffic analytics Multimedia processing Virtual metrology in semiconductor manufacturing Publishing trends show consistent contributions to machine learning, data mining, and graph-based methods across multiple domains including semiconductor manufacturing, social networks, and multimedia. She has collaborated with researchers from Stevens Institute of Technology, IBM, and Carnegie Mellon University on both theoretical and applied problems.

Ivan Duricمشاهده پروفایل

پژوهشگر ارشد

• Digitalization in agriculture
• Artificial intelligence and machine learning in agri-food systems
• Blockchain applications in agriculture and food industry
• +۴ مورد دیگر

Dr. Ivan Duric is a Research Fellow at the Department of Agricultural Markets, Agricultural Marketing and World Agricultural Trade, Leibniz Institute of Agricultural Development in Transition Economies (IAMO), Halle (Saale), Germany. Since October 2008 he has led and contributed to numerous international research projects focusing on digital transformation, trade policy, and value-chain analysis in agriculture and food systems. Education: Doctorate (Dr.) “summa cum laude” in Agricultural Economics, Faculty of Agriculture, Martin Luther University Halle-Wittenberg. Research Interests: Dr. Duric’s core expertise lies at the intersection of digital technologies and agri-food economics . His work explores how machine learning, blockchain, and immersive analytics reshape agricultural value chains, enhance transparency, and improve competitiveness. He continually investigates price transmission mechanisms , the impact of trade policy shocks (e.g., export bans, import restrictions), and pathways to strengthen food security in transition and emerging economies. Across more than forty peer-reviewed articles and policy briefs, a clear trend emerges: rigorous empirical assessment of how policy interventions and digital innovations jointly determine market outcomes—from wheat-to-bread chains in Serbia to salmon value networks spanning Norway, France and Poland. Awards & Recognition: Doctoral degree awarded “summa cum laude” (highest distinction), Martin Luther University Halle-Wittenberg. Grants & Collaborative Projects: Dr. Duric has co-ordinated or served as senior researcher in major EU and German-funded initiatives including AGRICISTRADE, AgriDigital, AGRIIMMERSE, VALUMICS, SecureFood, GERUKA, eTrust-Food, DITAC, GTRS, STARLAP, TAAST, UaFoodTrade , and the IAMO XR Lab . These projects investigate global grain trade, digital platform adoption, consumer trust, resilience of food systems, and immersive data analytics. Labs & Teams: He is a founding member and scientific lead of the IAMO XR Lab , where virtual-reality and immersive analytics are leveraged to visualize and interpret complex agricultural market data, creating new avenues for stakeholder engagement and policy dialogue.

Christoph Heinzlمشاهده پروفایل

استاد

• Scientific Visualization
• Visual Analytics
• Immersive Analytics
• +۳ مورد دیگر

Christoph Heinzl is a Professor of Cognitive Sensor Systems at the University of Passau since September 2022. He leads the Knowledge-based Image Processing research group at the Fraunhofer Development Center X-ray Technology (EZRT) . His academic background includes a PhD in Informatics and a Habilitation in 2022 , both from TU Wien . Research Focus: Scientific visualization, visual analytics, immersive analytics, virtual/augmented reality, machine learning, and X-ray computed tomography (XCT). Key Trends: Development of novel visualization techniques for complex volumetric data (e.g., dynamic volume lines, visual coherence frameworks), parameter space analysis, and cross-virtuality collaboration tools. Applications: Aerospace component inspection, defect analysis in composites (CFRP, GFRP), porosity quantification, and 4DCT time-series exploration.

Ben Liangمشاهده پروفایل

استاد

• Networked Systems
• Mobile Communications
• Distributed Machine Learning
• +۴ مورد دیگر

Professor Ben Liang is a faculty member at the Department of Electrical and Computer Engineering , University of Toronto, holding the L. Lau Chair . He has served on editorial boards of IEEE Transactions on Mobile Computing , IEEE Transactions on Wireless Communications , and Wiley Security and Communication Networks . His research focuses on networked systems , mobile communications , and distributed machine learning , with applications in wireless network virtualization, edge computing, and resource optimization. He explores stochastic scheduling , computation-communication co-design , and multi-resource fair allocation . Key publication trends: Wireless federated learning (2024-2025) Network virtualization and MIMO systems (2022-2025) Online distributed optimization (2023-2025) Stochastic resource management (2020-2024) Scientific Awards: Fellow of IEEE Best Paper Award, ACM MSWiM 2013 INFOCOM 2010 Finalist Ontario ERA Award 2007 IFIP Networking 2005 Best Paper Intel Foundation Graduate Fellowship 2000 Polytechnic University valedictorian 1997 Affiliated with IEEE , ACM , and Tau Beta Pi , he teaches courses like ECE368: Probabilistic Reasoning and ECE421: Machine Learning , emphasizing stochastic networks and random processes .

