جستجوی استاد راهنمای دانشگاهی

Laura Toni is an Associate Professor in the Department of Electronic & Electrical Engineering at University College London (UCL). She serves as Director of the MSc in Telecommunications and Internet Engineering and the MRes in Telecommunications. Additionally, she is a Turing Fellow at the Alan Turing Institute and a member of ELLIS (European Lab for Learning and Intelligent Systems). Her research focuses on coding, streaming technologies, machine learning for immersive communications, decision-making under uncertainty, and large-scale signal processing. She leads the LASP (Learning And Signal Processing) group at UCL. Education: MSc (2005) and PhD (2009) from the University of Bologna, followed by postdoctoral research at UC San Diego and EPFL under Professors L. Milstein, P. Cosman, and P. Frossard. Key roles include Technical Program Chair at ACM MM 2022, Keynote Co-Chair at ACM MMSys 2022, and leadership in organizing workshops on graph-based machine learning and emerging technologies in performing arts. She is a Senior IEEE Member and holds editorial roles in IEEE Multimedia Magazine and EURASIP Journal on Signal Processing. Her work bridges communication systems and machine learning, with contributions to adaptive streaming, network optimization, and graph signal processing. She actively promotes diversity and inclusion in technical conferences, including roles as Diversity Chair at MMSys 2021 and PIMRC 2020.

• Machine Learning
• Signal Processing
• Immersive Communications
• +۵ مورد دیگر

Jannik Matuschke serves as Associate Professor in the Department of Decision Sciences and Information Management at KU Leuven's Faculty of Economics and Business (FEB). He is an active member of both the KU Leuven Institute for Artificial Intelligence (Leuven.AI) and the KU Leuven Institute for Mobility (LIM), holding office at Hogenheuvelcollege (HOGC) 04.123 in Leuven, Belgium. His academic career spans multiple prestigious institutions across Europe, reflecting his international recognition in operations research and theoretical computer science. Dr. Matuschke completed his PhD in Mathematics in 2013 at Technische Universität Berlin under Martin Skutella and Britta Peis. His academic journey included a postdoctoral position at Universidad de Chile (2014), a DAAD P.R.I.M.E. fellowship at the University of Rome 'Tor Vergata' (2015), and a junior group leader/lecturer position at Technische Universität München (2016-2018) before joining KU Leuven in 2019. His research focuses on the intersection of discrete mathematics, theoretical computer science, and operations research, with specific expertise in combinatorial optimization, algorithm design and analysis, game theory and social choice, robustness and uncertainty, and logistics applications. Dr. Matuschke has made significant contributions to network flow theory, security games, and robust optimization frameworks, developing both theoretical foundations and practical applications. Analysis of his recent publications reveals a strong emphasis on robustness under uncertainty, with increasing focus on security applications and theoretical aspects of scheduling problems. His work demonstrates consistent innovation in decomposing complex optimization problems and developing approximation algorithms for challenging combinatorial settings. 2024 Meritorious Service Reward of the journal Operations Research Dr. Matuschke actively mentors several PhD students and postdocs, including Yanfei Chen, Léonie Gallois, Phablo Moura, Felix Rauh, and Fei Wu. He leads significant research projects such as 'Rigidity and Flexibility: Structures and Algorithms' (starting 2025), 'Designing resilient and recoverable infrastructures via multi-level and multi-stage optimization' (2022), and 'Optimization and analytics for stochastic and robust project scheduling' (2020), with funding from diverse sources including KU Leuven start-up grants, FWO research projects, and DAAD fellowships. As an integral member of the academic community, Dr. Matuschke serves as Associate Editor for Omega (since 2023), Operations Research Letters (since 2024), and OR Spectrum (since 2019). He co-chairs the program committee for WAOA 2025 and has participated in numerous prestigious conference committees. At KU Leuven, he coordinates the 'Master's Thesis in Production and Logistics' program and serves on the Teaching Portfolio Peer Review Committee.

