جست‌وجوی استاد و پژوهشگر

Daniel S. Katzمشاهده پروفایل

عضو هیئت علمی

• Parallel and Distributed Computing
• High-Performance Computing (HPC)
• Fault Tolerance
• +۶ مورد دیگر

Daniel S. Katz is a Research Professor and Chief Scientist at the National Center for Supercomputing Applications (NCSA) at the University of Illinois Urbana-Champaign. He holds Research Associate Professor appointments in the Siebel School of Computing and Data Science and the School of Information Sciences (iSchool). His work focuses on advancing scientific software sustainability, open science practices, and high-performance computing (HPC). Katz earned his B.S., M.S., and Ph.D. in Electrical Engineering from Northwestern University (1988–1994). Roles and Affiliations: Chief Scientist, NCSA (100%, 2020–Present) Research Associate Professor, School of Information Sciences (0%, 2016–Present) Research Associate Professor, Computer Science (0%, 2016–Present) Editor-in-Chief, Journal of Open Source Software (JOSS) Co-founder, US Research Software Engineer Association (US-RSE) Research Interests: Katz's research spans parallel/distributed computing, fault tolerance, software sustainability, and open science policies. He advocates for FAIR (Findable, Accessible, Interoperable, Reusable) principles in research software and promotes equitable software practices. His work includes developing frameworks for software citation, improving reproducibility in AI, and fostering collaboration through community-driven initiatives. Awards: 2024 US-RSE Impact Award 2023 IEEE Computer Society Golden Core recognition R&D 100 Award (2018) for Swift/T workflow system Grants and Projects: Katz leads efforts in strategic initiatives like the FARR Research Coordination Network for FAIR and AI readiness. He collaborates on projects funded by the NSF and NASA, including work on sustainable HPC software and AI training programs at NCSA. Labs and Teams: He contributes to NCSA's research initiatives and is affiliated with the Better Scientific Software (BSSw) Fellowship program. His work integrates with teams like the Research Software Alliance (ReSA) to advance software engineering practices in academia.

David Simchi-Leviمشاهده پروفایل

استاد

• Supply Chain Management
• Business Analytics
• Operations Research
• +۳ مورد دیگر

David Simchi-Levi is the William Barton Rogers Professor of Engineering Systems at MIT and serves as the head of the MIT Data Science Lab. He is a leading expert in supply chain management and business analytics, with significant contributions to risk mitigation in global supply chains. His academic leadership roles include serving as Editor-in-Chief of Management Science and Operations Research. He has advised PhD students who have secured faculty positions at top universities like Berkeley, Carnegie Mellon, and Harvard. His research focuses on dynamic pricing, inventory control, and operations management in shared economies. Notable awards include the INFORMS Impact Prize (2020), National Academy of Engineering membership (2023), and multiple industry accolades. His industry ventures include founding LogicTools (acquired by IBM), OPS Rules (acquired by Accenture), and Opalytics (acquired by Accenture Applied Intelligence). Key articles in 2025-2024 explore topics like feature-based pricing, supply chain resilience, and reinforcement learning applications. His work bridges academic rigor with practical solutions for modern business challenges.

Alan Scheller-Wolfمشاهده پروفایل

استاد

• Stochastic Processes
• Operations Management
• Energy and Sustainability
• +۵ مورد دیگر

Alan Scheller-Wolf is the Richard M. Cyert Professor of Operations Management at Carnegie Mellon University's Tepper School of Business. His research focuses on stochastic processes applied to energy sustainability , supply chain management , renewable energy , and healthcare operations , including split liver transplantation and child welfare systems . He is affiliated with the Wilton E. Scott Institute for Energy Innovation. PhD in Operations Research (1996), Columbia University BS in Mathematics and Computational Science (1989), Stanford University His recent work emphasizes data-driven optimization , fairness in resource allocation , and algorithmic approaches for complex systems like server farms and quantum networks . Publications highlight applications in organ procurement , remanufacturing , and public service operations .