Baris Kasikciمشاهده پروفایل

دانشیار

• Computer Systems
• Reliability
• Security
• +۸ مورد دیگر

Baris Kasikci is an Associate Professor in the Paul G. Allen School of Computer Science & Engineering at the University of Washington. Previously (2017-2023), he was a Morris Wellman Assistant Professor in the Electrical Engineering and Computer Science Department at the University of Michigan. His research focuses on building efficient and trustworthy computer systems through innovative combinations of approaches from systems, computer architecture, and programming languages. Dr. Kasikci received his PhD in Computer Science at EPFL and has held research positions at Microsoft Research Cambridge, Google, Intel, and VMware. His work addresses critical challenges in system reliability, security, and performance in increasingly complex software ecosystems. His research interests center on improving the efficiency of datacenter applications and machine learning systems, analyzing and fixing failures, and enhancing hardware security. His lab develops techniques for automated bug detection, formal verification of distributed systems, and building systems support for heterogeneous hardware architectures. Recent projects include Whisper (profile-guided branch misprediction elimination), Huron (taming false sharing), and Agamotto (automatic detection and repair of bugs in persistent memory applications). Analysis of his recent publications shows a strong trend toward optimizing large language model serving, hardware security, and performance optimization for modern heterogeneous architectures. His work bridges traditional systems research with emerging AI infrastructure needs, particularly in efficient LLM serving, security vulnerabilities in modern hardware, and performance optimization for heterogeneous computing environments. NSF CAREER award Microsoft Research Faculty Fellowship Intel Rising Star Award VMware Early Career Faculty Grant Google Faculty Award Roger Needham PhD Award (best PhD thesis in computer systems in Europe) Patrick Denantes Memorial Prize (best PhD thesis at EPFL) Best Paper Award at OSDI'18 Best Paper Award at MICRO'22 Dr. Kasikci has advised numerous PhD students who have gone on to prestigious positions in academia and industry, including Tanvir Ahmed Khan (Assistant Professor at Columbia University), Akshitha Sriraman (Assistant Professor at CMU), and Jiacheng Ma (AMD). His research has been supported by significant grants from NSF, DARPA, Intel, Google, Microsoft, VMware, and Amazon. His lab, the EfesLab, focuses on building tools and techniques that make computer systems more reliable, secure, and efficient. The EfesLab, led by Dr. Kasikci, brings together postdocs, PhD students, and undergraduate researchers to tackle fundamental challenges in systems reliability and performance. The lab has developed numerous influential tools including Whisper, Huron, and Agamotto that address critical performance and reliability issues in modern computing systems. Current research directions include efficient LLM serving, security of emerging hardware technologies, and automated debugging techniques.

Sairaj Dhopleمشاهده پروفایل

استاد

• Power Systems
• Power Electronics
• Renewable Energy Integration
• +۳ مورد دیگر

Sairaj Dhople is the Oscar A. Schott Professor in the Department of Electrical and Computer Engineering at the University of Minnesota. His research focuses on renewable energy systems, particularly modeling and control of grid-connected inverters, power-system reliability, and distributed energy resources. University: University of Minnesota Department: Electrical and Computer Engineering Academic Rank: Professor His work spans power systems, power electronics, and control theory, with recent publications examining grid-forming inverters, stability analysis, and hybrid computing solutions for optimization problems. Key research themes include: Equivalent-circuit modeling for renewable systems Large-signal stability assessment inverter-based resources Grey-box system identification of power networks Interoperability standards for grid-forming technologies Scientific awards include the Institute for Advanced Study Faculty Fellowship (2018). Current projects funded by the National Science Foundation and U.S. Department of Energy explore analog/hybrid computing and universal interoperability for grid-forming inverters (UNIFI Consortium). His Dhople Research Group investigates power-system architecture and sustainability challenges.