• Combinatorial Optimization
• Algorithm Design and Analysis
• Game Theory and Social Choice
• +۴ مورد دیگر

Renata Medeiros de Carvalho is an Assistant Professor at Eindhoven University of Technology (TU/e), affiliated with the Process Analytics and EAISI Health groups. She holds a PhD in Computer Science from Federal University of Pernambuco (Brazil), an MSc and BSc in Computer Engineering from University of Pernambuco, and has conducted postdoctoral research at UQAM (Canada). Her research focuses on adaptive and declarative business processes, with particular emphasis on healthcare and data privacy. Education: PhD in Computer Science, Federal University of Pernambuco (2015) MSc in Computer Engineering, University of Pernambuco BSc in Computer Engineering, University of Pernambuco Research Interests: Flexible business processes and Process Mining Declarative modeling (e.g., OCBC language) Healthcare process optimization GDPR compliance frameworks Key Projects: PATIENCE 2 : Patient-centric healthcare through nomadic sensing BPR4GDPR : GDPR compliance toolkit Awards: Xerox University Affairs Committee Grant NSERC Engage Grant Teaching & Leadership: Local coordinator for EIT Digital Data Science and Erasmus Mundus BDMA master programs Teaches courses like Advanced Process Mining and DBL Data Challenge

• Business Process Management
• Process Mining
• Declarative Business Processes
• +۳ مورد دیگر

Mohammad T. Khasawneh is a SUNY Distinguished Professor and Director of the School of Systems Science and Industrial Engineering at Binghamton University. He leads the Watson Institute for Systems Excellence (WISE) and the Healthcare Systems Engineering Center. His roles include Director of the Manhattan Graduate Program in Health Systems. Education: BS and MS in Mechanical Engineering from Jordan University of Science and Technology (1998, 2000), PhD in Industrial Engineering from Clemson University (2003). Research focuses on healthcare systems engineering, operations management, and data science. His work optimizes healthcare systems for improved patient outcomes and cost efficiency. Key areas include predictive analytics, hospital resource utilization, and clinical performance improvement. He has generated over $15M in external funding and led projects with U.S. hospital systems. Notable achievements include developing the Executive Master of Science in Health Systems and an MS in Healthcare Systems Engineering. His research has produced 60+ journal articles and 120+ conference papers. Awards include SUNY Chancellor’s Awards for Teaching (2011) and Scholarship (2021), University Awards for Graduate Director (2015) and International Education (2016). He is an IISE Fellow and holds honorary visiting professorships at Hebei University of Technology (China) and Vellore Institute of Technology (India). Grants and funding: $2.5-3M annually via WISE, $39M in software/equipment grants. Lab/Initiatives: Healthcare Systems Engineering Center, WISE, and multiple hospital partnerships.

• Healthcare Systems Engineering
• Operations Management
• Data Science
• +۳ مورد دیگر

Markus Keller is a **Château Ste. Michelle Distinguished Professor** in the **Department of Horticulture and Landscape Architecture** at **Washington State University (WSU)**, affiliated with the **Prosser Irrigated Agriculture Research and Extension Center (IAREC)**. His research focuses on grapevine physiology, viticulture production systems, and environmental stress management. He holds a **Ph.D. (1995)** and **M.S. (1989)** in Agricultural Engineering from the **Federal Institute of Technology (ETH Zurich), Switzerland**. **Research Interests**: Dr. Keller’s work addresses crop physiology, irrigation strategies, cold hardiness, berry shrivel, and mechanized viticulture. His projects include developing deficit irrigation frameworks, understanding water movement in berries, and predicting frost damage risks using machine learning. He collaborates with industry partners like the USDA and Washington wine producers. **Key Contributions**: His studies on grapevine water relations, berry development disorders, and cold tolerance have advanced sustainable viticulture practices. He leads teams investigating precision agriculture tools for vineyards, including hyperspectral imaging and decision-support systems. **Grants & Funding**: Supported by grants from USDA, Washington wine tax, and juice processors. His work integrates applied research with grower education on frost protection and yield optimization. **Lab & Collaborations**: Directs research at WSU’s Viticulture and Enology program, collaborating with international teams on climate resilience and grapevine health. Mentors Ph.D. and M.S. students in experimental design and field studies.

• Viticulture
• Grape Physiology
• Irrigation Management
• +۴ مورد دیگر

Amitabh Mishra is an Adjunct Professor at the University of Delaware. His research focuses on three core areas: computer-communication networks (wireless architectures, cross-layer design, mobile cloud computing), network performance analysis (stochastic models, numerical optimizations), and network security (vulnerability assessments, authentication protocols). He has contributed to interdisciplinary fields including IoT security, smart healthcare frameworks, and socio-technical systems analysis. His work spans technical domains like wireless sensor networks, tactical network management, and quantum dot material studies, alongside applied research in tourism economics, healthcare data analytics, and educational technology. Notable contributions include frameworks for energy-efficient physiological monitoring, secure IoT configurations, and machine learning-driven security protocols. Recent research highlights include: Developing secure mobile cloud computing paradigms Modeling Multipath TCP capacity bounds using stochastic theory Investigating AI applications for deepfake ethics and tourism marketing His publications span technical journals in computer networks, medical IoT systems, and interdisciplinary studies in cultural tourism and climate change resilience.

