Find Academic Supervisors

• Information Retrieval
• Text Categorization
• Search Engines
• +4 more

Abdül Kadir GÖRÜR is a Lecturer in the Department of Computer Engineering at Çankaya University. He serves as Head of the Division (Data Analytics) and Vice Director (Institute of Graduate Studies). His research focuses on Information Retrieval, Text Categorization, and Search Engine Evaluation, with expertise in Machine Learning applications. Education: Bachelor of Engineering in Electrical and Electronics Engineering, Eastern Mediterranean University (1993) Master of Science in Electrical and Electronics Engineering, Eastern Mediterranean University (1997) Doctor of Philosophy in Computer Engineering, Eastern Mediterranean University (2004) Thesis: Text Categorization Using Inductive Learning Algorithm and Experiments with Document Representation Research Interests: Dr. GÖRÜR’s work spans: Search Engine Optimization for Turkish Language Documents Deep Learning for Multi-Label Text Classification Constraint Programming in Manufacturing Scheduling Data Mining in Healthcare Systems Inductive Learning Algorithms (ILA) Development Professional Contributions: His publications address topics ranging from workforce scheduling optimization to plagiarism detection systems in e-learning platforms. Recent work emphasizes neural network architectures for text categorization and real-time data processing frameworks. Laboratory & Teams: While specific lab affiliations aren’t detailed, his administrative roles indicate involvement in data analytics initiatives and graduate research coordination.

Borja SotomayorView profile

Professor

• Computer Science Education
• Distributed Systems
• Resource Allocation
• +3 more

Borja Sotomayor is a Senior Instructional Professor in the Department of Computer Science at the University of Chicago. He specializes in teaching introductory computer science, software development, and computer networks. His research focuses on resource allocation in distributed systems using virtualization and, more recently, on computer science education. He has published widely in these areas and contributed to projects like the chidb database system and the Haizea resource management framework. He is actively involved in campus activities, including advising student organizations and designing educational tools. Sotomayor holds a PhD from the University of Chicago (2010) and has authored books on the Globus Toolkit. He is also known for designing t-shirts and promoting STEM education through initiatives like the CRA Education Committee.

Stephen SmithView profile

Research Professor

• Artificial Intelligence
• Planning and Scheduling
• Multi-Agent Coordination
• +5 more

Stephen Smith is a Research Professor at the Robotics Institute, Carnegie Mellon University. He directs the Intelligent Coordination and Logistics Laboratory and holds affiliations with Traffic21, Metro21, and the TSET University Transportation Center. His research focuses on AI-driven solutions for planning, scheduling, and coordination in complex systems, including transportation infrastructure, robotics, and manufacturing. Research interests include constraint-based optimization, multi-agent coordination (e.g., robot teams), robust planning under uncertainty, and adaptive traffic control systems like Surtrac. Applications span smart cities, autonomous vehicles, and distributed resource management. He collaborates with municipal partners on projects such as pedestrian safety apps and snowplow route optimization. His work bridges theoretical advances with real-world deployment, emphasizing scalability and practicality. Notable contributions include decentralized traffic control systems, learning-based planning assistants, and frameworks for distributed decision-making in uncertain environments. Current and former advisees include PhD students Hsu-kuang Chiu and Jayanth Krishna Mogali, alongside master’s students like Viraj Parimi. Projects include the PedPal smartphone app and the RADAR cognitive assistant.

Margarita JaneskaView profile

Professor

• Management Information Systems
• Financial Mathematics
• Project Management
• +4 more

Prof. Margarita Janeska is a Full Professor at the Economic Faculty in Prilep, part of the University of Goce Delčev. She holds the title of Full Professor since 2004 and specializes in Management Information Systems, Financial Mathematics, and Project Management. Her academic journey includes a BSc (1988), MSc (1995), and PhD (2004) from the Economic Faculty in Prilep, with her doctoral thesis focusing on optimal production series in industrial enterprises. Bachelor of Science in Econometrics & Cybernetics (1988) Master of Science in Production Optimization (1995) PhD in Management & Industrial Optimization (2004) Her research interests span statistical analysis of socio-economic development, e-business strategies, and the application of IT in business processes. She has authored multiple textbooks including Management Information Systems (2004), Mathematics for Economists (2007), and Financial and Actuarial Mathematics (2009). Collaborations with Prof. Kosta Sotirovski have produced influential works on IT effectiveness and e-commerce adoption. Her articles emphasize cloud computing, statistical performance evaluation, and strategic IT integration. Notable contributions include analyzing Macedonia’s ICT labor market, e-retailing trends in Ohrid, and the role of autonomic computing systems.