• Structural Health Monitoring
• Civil Infrastructure
• Machine Learning for Engineering
• +۷ مورد دیگر

Dr. Andy Nguyen is a Senior Lecturer in Structural Engineering at the University of Southern Queensland, within the School of Engineering. He is an active researcher and educator, specializing in the Structural Health Monitoring (SHM) of critical civil infrastructure such as bridges, buildings, and transport tunnels. Bachelor of Engineering (BEng), NUCE, 1999 Master of Engineering (MEng), NUCE, 2003 Doctor of Philosophy (PhD), Queensland University of Technology (QUT), 2014 Dr. Nguyen's research is at the forefront of integrating advanced technologies into civil engineering. His primary focus is on developing and deploying sophisticated SHM systems that utilize sensors, data analytics, and machine learning to provide real-time insights into the structural integrity of ageing infrastructure. His work aims to enable proactive maintenance, extend the lifespan of structures, and enhance public safety. He has successfully implemented monitoring systems on major bridges and high-rise buildings in Queensland and New South Wales, with systems capable of even detecting distant earthquake events. His research interests span Structural Health Monitoring, Machine Learning for Engineering, Damage Detection, Finite Element Model Updating, Sustainable Building Materials like bamboo, and the application of AI for automated condition assessment of transport infrastructure. The analysis of his recent publications reveals a strong and consistent research trajectory centered on the application of data-driven and AI methods to solve practical problems in civil infrastructure. His work frequently combines signal processing techniques (like Stockwell Transform) with deep learning models for tasks such as crack detection in concrete and pavement. He also conducts significant research on model updating for complex structures like cable-stayed and arch bridges, using vibration data and optimization algorithms. The integration of machine learning for overload classification and the development of cost-effective, automated monitoring systems are key trends in his recent output. Advanced Queensland Fellow (2024-2027) Dr. Nguyen is actively involved in research supervision and collaboration. He is currently supervising several postgraduate students on projects related to AI-powered condition assessment, bamboo as a sustainable building material, and railway track design. He receives research funding from the Queensland Government through his Advanced Queensland Fellowship. His research has direct practical applications, as evidenced by his public engagement, such as writing for The Conversation on safeguarding ageing bridges, and his work with the Australian Network of Structural Health Monitoring. Dr. Nguyen's work embodies the development of a next-generation 'Living' Laboratory for engineering education, where research, teaching, and real-world infrastructure monitoring are integrated. His current projects involve creating smart, automated fault detection systems and advancing 'digital twin'-based monitoring platforms for infrastructure.

• Telecommunication Networks
• Distributed Machine Learning
• Edge Computing
• +۵ مورد دیگر

Falko Dressler is a Full Professor and Chair for Telecommunication Networks at the School of Electrical Engineering and Computer Science, Technische Universität Berlin. He holds a Ph.D. and M.Sc. in Computer Science from Friedrich-Alexander University of Erlangen-Nuremberg (1998-2003). His research focuses on next-generation wireless systems , distributed machine learning , edge computing , and applications in Internet of Things (IoT) , cyber-physical systems , and internet of bio-nano-things . Editorial roles: IEEE Trans. on Mobile Computing, Elsevier Computer Communications, IEEE/ACM Trans. on Networking Conference leadership: IEEE INFOCOM, ACM MobiSys, IEEE VNC Textbooks: Self-Organization in Sensor and Actor Networks (Wiley), Vehicular Networking (Cambridge) Recent publications highlight trends in Edge Computing Resilience and 6G Network Architecture , with a strong emphasis on Molecular Communication , Terahertz Band Synchronization , and Federated Learning in vehicular environments. Scientific contributions include multiple IEEE Fellow , ACM Fellow , and VDE ITG Prize 2023 recognitions. Advisory and professional activities include membership in the German National Academy of Science and Engineering (acatech), IEEE COMSOC Conference Council, and ACM SIGMOBILE Executive Committee. His work spans cooperative driving, ultra-low power sensor networks, and security in nano-communication systems.