• Computer-Communication Networks
• Wireless Networks
• Network Security
• +۵ مورد دیگر

Zhen Xie is an Assistant Professor in the Department of Computer Science at Binghamton University (SUNY), serving as Director of the Parallel Computing and Intelligent System (PCIS) Lab. He holds a PhD from the Chinese Academy of Sciences and a BA from Wuhan University of Technology. His research focuses on high-performance computing (HPC), machine learning, and their intersections, particularly optimizing performance for HPC and AI/DL applications across heterogeneous architectures. Research Highlights: Dr. Xie’s work emphasizes system-level performance optimization for ML and HPC, including GPU acceleration, memory optimization, and AI accelerator selection. His team has won the ACM Gordon Bell Special Prize (2022) for their GenSLMs project predicting SARS-CoV-2 evolution. Recent grants include a 2024 gift from OpenAI for AI testbed initiatives. Awards: ACM Gordon Bell Special Prize (2022), Impact Argonne Awards (2023) Lab: PCIS Lab explores middleware for parallel computing, targeting scientific simulations and big data analytics. Collaborations include Argonne National Lab and Lawrence Berkeley National Lab. Teaching: Teaches Distributed Systems (CS 457/557) and oversees independent studies. Previously trained researchers at Argonne’s ATPESC program. Grants & Collaborations: Subcontract with Lawrence Berkeley Lab (HEVI-LOAD), Argonne testbed expeditions, and OpenAI-funded projects. Active in DOE labs like Summit and Aurora supercomputers.

• High-Performance Computing (HPC)
• Machine Learning
• Parallel Computing
• +۳ مورد دیگر

Dr. Katie McConky is a Professor and Department Head of Industrial and Systems Engineering at Rochester Institute of Technology (RIT). She holds a Ph.D. in Industrial Engineering from SUNY Buffalo and prior experience as a research scientist at CUBRC Inc., where she worked on military and data mining projects. Her research focuses on operations research, machine learning, and energy systems optimization, addressing challenges in combinatorial optimization, cyberattack forecasting, and sustainable energy management. She has secured funding from agencies like ONR, AFRL, NASA, and NYSERDA. Education: BS and MS (RIT), Ph.D. (SUNY Buffalo) Key Roles: Department Head, Faculty Member, Research Scientist (CUBRC) Her work spans applications such as kidney exchange optimization, rover mission planning, and energy demand forecasting. She emphasizes interdisciplinary collaboration in her research, integrating machine learning with traditional optimization techniques. Dr. McConky’s publications highlight advancements in forecasting methodologies for cyber threats, energy systems, and transportation logistics. She teaches courses including Operations Research and Forecasting Methods, emphasizing practical software tools like Gurobi. Her contributions include patents on remote activity detection and energy storage optimization. Her research is supported by grants from federal agencies and industry partners, reflecting her expertise in both academic and applied domains.

• Operations Research
• Data Analytics
• Machine Learning
• +۴ مورد دیگر

Marianne Winslett is a Professor at the University of Illinois' Siebel School of Computing and Data Science, affiliated with the Department of Computer Science since 1987. Her research focuses on data security, information management, and privacy in cyber-physical systems. She co-led the TrustBuilder project, advancing access control and authentication in open computing environments, and directed the Advanced Digital Sciences Center (ADSC) in Singapore from 2009–2013, addressing challenges in data analytics and smart grids. Her work includes pioneering methods to ensure privacy in biomedical data analysis. Education: Earned her doctorate in Computer Science from Stanford University and worked at Bell Labs before joining Illinois. Awards: ACM Fellow (2006), NSF Presidential Young Investigator (1989), University Scholar, and Stanley H. Pierce Award for advising. She has supervised 24 PhD theses and mentored numerous graduate students, particularly supporting female scholars. Research Interests Secure data management in distributed systems Privacy-preserving techniques for biomedical data Adversarial attack detection in cyber-physical systems like smart grids Elastic resource scheduling in cloud environments Query optimization under differential privacy constraints Key Contributions Developed frameworks for self-supervised learning in smart grid cybersecurity Pioneered causal mechanism transfer networks for mechanical system domain adaptation Advanced auto-scaling strategies for real-time stream processing (DRS/Elasticutor systems) Labs & Teams Former Director of the Advanced Digital Sciences Center (ADSC), a University of Illinois research outpost in Singapore focusing on data analytics and IoT applications.

