جست‌وجوی استاد و پژوهشگر

Ismail Aliمشاهده پروفایل

مدرس

• Optimization Problems
• Evolutionary Algorithms
• Combinatorial Optimization
• +۷ مورد دیگر

Dr. Ismail Ali is a Lecturer at the School of Systems and Computing at UNSW Canberra, where he is affiliated with the Capability Systems Centre. He specializes in optimization problems, evolutionary algorithms, and simulation-based optimization techniques, with applications in production systems, supply networks, and defense-related problems. Dr. Ali's educational background includes: Bachelor's degree in Computer and Information from Zagazig University, Egypt (2010) Master by Research in Computer Science from UNSW Canberra (2014-2016) PhD in Computer Science from UNSW Canberra (2016-2020) Dr. Ali's research focuses on developing advanced optimization algorithms, particularly differential evolution techniques, for solving complex combinatorial optimization problems. His work spans multiple domains including production systems, supply chain management, and defense applications. He has made significant contributions to the adaptation of evolutionary algorithms for discrete optimization problems such as the traveling salesman problem and knapsack problems. His recent research has expanded into applications involving swarm robotics, carbon policy modeling, and secure simulation frameworks for defense applications. Analysis of Dr. Ali's publication record shows a consistent progression from theoretical algorithm development to practical applications in manufacturing, supply chains, and defense systems. A notable trend is the increasing integration of simulation techniques with optimization algorithms to address complex, multi-objective problems in dynamic environments. His work demonstrates strong interdisciplinary connections between computer science, operations research, and applied engineering domains. Dr. Ali has received significant recognition for his academic work: The Stephen Fester Prize for Outstanding Master's Thesis (2016) The Stephen Fester Prize for Outstanding PhD Thesis (2020) Dean's Award for Outstanding PhD Thesis at UNSW Canberra (2021) As an academic supervisor, Dr. Ali mentors PhD students and final-year graduation projects at UNSW Canberra. He has secured research funding through the Rapid Research Funding program ($16,500 in 2023) and the Faculty Seed Fund ($38,000 in 2024), supporting his work on optimization algorithms and their applications. His teaching responsibilities include courses in simulation, reliability engineering fundamentals, reliability program management, and reliability engineering assurance. As a member of the Capability Systems Centre at UNSW Canberra, Dr. Ali collaborates with researchers working on complex systems analysis, defense applications, and advanced computational methods. His work contributes to the Centre's mission of addressing challenging problems in defense and security through innovative systems approaches.

• Microgrid Control and Optimization
• Networked Control Systems
• Distributed Filtering and Sensing
• +۴ مورد دیگر

Professor Fuwen Yang is a leading academic at Griffith University's School of Engineering and Built Environment, specializing in Electrical and Electronic Engineering. With expertise in microgrid control, networked control systems, and renewable energy integration, he leads the Smart Energy Systems Group at the Institute for Intelligent and Integrated Systems. His research focuses on optimizing distributed energy resources and enhancing grid resilience through advanced control strategies. Current research aligns with Australian net-zero emissions goals Secured significant grants including ARC Discovery and Linkage projects Supervises 23 PhD and 35 Master's students Recent publications highlight innovations in virtual inertia control, digital twin frameworks, and data-driven predictive control. His work has earned global recognition, including the Stanford Top 2% Researchers list and Fellowships from Engineers Australia. Professor Yang's editorial roles include Associate Editor for IEEE Transactions on Industrial Informatics and other prominent journals. Acted as Chief Investigator on 8 major funded projects Contributed to Sustainable Development Goals 7 (Affordable Energy) and 9 (Infrastructure Innovation)

Michael Richterمشاهده پروفایل

استادیار

• Microeconomic Theory
• Game Theory
• Behavioral Economics
• +۳ مورد دیگر

Michael Richter is an Assistant Professor at the Bert W. Wasserman Department of Economics and Finance within the Zicklin School of Business at Baruch College, City University of New York (CUNY). He holds a PhD in Economics from New York University (2012), an MS in Mathematics from the University of Oregon (2004), and a BS in Mathematics from the University of Chicago (2002). Research Interests: His work spans Microeconomic Theory, Game Theory, and Behavioral Economics, focusing on topics like aspiration-based choice, switching costs, matching markets, and mechanism design. His research often bridges mathematical rigor with behavioral insights. Grants: Efficient Investment and Search in Matching Markets (PSC-CUNY, 2023-2024, $1,250, Funded) Submitted proposals to UK Research and Innovation and the John Templeton Foundation (status: pending). Service: He serves as a Committee Member on the Hiring Committee at Baruch College.