Marc Lichtmanمشاهده پروفایل

استادیار مدعو

• Machine Learning
• Data Science
• Systems
• +۴ مورد دیگر

Marc Lichtman is an Adjunct Assistant Professor at the University of Maryland's Department of Computer Science. He concurrently serves as a Principal Software Engineer at Microsoft and contributes to the GNU Radio open-source project. His work bridges academia and industry through research in software-defined radio (SDR), machine learning for wireless communications, and resilient communication systems. Education: Ph.D. in Computer Science, Virginia Tech, 2016 M.S. in Computer Science, Virginia Tech, 2012 B.S. in Computer Science, Virginia Tech, 2011 Research focuses on machine learning integration with SDR frameworks, cybersecurity for wireless systems, and distributed signal processing. Notable contributions include the PySDR textbook and advancements in GNU Radio's architecture. He has taught courses such as Machine Learning for Wireless Communications and Intro to Wireless Communications and SDR . His publications highlight trends in securing 5G/LTE systems against jamming, spoofing, and interference. Work emphasizes antifragile communication protocols and heterogeneous computing frameworks for SDR applications. Contributions span academic journals and industry collaborations. Advising and grants: While no formal student advisees are listed, his educational efforts foster SDR expertise. Current projects involve cloud computing integration with SDR platforms. Labs/Teams: Co-leads the GNU Radio project, advancing open-source SDR tools and frameworks.

Elham Mardanehمشاهده پروفایل

دانشیار

• Operations research
• Industrial optimization
• Mathematical modelling
• +۲ مورد دیگر

Elham Mardaneh is an Associate Professor at Curtin University's Centre for Optimisation and Decision Science. She develops mathematical frameworks for optimizing complex industrial systems, with applications in mining logistics, agricultural supply chains, and energy-efficient scheduling. Her grain industry optimization research won Curtin University's 2018 Business and Law innovation prize. Research Focus: Decision support systems for resource-constrained environments; stochastic optimization under uncertainty; applications in mining operations and supply chain management. Recent publications address open-pit mine scheduling and parallel machine optimization challenges.

Hoa Buiمشاهده پروفایل

پژوهشگر ارشد

• Operations Research
• Optimisation
• Discrete Optimization
• +۴ مورد دیگر

Dr. Hoa Bui is a Research Fellow at Curtin University's Centre for Optimisation and Decision Science, affiliated with the School of Electrical Engineering, Computing and Mathematical Sciences. Her research focuses on Operations Research, Optimization, Combinatorics and Discrete Mathematics, and Variational Analysis. She holds a PhD in Mathematics from Federation University, Australia (2020) and a BSc (Hons) in Mathematics from the University of Education, Ho Chi Minh City, Vietnam (2016). Research Interests: Dr. Bui's work bridges theoretical and applied aspects of optimisation, including discrete optimisation, convex optimisation, and their applications in scheduling, facility location, and combinatorial problems. She also explores variational analysis and graph theory, contributing to both foundational and industry-driven solutions. Awards: Trailblazer Prize Curtinnovation Award (2024) AustMS WIMSIG Cheryl E. Praeger Travel Award (2021) Maryam Mirzakhani Award (2020) Lift-Off Fellowship (2020) Advising & Grants: While her profile does not list formal advisees, her collaborative work indicates involvement in interdisciplinary projects. She is active in grant-funded research, particularly in optimisation for mining and industrial applications. Labs/Teams: Dr. Bui contributes to the Centre for Optimisation and Decision Science, focusing on cutting-edge optimisation methodologies and their real-world implementation.

Ryan Loxtonمشاهده پروفایل

استاد

• Optimisation
• Optimal Control
• Data Science
• +۳ مورد دیگر

Professor Ryan Loxton is the Director of the Centre for Optimisation and Decision Science at Curtin University, leading research in optimisation, optimal control, and data science. His work focuses on applying advanced mathematics to complex industrial processes, collaborating with companies like Woodside Energy and BHP. He holds a PhD and BSc Honours in Applied Mathematics from Curtin University. His research interests include optimisation algorithms, maintenance scheduling, and resource management, supported by grants from the Australian Research Council and industry partners. Notable awards include the 2020 Christopher Heyde Medal and the 2014 West Australian Young Scientist of the Year Award. Professor Loxton has pioneered software tools like the Quantum platform for maintenance optimisation, which won the 2017 South32 Designing for Excellence Innovation Award. His publications span optimisation techniques for mining, energy, and logistics, with a focus on cutting-edge methods like Benders decomposition and control parametrisation. Current projects include the ARC Industrial Training Centre for Transforming Maintenance through Data Science, addressing industry challenges in the resources sector.