• Information Management
• Data Security
• Scientific Databases
• +۵ مورد دیگر

Dr. Juan Carlos De Luna Ducoing is a Research Fellow at the University of Surrey, specializing in advanced wireless communication systems with a focus on MIMO (Multiple-Input Multiple-Output) technologies. His work integrates neuromorphic computing, quantum annealing, and non-linear processing to enhance the efficiency and scalability of next-generation wireless networks. Research Interests: MU-MIMO detection and precoding Neuromorphic computing applications Quantum computing in wireless systems 6G network architectures Non-linear signal processing Hardware-software co-design (e.g., SWORD platform) Key Publications: His recent work includes NeuroMIMO (2024), which explores neuromorphic principles for power-efficient MU-MIMO detection, and Scalable MU-MIMO User Scheduling (2023), addressing resource allocation in dense networks. He also contributed to quantum annealing-based detection (2022) and Gyre Precoding (2021), achieving significant SNR gains. Collaborations: Works closely with Konstantinos Nikitopoulos and the SWORD research team to develop open-source platforms for rapid prototyping of advanced communication systems.

• Wireless Communications
• MIMO Systems
• Neuromorphic Computing
• +۴ مورد دیگر

Stella Kapodistria is an Associate Professor at Eindhoven University of Technology's Department of Mathematics and Computer Science, specializing in Stochastic Operations Research. She holds roles as EAISI High Tech Systems Associate Professor and editorial board member of journals like MCAP and PEIS. Her research focuses on data-driven decision-making, stochastic systems optimization, and maintenance policies, with applications in renewable energy, critical infrastructure, and cryptocurrency networks. She has secured grants including NWA-ORC, NWO Big Data, and TKI WoZ, and collaborates with industry partners in the Brainport region. Education: BSc (2003), MSc (2006, Hons.), and PhD (2009, summa cum laude) in Mathematics from the University of Athens. Postdoc at TU/e, followed by roles at Groningen University and TU/e's Stochastic Operations Research group. Teaching includes courses on Optimal Decision Making, Stochastic Performance Modeling, and Financial Mathematics. Research interests emphasize real-time learning, system resilience, and scalable algorithms for complex networks. Recent work addresses maintenance logistics, blockchain confirmation times, and wind energy prediction. She has published over 40 peer-reviewed articles and contributed to the 4TU Resilience Engineering Center. Awards include editorial leadership roles and grant funding. Advised 32 academic works and oversees industrial projects bridging theory and practice. Her labs and collaborations focus on adaptive systems, predictive analytics, and sustainable engineering solutions.

• Stochastic Processes
• Operations Research
• Data-Driven Decision Making
• +۴ مورد دیگر

Krzysztof Czarnecki is a Professor at the University of Waterloo's Department of Electrical and Computer Engineering, with a cross-appointment to the School of Computer Science. He serves as leader of the Waterloo Intelligent Systems Engineering Lab and holds the title of University Research Chair. His research focuses on generative software development, model-driven engineering, and autonomous systems, particularly in automotive cybersecurity and perception safety. Education: Doctorate in Computer Science, Technical University of Ilmenau (1999) Master of Science in Computer Science, Technical University of Ilmenau (1995) Bachelor of Science in Computer Science, California State University (1994) Research Interests: Dr. Czarnecki's work spans generative programming, software product lines, and safety-critical AI for autonomous vehicles. Recent projects address robust perception systems, uncertainty quantification in neural networks, and strategic driving behavior modeling. He co-authored Generative Programming (Addison-Wesley, 2000), a foundational text in the field. Publications Trends: Recent work emphasizes multimodal AI integration (e.g., LEO-MINI), 3D object detection improvements (OV-SCAN), and safety assurance frameworks for autonomous systems. His research bridges theoretical software engineering with applied robotics challenges. Awards: Premier’s Research Excellence Award (2004) British Computing Society’s Upper Canada Award (2008) University Research Chair, University of Waterloo (2023) Teaching & Leadership: Teaches courses like ECE 495 (Autonomous Vehicles) and ECE 651 (Software Engineering Foundations). Oversees WatCAR initiatives and collaborates on industry projects through the NSERC Bank of Nova Scotia Industrial Research Chair (previous). Labs & Teams: Directs the Waterloo Intelligent Systems Engineering Lab, focusing on AI-driven solutions for autonomous systems and safety-critical software. Active in cross-disciplinary collaborations with automotive and robotics partners.