Rob Rozehnalمشاهده پروفایل

استاد

• Sufism
• Digital Religion
• Ritual Studies
• +۶ مورد دیگر

Rob Rozehnal is a Professor and Chair in the Department of Religion at Lehigh University, where he also serves as Founding Director of the Center for Global Islamic Studies. His academic career spans interdisciplinary roles in Global Studies, Asian Studies, and South Mountain College. 2003 Ph.D. in Islamic Studies and History of Religions from Duke University 1995 M.A. in South Asian Studies from University of Wisconsin-Madison 1991 B.A. summa cum laude in History and Asian Studies from University of Puget Sound Rozehnal's research focuses on Sufism in South Asia, digital religion in Islamic contexts, ritual studies , postcolonial theory , religious nationalism , and globalization . His work bridges traditional Islamic scholarship with contemporary digital media analysis. His publications map Islamic digital media trends, including cyber Sufi communities and virtual expressions of American Islam. He has received significant funding such as the $1.4 million Mellon Foundation grant (2009-2015) and multiple Lehigh University fellowships. Lehigh University, College of Arts and Sciences, New Directions Fellowship (2013-2015) Charlotte W. Newcombe Doctoral Dissertation Fellowship (2003) American Academy of Religion, graduate student paper award (2000) Duke University Graduate School and International Studies Fellowship (2000) Rozehnal directs Lehigh's summer study abroad programs in India and Turkey focused on Islamic heritage, while maintaining personal interests in outdoor activities and meditation.

Federico Silvestroمشاهده پروفایل

استاد

• Power Systems
• Renewable Energy Integration
• Cybersecurity in Energy Networks
• +۷ مورد دیگر

Federico Silvestro is a Full Professor at the University of Genoa , affiliated with the Naval, Electrical, Electronic and Telecommunications Engineering Department . His academic roles include being a Course Coordinator, Department Council Member, and Deputy Director of DITEN. His research focuses on Power systems stability and control Cybersecurity in energy networks Electric propulsion for marine applications Optimal energy storage and microgrid design Integration of renewable energy in maritime contexts Recent publications highlight trends in data-driven power system analysis , DC microgrid modeling , cybersecurity for virtual power plants , and advanced energy management strategies for maritime and port systems. Email: federico.silvestro@unige.it He leads the ENET-RT Lab , focusing on real-time power systems simulation and co-simulation platforms for marine and grid applications.

David Colonمشاهده پروفایل

مدرس

• Propaganda
• Information Warfare
• Political History
• +۴ مورد دیگر

David Colon is a Tenured Lecturer at the Centre for History (CHSP) of University of Paris Institute of Political Studies, specializing in propaganda, communication, and digital history. His research focuses on mass persuasion mechanisms, information warfare, and media influence from historical and contemporary perspectives. Position: Tenured Lecturer Institution: Sciences Po (University of Paris Institute of Political Studies) Research Themes: • Propaganda and psychological manipulation • Digital history and modern information warfare • Political communication and social movements Scientific Awards: Prix Akropolis 2019 Prix Jacques Ellul 2020 Teaching & Publications: Holder of the agrégation in history, Colon contributes to graduate studies and has published extensively on propaganda, including works on Edward Bernays, cognitive warfare, and artificial intelligence's role in information manipulation.

Paul Fletcherمشاهده پروفایل

استاد

• Neuroscience
• Psychiatry
• Cognitive Psychology
• +۷ مورد دیگر

Professor Paul Fletcher is a Principal Investigator at the Institute of Metabolic Science, University of Cambridge, and holds the Bernard Wolfe Health Neuroscience Fund. He is affiliated with the Department of Psychiatry and collaborates with Professors Steve O’Rahilly, Sadaf Farooqi, Fiona Gribble, and Frank Reimann. His research bridges neuroscience and psychiatry to explore higher-level perceptual and learning processes shaping decision-making and behavior, particularly in relation to obesity and mental disorders. Academic Rank: Professor University: University of Cambridge School: Institute of Metabolic Science Department: Psychiatry Fletcher employs functional neuroimaging, behavioral studies, and pharmacological perturbations (e.g., dopamine agonists/antagonists) to investigate reward-related brain processes and their role in food choice, obesity, and psychiatric conditions like psychosis. His work emphasizes the integration of the brain with metabolic/endocrine signals and external environments. Key trends in his publications include predictive coding , delusions , neuroimaging , and virtual reality applications in mental health. Recent studies focus on anxiety , foraging behavior , schizophrenia , and health interventions . Scientific Awards Bernard Wolfe Health Neuroscience Fund Wellcome Trust Senior Clinical Fellow Fletcher’s research is funded by Wellcome and the Bernard Wolfe Fund, with collaborations spanning psychiatry, psychology, and clinical neuroscience. His work addresses mental health , obesity , and neurocognitive mechanisms of decision-making, supported by recent publications in top-tier journals.