• Operations Research
• Data Science
• Supply Chain Optimization
• +۶ مورد دیگر

Dr. Amir Hossein Ansaripoor is a Senior Lecturer at Curtin University's School of Management and Marketing (Faculty of Business and Law), specializing in Supply Chain & Operations Management. He holds a Ph.D. in Business Administration from ESSEC Business School (France/Singapore) and a Master’s in Industrial Engineering from Sharif University of Technology (Iran). His research focuses on applying Operations Research, Data Science, and Industry 4.0 technologies to address challenges in supply chain optimization, agribusiness, sustainable energy, and healthcare operations. He has developed courses like MGMT2017 and MGMT3018, integrating tools like AnyLogistix for immersive student training. His research has been published in top-tier journals such as the European Journal of Operational Research and Transportation Research Part C. Notable contributions include work on blockchain in supply chains, closed-loop supply chains, and evolutionary algorithms for agricultural routing. He has received awards including Curtin's Early Career Researcher Excellence Award (2017) and ESSEC's Ph.D. Fellowship (2009–2013). Amir actively supervises PhD and MPhil students and maintains collaborations with institutions in France, Italy, and Australia. Professional Memberships: INFORMS, ASOR, SCLAA Grants: British Telecom Ph.D. Research Grant (2011–2013) Amir leads research into resilient supply chain design, Industry 4.0 applications, and net-zero food systems. His lab focuses on merging advanced analytics with real-world operational challenges, emphasizing sustainability and technological adoption.

Celso Gustavo Stall Sikoraمشاهده پروفایل

پژوهشگر

• Operations Research
• Logistics Optimization
• Manufacturing Systems
• +۵ مورد دیگر

Dr. Celso Gustavo Stall Sikora is a Researcher at the Institute for Operations Research within the University of Hamburg Business School at the University of Hamburg. His work focuses on advanced manufacturing systems, particularly in assembly line balancing, logistics optimization, and stochastic modeling. He holds an office at Moorweidenstr. 18, Room 4001, and can be reached via email celso.sikora@uni-hamburg.de or phone +49 40 42838 5518 . His research emphasizes optimizing assembly line operations under uncertainty, integrating robotics, buffer management, and decomposition algorithms. Key areas include mixed-model production planning, last-mile logistics via innovative infrastructure (e.g., cargo tunnels), and real-time resequencing strategies. He has contributed to both theoretical advancements, such as chance-constrained stochastic balancing, and practical case studies involving robotic assembly line design and industrial collaboration. Publications span 2015–2025, reflecting sustained engagement with topics like Benders’ decomposition for balancing problems, cyclic scheduling, and maintenance-integrated production systems. His work bridges academic rigor and industrial application, addressing challenges in automotive manufacturing, renewable energy systems, and buffer-aware line configurations. No academic awards or formal student advisees are listed, but his contributions to operations research and manufacturing efficiency are evident through his prolific publication record. His office hours are by appointment, indicating a focus on project-based or collaborative research activities.

Petros Aristidouمشاهده پروفایل

استادیار

• Power and energy system informatics
• Control and operation of hybrid dynamical systems
• Modelling and simulation of large-scale power systems

Petros Aristidou is an Assistant Professor in Sustainable Power Systems at the Cyprus University of Technology (CUT), where he directs the Sustainable Power Systems Lab. His academic journey includes a PhD in Engineering Sciences from the University of Liège (2015) and a Diploma in Electrical & Computer Engineering from the National Technical University of Athens (2010). Previously, he held positions as Lecturer at the University of Leeds and Postdoctoral Researcher at ETH Zurich. His research focuses on three primary areas: power and energy system informatics, control of hybrid dynamical systems, and modeling/simulation of large-scale power systems. He specializes in addressing challenges related to low-inertia power systems, renewable integration, and grid stability. Award trends show consistent recognition from IEEE societies, with honors spanning best paper awards (TPWRS, ISGT-Europe), technical report awards, and scholarships. His publications demonstrate a progression from fundamental simulation methods toward applied solutions for renewable integration and grid resilience. TPWRS Best Paper Award (2021) IEEE PES ISGT-Europe Best Paper (2021) IEEE PES PowerTech High Quality Paper (2021) IEEE SEST Best Paper (2020) IEEE Outstanding Technical Report (2018) He leads multiple grants including the Horizon Europe MSCA ITN project Dependable Energy Systems (PI) and industrial collaborations on power system simulation methods. As lab director, he oversees research on power system dynamics and control, participating in international working groups addressing low-inertia system challenges.