• Generative Programming
• Model-Based Development
• Software System Families
• +۷ مورد دیگر

Ronald Graham is a Professor in the Computer Science and Engineering Department at the University of California San Diego (UCSD), affiliated with the Jacobs School of Engineering. He also serves as Chief Scientist at the California Institute for Telecommunications and Information Technology (Calit2). Graham’s career spans academia and industry, including a 37-year tenure at Bell Labs and leadership roles at AT&T Labs. He is renowned for contributions to combinatorics, Ramsey theory, scheduling algorithms, and discrete mathematics. His Erdős number of 1 underscores his collaborative ties to Paul Erdős, a legendary mathematician. Education: Graham earned his PhD in Mathematics from UC Berkeley in 1962. Research Interests: Graham’s work focuses on combinatorics, graph theory, number theory, computational geometry, scheduling theory, and quasi-randomness. He has also explored recreational mathematics, notably through his book Magical Mathematics (2011), which intertwines card tricks with mathematical principles. His research has influenced internet infrastructure design, including foundational work on routing algorithms and the development of Akamai Technologies. Notable Achievements: Graham has received the Steele Prize for Lifetime Achievement (2003), Euler Medal (1994), and Polya Prize in Combinatorics (1972). His concept of “Erdős numbers” revolutionized academic collaboration tracking, later adapted into Hollywood’s “Six Degrees of Separation” game. Advising & Grants: Graham mentors students and faculty, inspiring future generations through teaching and mentorship. The UCSD CSE Department established the Ronald L. Graham Chair in Computer Science in 2015 to honor his legacy, funded by an $18.5M alumni donation. Labs & Collaborations: As Calit2’s Chief Scientist, Graham advises on strategic directions, emphasizing interdisciplinary research in information technology and communications. His work bridges theoretical mathematics and applied computing, shaping global technological advancements.

• Combinatorics
• Graph Theory
• Number Theory
• +۷ مورد دیگر

Per Gustavsson is a Senior Professor at the Institute of Environmental Medicine, part of Karolinska Institutet in Stockholm, Sweden. He leads research in the Unit of Occupational Medicine and is affiliated with Jenny Selander's research group focusing on chemical and physical work environment exposures. His primary role involves epidemiological studies on occupational health risks, particularly linking workplace exposures to chronic diseases like cancer and cardiovascular issues. Education: He holds a Docent degree from Karolinska Institutet (1996). His research emphasizes methodological advancements in exposure assessment, including job-exposure matrices and expert evaluations. Key topics include motor exhaust effects, particulate matter toxicity, and occupational carcinogens in professions like chimney sweeps and drivers. Research Interests: His work spans occupational epidemiology, environmental health, and exposure-response relationships. Current studies investigate respirable crystalline silica, diesel exhaust, and shift work impacts. He collaborates internationally on large-scale analyses like the SYNERGY project for lung cancer etiology. Grant Activities: His research has been supported by grants (detailed in his profile). He contributes to public health policy through studies on labor market reforms and occupational disease recognition. Labs/Teams: Active in the Unit of Occupational Medicine and cross-disciplinary groups like the EPHOR Mega Cohort project. He advises on exposure assessment and collaborates with multiple European institutions.

• Epidemiology
• Occupational Health
• Environmental Health
• +۴ مورد دیگر

John McNamara is an IBM Master Inventor and Advanced Visiting Research Fellow at the University of Sheffield, holding Honorary Professorships at University College London (UCL) and Sheffield Hallam University. He specializes in interdisciplinary innovation across cybersecurity, transportation systems, and artificial intelligence, leveraging technologies like Cloud and Watson for Tech for Good initiatives. His roles include IBM Technical Specialist, IBM Thought Leader, and Open Group Distinguished Technical Specialist, with industry expertise spanning defense, finance, and healthcare sectors. Education: BSc (Hons) in Information Systems from the University of Hull. Research focuses on patentable inventions addressing complex event processing, automated systems optimization, and regulatory compliance. Key innovations include intelligent fuel management systems, automated style-checking frameworks, and goal-directed simulation tools for business processes. His work bridges academic research with real-world industry applications. Awards: IBM Master Inventor IBM Thought Leader Technical Specialist Open Group Distinguished Technical Specialist Collaborates with IBM UK University Programs to develop socially impactful technologies. Active in creating solutions for disease control, banking systems, and defense applications through cross-disciplinary partnerships.

• Artificial Intelligence
• Cybersecurity
• Transportation Systems
• +۳ مورد دیگر