Robert L. Carrawayمشاهده پروفایل

استاد

• Data Analytics
• Decision Sciences
• Optimization
• +۴ مورد دیگر

Robert L. Carraway is a Professor at the University of Virginia's Darden School of Business, where he has been a faculty member since 1984. He currently serves as the Quantitative Analysis (QA) area head and previously held the position of Senior Associate Dean for MBA Programs from 2006-2011. Carraway teaches Data Analytics and Decision Sciences courses in Darden's MBA program, including First Year Decision Analysis, Managerial Quantitative Analysis, Optimization Models, and Darden Business Projects: Venturing. His global executive education work spans Europe, Asia, and Latin America. Education: B.S., East Carolina University M.B.A., East Carolina University Ph.D., Purdue University Carraway's research spans multiple areas of quantitative business analysis. His original work focused on Optimization, but he has expanded his focus to the broader role of analytics in decision making. He examines the relationship between intuition and rational analysis, exploring how these approaches complement one another in business contexts. His work investigates how analytical methods enhance innovation processes, making them more effective and efficient. A significant portion of his recent research addresses 'Big Data' applications in business. He has authored articles such as 'Big Data, Small Bets' and 'Meeting the Big Data Challenge: DON'T Be Objective,' which explore practical approaches to leveraging large datasets for competitive advantage. His work emphasizes combining analytical rigor with business judgment rather than relying solely on data-driven approaches. Carraway's publication record demonstrates a consistent focus on quantitative methods for business decision-making. His earlier work centered on optimization models and mathematical programming, while more recent publications address analytics, probability distributions, and risk analysis. A notable trend is his exploration of how decision-makers integrate quantitative analysis with intuitive judgment in complex, uncertain environments. Award Recognition: Multiple teaching honors at Darden School of Business Carraway has significantly influenced business education through his case method teaching, with numerous cases used in Darden classrooms worldwide. His global executive education work extends his impact to practicing managers across continents. While specific doctoral students aren't listed, his long tenure suggests substantial mentoring experience. As QA area head, he oversees faculty specializing in quantitative business analysis and collaborates with colleagues like Sam Bodily, Phillip Pfeifer, and Sherwood Frey on research teams focused on decision sciences.

• Cryptography
• Mathematics
• Computer Science
• +۲ مورد دیگر

Sorina Ionica is a Lecturer at the University of Picardie Jules Verne, specializing in Cryptography , Mathematics , and Artificial Intelligence . Her research focuses on the application of optimization techniques and algebraic geometry to cryptographic protocols, particularly in the context of genus 3 curves and isogeny-based cryptography. Research Interests: Cryptography, isogeny graphs, complex multiplication, index calculus, and AI-driven optimization algorithms. Projects: Involved in BforSAT (application of SAT solvers to cryptographic problems) and POSTCRYPTUM (post-quantum cryptography research). Recent Articles: Her work spans mathematical cryptography (e.g., CM curves and Weil descent attacks), algorithm optimization (Crossbred algorithm), and AI integration in cryptanalysis (tree search and SAT solvers). Labs: Sorina is affiliated with the OCIA Lab (Optimization and Cryptography, AI).