Jeffrey P. Kharoufehمشاهده پروفایل

استاد

• Applied Probability
• Stochastic Processes
• Renewable Energy Systems
• +۶ مورد دیگر

Jeffrey P. Kharoufeh is a full-time Professor in the Department of Industrial Engineering at Clemson University, where he also serves as the Undergraduate Program Coordinator. He holds Fellow status with the Institute of Industrial and Systems Engineers (IISE) and is an active member of INFORMS, Omega Rho, and the Military Operations Research Society (MORS). Ph.D. in Industrial Engineering & Operations Research (Penn State University, 2001) M.S. in Industrial & Systems Engineering (Ohio University, 1997) B.S. in Industrial & Systems Engineering with Mathematics minor (Ohio University, 1995) His research focuses on applied probability, stochastic processes, reliability theory, and maintenance optimization for systems under uncertainty. He has contributed significantly to modeling renewable energy systems, service systems, and degradation-based reliability analysis. Key research trends include stochastic modeling of energy systems (offshore wind turbines, microgrids), maintenance optimization for heterogeneous components, and queueing theory applications in call centers and sensor networks. His work combines theoretical probability with practical operations research. Scientific awards: IISE Fellow Jeffrey teaches courses in industrial engineering, probability and statistics, and risk modeling. His publications reflect interdisciplinary applications in healthcare scheduling, wireless networks, and manufacturing reliability. While not explicitly listing student advisees, his academic contributions span over 20 years of research mentorship.

James Z. Wangمشاهده پروفایل

استاد

• Bioinformatics
• Computer Networks
• Medical Imaging
• +۶ مورد دیگر

James Z. Wang is a Professor in the School of Computing at Clemson University. He holds a B.S. and M.S. in Computer Science from the University of Science and Technology of China, and a Ph.D. in Computer Science from the University of Central Florida. He is a Senior Member of IEEE and ACM. His research focuses on bioinformatics, distributed systems, medical imaging, and data mining, with notable projects including G-SESAME for gene similarity analysis, ontology-based P2P information retrieval, and non-invasive skin cancer detection systems. He has taught numerous courses on databases, data mining, and multimedia systems since joining Clemson in 2005. Research Highlights: Developed tools for semantic similarity measurement in biomedical contexts (G-SESAME) Pioneered ontology-based approaches for P2P networks and proxy caching systems Advanced algorithms for distributed systems, self-stabilizing networks, and energy-efficient cloud computing Collaborated on medical imaging applications including melanoma detection and brain image analysis Publications reflect contributions to algorithms, distributed computing, bioinformatics, and multimedia systems, with over 100 peer-reviewed articles since 2000. His work bridges theoretical computer science with applied domains in healthcare and network infrastructure.

Abusayeed Saifullahمشاهده پروفایل

دانشیار

• Internet of Things
• Real-time Systems
• Cyber-Physical Systems
• +۳ مورد دیگر

Abusayeed Saifullah is an Associate Professor of Computer Science at Wayne State University's James and Patricia Anderson College of Engineering. He received his Ph.D. from Washington University in St. Louis in 2014, where he was awarded the Turner Dissertation Award. His research focuses on Internet-of-Things, real-time and embedded systems, cyber-physical systems, and wireless networks. Dr. Saifullah has published approximately 100 papers with over 6,700 citations (h-index 35) and received numerous best paper awards at top conferences including RTSS (2019, 2014, 2011) and IEEE ICII (2018). He has secured significant research funding including an NSF CAREER award (2019) and Department of Defense grants. His research spans low-power wide-area networks, real-time communication protocols, network security against jamming attacks, and energy-efficient scheduling. Current projects explore IoT for industrial automation and wireless systems over TV white spaces. Awards include: NSF CAREER Award (2019) College of Engineering Faculty Research Excellence Award (2020) Multiple Best Paper Awards (RTSS, ICII, EWSN) NSF CRII Award (2016) Turner Dissertation Award (2014)

Bo Shengمشاهده پروفایل

دانشیار

• Collaborative AI
• Edge Computing
• Mobile Computing
• +۳ مورد دیگر

Dr. Bo Sheng is an Associate Professor in the Department of Computer Science at the University of Massachusetts Boston. He holds a Ph.D. from the College of William and Mary and a B.S. from Nanjing University (China), both in Computer Science. His research focuses on collaborative AI, edge computing, mobile computing, cloud computing, cyber security, and wireless networks. He has served on Technical Program Committees for MILCOM 2025, IEEE Healthcom 2025, and IEEE ICC 2025. His recent work addresses challenges in data center congestion control, cloud-based object detection, and resource allocation in distributed systems. Dr. Sheng currently advises two Ph.D. students: Allen Yang (4th year) and Xiangtao Fu (1st year). His office is located in McCormack Hall, Room M-3-201-23. Research highlights include developing algorithms for optimizing network performance in disaggregated storage systems and enhancing fairness in data center operations. His publications span topics like machine learning-driven memory management and game-theoretic approaches to edge-cloud revenue sharing. Dr. Sheng’s contributions also extend to wireless signal analysis for mobile device proximity monitoring and secure RFID systems.

Jacek Błażewiczمشاهده پروفایل

استاد

• Scheduling Theory
• Operations Research
• Bioinformatics
• +۷ مورد دیگر

Jacek Błażewicz is a distinguished Professor at Poznan University of Technology, affiliated with the Institute of Computing Science. He is a member of the Polish Academy of Sciences (since 2002), IEEE Fellow (2013), and has held numerous prestigious positions including Vice President of IFORS (2014-2019). His educational background includes: B.Sc. in Control Engineering (June 1973) M.Sc. with distinction in Control Engineering (June 1974) Ph.D. in Computer Science (November 1977) Dr. habil. in Computer Science (May 1980) Professor Błażewicz is a world-renowned expert in scheduling theory, operations research, and computational biology. His research bridges theoretical computer science with practical applications in bioinformatics, particularly in DNA sequencing, RNA structure analysis, and protein structure prediction. He has pioneered the application of combinatorial optimization techniques to solve complex problems in molecular biology. His recent publications (2023-2025) demonstrate continued leadership in both traditional scheduling theory and cutting-edge interdisciplinary research. While maintaining strong contributions to classical scheduling problems (late work minimization, machine scheduling), he has expanded into computational biology applications including RNA world modeling, microRNA analysis in cancer research, and DNA algorithms. His work increasingly integrates modern AI techniques like graph neural networks with traditional operations research methods. His numerous scientific awards include: Member of the Polish Academy of Sciences (since 2002) 8 Scientific Awards of the Ministry of Science, Higher Education and Technology (1978-2008) Gold Medal of the Association of the European Operational Research Societies (1991) Doctor Honoris Causa at the University of Siegen (2006) Copernicus Prize awarded by FNP and DFG (2012) IEEE Fellow (2013) Member of Academia Europea (since 2023) Member of The National Academy of Artificial Intelligence (since 2025) Throughout his career, Professor Błażewicz has supervised numerous students and researchers, contributing significantly to the development of young scientists in both computer science and computational biology. He has led multiple EU projects and grants, establishing collaborative networks across Europe. His work has resulted in influential editorial roles, including Series Editor of International Handbooks in Information Systems for Springer Verlag and membership on editorial boards of leading journals like IEEE Transactions on Industrial Informatics and Journal of Scheduling. He directs several research initiatives including the Laboratory of Algorithm Design and Programming Systems, the BioServer - Computational Biology Server, and the European Centre for Bioinformatics and Genomics. His RNApolis project represents a significant contribution to RNA structure analysis and prediction.