Wolfgang Echelmeyerمشاهده پروفایل

استاد

• Logistics and Supply Chain Management
• Material Handling
• Operations Research
• +۳ مورد دیگر

Professor Wolfgang Echelmeyer is a faculty member at Reutlingen University’s Faculty of Sustainability and Technology, specializing in Technical Logistics. His research focuses on logistics automation, human-robot interaction, and sustainable supply chain systems. Position: Professor Department: Technical Logistics Email: wolfgang.echelmeyer@reutlingen-university.de Research interests include robotic container unloading, lean logistics, and ergonomics in automated systems. Recent projects involve EU-funded initiatives like RobLog (EU# 270350) for cognitive robotics in freight handling. His work spans applications in city logistics, milk-run transportation systems, and decision support tools for automation investments. Key article trends explore robotics in logistics, sustainability in freight systems, and ergonomic resource planning. Publications from 2018–2024 emphasize innovative solutions for intermodal terminals, deformable cargo handling, and smart transportation networks. Administrative roles include Dean of Studies for the BSc in Sustainable Production and Business and Pro-Dean for Teaching at the Faculty of Sustainability and Technology. Collaborators include Marco Bonini, Tuan Nguyen, and Augusto Urru. Labs and teams: Active in projects like LogFabr (Logistics Fabrication) and partnerships with industry leaders such as Merck AG, Proctor & Gamble, and STIHL. His work addresses real-world challenges in logistics planning and automation deployment.

Rubén Alcarazمشاهده پروفایل

دانشیار

• Digital Humanities
• Web Accessibility
• Human-Computer Interaction
• +۳ مورد دیگر

Rubén Alcaraz is an Associate Professor at the University of Barcelona's Department of Library and Information Science, with teaching roles at Pompeu Fabra University (since 2013) and EINA Barcelona (since 2014). He holds a PhD in Engineering and Information Technology from University of Lleida (cum laude), Master's in Digital Content Management (UB/UPF), and Library Science Diploma (UB).

Rizos Sakellariouمشاهده پروفایل

استاد

• Parallel Computing
• Distributed Systems
• Large-Scale Software Systems
• +۵ مورد دیگر

Rizos Sakellariou is a Professor in the Information Management department at the University of Manchester. His research focuses on Parallel, Distributed and Large-Scale Software Systems , with significant contributions to Cloud Computing and Social Network Analysis. He is actively accepting PhD students for projects related to his expertise. Research Interests Parallel and Distributed Computing Cloud and Fog Computing Scientific Workflow Optimization Quality of Service in Distributed Systems Application of Computational Methods to UN Sustainable Development Goals Recent Research Trends Recent publications demonstrate his ongoing work in: Algorithm Design for Social Network Analysis Resource Optimization in Fog/Edge Computing Virtual Machine Migration in Cloud Environments Uncertainty Modeling with Fuzzy Logic Network Dynamics and Ethical AI Considerations

Florian Pommereningمشاهده پروفایل

استاد

• Classical Planning
• Heuristic Search
• Linear Programming
• +۳ مورد دیگر

Dr. Florian Pommerening is a Professor at the Department of Mathematics and Computer Science within the Faculty of Science at the University of Basel, Switzerland. He holds an email address of florian.pommerening@unibas.ch and can be reached via +41 61 207 05 37. His academic career is deeply rooted in classical domain-independent planning, with a focus on optimal planning through heuristic search and the application of linear and mixed integer programming in planning domains. University of Basel, Switzerland Faculty of Science Department of Mathematics and Computer Science Professor Rank Florian completed his PhD at the University of Basel in 2017 under the supervision of Malte Helmert. He also holds a Master's degree in Computer Science from the University of Freiburg (2012) and a Master's in Information Technology from Monash University (2010). His research spans topics such as classical planning, heuristic search, linear programming, mixed integer programming, and automated planning systems. His publication record from 2012 to 2025 demonstrates sustained contributions to planning algorithms, including cost partitioning heuristics, Lagrangian decomposition, and transition landmark generation. His work has been recognized with multiple awards, including the ICAPS 2024 Influential Paper Award, ECAI 2023 Quality Champion PC award, and the Dux of the Master of Information Technology at Monash University. ICAPS 2024 Influential Paper Award Quality Champion PC award (ECAI 2023) Runner Up, Best Student Paper Award (ICAPS 2023) CoRe Challenge 2022 Awards Best Student Paper Runner-Up (ICAPS 2022) Best System Demonstration (ICAPS 2022) Outstanding Senior Program Committee Award (AAAI 2021) ICAPS 2019 Best Paper Award Faculty Award 2018 (University of Basel) EurAI Artificial Intelligence Dissertation Award 2017 ICAPS 2018 Best Dissertation Award Outstanding PC Member Award (SoCS 2016) Winner, Unsolvability IPC 2016 AAAI 2015 Outstanding Paper Award ICAPS 2014 Outstanding Paper Award Dux of the Master of Information Technology 2010 (Monash University) Florian actively contributes to the planning community through tutorials at AAAI 2019 and ICAPS 2015, and through software development such as the Fast Downward planner and Planutils framework. His notable side project includes creating a quine in the Shakespeare Programming Language (SPL) with Thomas Mayer, showcasing technical creativity beyond core research.

• Modeling and Optimization
• Supply Chain Management
• Operations Research
• +۳ مورد دیگر

Assoc. Prof. Dr. Barış Keçeci is an Associate Professor in the Industrial Engineering program at Başkent University. He earned his PhD in Industrial Engineering from Gazi University (2014), Master's Degree from Başkent University (2008), and BSc from Gazi University (2002). Research interests include Modeling and Optimization, Supply Chain Management, Operations Research, Decision Science, and Multi-Criteria Decision Making, with a focus on logistics and transportation systems. His work often integrates advanced algorithms like fuzzy logic and neural networks for solving complex optimization problems. Recent publications emphasize variants of the Traveling Salesman Problem (e.g., with hotel selection, clustered trips), vehicle routing with simultaneous pickup/delivery, and applications of hesitant fuzzy models. These studies span sectors like defense industry, tourism, and shared mobility systems. Advising includes Master's theses on topics such as pandemic-era educational quality, intelligent transportation systems, and ERP software selection. Notable advisees include Neslişah Albayrak Melis Boran Cemal Aykut Gencel Nelişah Albayrak İpek Damla Akpinar Pelin Akyıl Kurt

Feng Xiaoمشاهده پروفایل

دانشیار

• Second Language Acquisition
• Pragmatics
• AI-Supported Language Learning
• +۱۲ مورد دیگر

Feng Xiao is an Associate Professor in the Department of Asian Languages and Literatures at Pomona College, where he also holds the title of Oldenborg Faculty Fellow. He contributes significantly to research and teaching in second language acquisition, particularly in Chinese as a second language, and integrates AI into language pedagogy. Educational Background: Ph.D., Carnegie Mellon University B.A. and M.Ed., Beijing Language and Culture University Feng Xiao's research centers on pragmatics in second language learning, examining how learners develop contextual language use during study abroad and how AI can support personalized language instruction. His work bridges applied linguistics, educational technology, and cross-cultural communication. He applies quantitative methods and data mining to analyze language development and assessment. His recent projects explore the role of AI beyond ChatGPT, gender-inclusive curricula, and the impact of the pandemic on study abroad. His recent publications reflect a strong trend toward integrating artificial intelligence into language education, expanding the understanding of pragmatic development in Chinese, and addressing equity and innovation in teaching. These works span journals in psycholinguistics, language assessment, and digital pedagogy. Scientific Awards and Grants: Hirsch Research Initiation Grant (2021–2023) EnviroLab Asia Curricular Innovation Award (Henry Luce Foundation, 2020) Andrew W. Mellon Grant for Digital Humanities (2016–2019) Hahn Fund for Innovative Teaching with Technology (awarded multiple times) Language Learning Dissertation Grant (2015) Modern Languages Department Dissertation Completion Scholarship (Carnegie Mellon, 2014–2015) Barbara F. Freed Award for Study Abroad Research (2014–2015) Feng Xiao actively mentors students and collaborates on digital tool development for language learning. He has led curriculum innovation projects and secured external funding for research and teaching. His work emphasizes educational equity, technological integration, and inclusive pedagogy. He teaches a range of courses from intermediate to advanced Chinese, as well as specialized topics such as Chinese in society, digital news, and culture. He is involved in interdisciplinary initiatives connecting language learning with digital humanities and environmental studies through grants like the EnviroLab Asia award. His lab-like collaborations focus on AI-driven pedagogical tools and data analysis in language acquisition.

• Artificial Intelligence
• Automated Planning
• Computer Science
• +۱ مورد دیگر

Mojtaba Elahi is a Doctoral Researcher and Visitor at the Department of Computer Science , Aalto University , affiliated with the research group led by Jussi Rintanen . His work focuses on artificial intelligence and automated planning , with a particular emphasis on optimization techniques and formal verification of planning systems. Email: mojtaba.elahi@aalto.fi

Marina Indriمشاهده پروفایل

دانشیار

• Industrial Robotics
• Mobile Robotics
• Collision Detection and Avoidance
• +۷ مورد دیگر

Marina Indri is a Tenured Associate Professor in the Department of Electronics and Telecommunications at Politecnico di Torino, Italy. She serves as a member of the Interdepartmental Center PIC4SeR for Service Robotics and chairs the Robotics Laboratory (1999–present). With over 100 publications, her work bridges industrial robotics , mobile robotics , and Industry 4.0 . Education: Laurea (Electronic Engineering, cum laude , 1991) Ph.D. (Systems Engineering, 1995) Research Interests: Specializing in Collision detection and avoidance for industrial manipulators Friction modeling and compensation Path planning and autonomous navigation Smart manufacturing systems Human-robot collaboration Awards: James C. Hung Best Paper Award (ETFA 2013, 2024) euRobotics Technology Transfer Prize (2014, 2017) Leadership: As IEEE Senior Member , she chairs the IEEE Industrial Electronics Society’s Factory Automation Technical Committee and serves on editorial boards for IEEE Transactions on Industrial Informatics and IEEE/ASME Transactions on Mechatronics . She leads projects like SpaceItUp! (space robotics) and PNRR FAIR (AI-driven manufacturing).

Laura Carnevaliمشاهده پروفایل

دانشیار

• Formal Methods
• Real-Time Systems
• Performance Evaluation
• +۴ مورد دیگر

Laura Carnevali is an Associate Professor of Computer Science at the Department of Information Engineering, University of Florence, where she leads research in formal methods and performance evaluation as a member of the Software Technologies Lab. She teaches Software Engineering for Embedded Systems, Quantitative Evaluation of Stochastic Models, and Foundations of Computer Programming at the School of Engineering. Her research focuses on formal methods for real-time software development and performance evaluation of non-Markovian models, with significant contributions to the ORIS Tool for quantitative system analysis. Key areas include: Stochastic modeling of critical infrastructure Formal verification of real-time systems Reliability engineering methodologies Performance evaluation of cyber-physical systems Her publications show strong emphasis on applied formal methods, with recent work focusing on workflow analysis, infrastructure reliability, and transportation systems modeling. Research consistently integrates theoretical frameworks with practical applications in engineering domains. Awards include: Best Paper Award at ICPE 2021 She actively contributes to academic service as program committee member for leading conferences including FORMATS, QEST, and EPEW, and serves as reviewer for IEEE Transactions on Software Engineering, Reliability, and other prestigious journals.

Marko Đukanovićمشاهده پروفایل

استادیار

• Combinatorial Optimization
• Graph Theory
• Bioinformatics
• +۴ مورد دیگر

Marko Đukanović serves as an Assistant Professor at the Department of Computer and Information Sciences within the Faculty of Natural Sciences and Mathematics at the University of Banja Luka. His academic career spans combinatorial optimization, graph theory, and bioinformatics applications, with significant contributions to algorithm design for complex computational problems. His research focuses on combinatorial optimization , particularly in graph domination problems and longest common subsequence variants . His work bridges theoretical computer science with practical applications in bioinformatics, social network analysis, and computational biology. Recent publications demonstrate expertise in developing advanced algorithms including biased random-key genetic algorithms, variable neighborhood search, and neural network-guided optimization techniques. Key publication trends show his specialization in solving constrained optimization problems on graphs, with growing emphasis on integrating machine learning components into traditional combinatorial algorithms. His 2024 publications in IEEE Transactions on Evolutionary Computation and Applied Mathematics and Computation represent significant contributions to the field. Best Paper Award at EvoStar Conference 2024 for 'A Neural Network Based Guidance for a BRKGA: An Application to the Longest Common Square Subsequence Problem' Dr. Đukanović actively participates in international academic collaboration, including recent panel discussions on knowledge transfer between Bosnia and Herzegovina and global expert communities. His work demonstrates strong international collaboration, particularly with researchers from TU Wien and institutions across Europe.