• Work and Organizational Psychology
• Human Factors
• AI and Robotics in Human Systems
• +4 more

Luca Pietrantoni is a Full Professor of Work and Organizational Psychology at the Department of Psychology 'Renzo Canestrari', University of Bologna. He coordinates the 'Human Factors, Risk and Safety' research group and actively participates in EU Horizon projects like SESTOSENSO and TUPLES, focusing on AI and robotics in human systems. His research spans mental health promotion in workplaces, cognitive ergonomics, and sustainable commuting. Education: PhD in Health Psychology (University of Florence, 2000) Postdoctoral fellowship in Social Psychology (University of Parma) Psychology Degree (University of Padua, 1995 with top honors) Research Interests: Human factors in AI/robotics integration Workplace mental health interventions Climate change adaptation strategies Cognitive ergonomics in manufacturing Grants & Projects: Principal Investigator in Horizon Europe projects (SESTOSENSO, TUPLES) Coordinator of H-WORK (mental health in SMEs/public workplaces) EU-funded studies on exoskeletons, coastal safety, and cyclist safety Labs/Teams: Human Factors, Risk and Safety research group.

Yaron ShaposhnikView profile

Associate Professor

• Stochastic Dynamic Optimization
• Machine Learning Applications
• Business Analytics
• +5 more

Yaron Shaposhnik is an Associate Professor of Information Systems and Operations Management at the Simon School of Business, University of Rochester. His research focuses on stochastic dynamic optimization, machine learning applications, and business analytics. He holds degrees from MIT (Operations Research) and the Technion–IIT (Industrial Engineering and Information Systems Engineering). Education: PhD in Operations Research, MIT MS in Industrial Engineering, Technion–IIT BS in Information Systems Engineering, Technion–IIT Research interests include developing decision support tools leveraging analytics to improve operations, with a focus on healthcare systems, financial lending, and scheduling algorithms. His work bridges optimization theory and practical applications, emphasizing interpretable machine learning models. Teaching includes predictive analytics using Python, PhD-level optimization courses, and seminars on data analytics in operations management. He advises PhD students and has industry experience as a research intern at Brigham and Women’s Hospital and software engineer at Mind CTI.

Deepak GuptaView profile

Professor

• Production Scheduling
• Supply Chain Optimization
• Energy Efficiency
• +2 more

Dr. Deepak Gupta is Professor and Department Chair of Industrial and Manufacturing Engineering at Wichita State University's College of Engineering. As Graduate Coordinator, he leads research in industrial systems optimization and sustainable manufacturing. His research develops computational models for production scheduling, supply chain management, and energy efficiency. Recent publications focus on Industry 4.0 applications in logistics, including dynamic vehicle routing algorithms and machine scheduling optimizations under uncertainty. Sustainability integration in manufacturing systems is a growing thematic focus. Earlier foundational work established energy efficiency frameworks through projects like the Energy Efficiency Knowledge Center (EEKC) and maintenance models for industrial equipment.

Katherine WatmoughView profile

Associate Professor

• Library and Information Science
• Academic Librarianship
• User Services
• +4 more

Katherine Watmough serves as Associate Librarian (equivalent to Associate Professor) at Thompson Rivers University Library, coordinating Borrower Services and acting as liaison for Adventure Studies, Agricultural Sciences, Animal Health Technology, Chemistry, Culinary Arts, Geology, Physics, Tourism Management, Trades & Technology, and Veterinary Technology. B.A. in History & English with First Nations Studies Minor M.L.I.S. with IT Management concentration B.C. Provincial Instructor's Diploma TESL level II eligible Her research centers on practical library operations including resource sharing models, staffing optimization, and innovative services like the 'Library of Things'. She critically examines neoliberalism's impact on academic libraries and actively integrates Indigenous knowledge frameworks through committee collaborations. Analysis of her 2010-2019 publications reveals consistent focus on user service enhancement, with recurring themes in staff training methodologies, extended-hour student engagement strategies, and collaborative collection development approaches across diverse academic disciplines. Watmough demonstrates professional leadership through conference presentations at national events including CAUT Librarian Conference and Access Services Conference, frequently partnering with committees like the Indigenous Knowledge Standing Committee to shape library policies and donation protocols.

• Computational Sustainability
• Cloud Computing
• Edge Computing
• +3 more

Ivona Brandic is a Full Professor of High Performance Computing Systems at TU Wien's Institute of Information Systems Engineering, leading the HPC Research Group. She specializes in Computational Sustainability, Cloud/Edge Computing, and Quantum-Classical Systems. Her roles include Head of the Computational Sustainability Research Unit and membership in TU Wien's Faculty Council. She teaches courses such as AI/ML in Climate Change and Hybrid Quantum-Classical Systems. Her research focuses on sustainable IT, energy-efficient systems, and hybrid quantum-classical workflows. Projects include computational sustainability initiatives funded by the Austrian Science Fund (FWF) and industry partnerships like the Virtual Shepherd project. She has contributed to over 50 publications, emphasizing edge computing, quantum algorithms, and HPC optimization. Notable contributions include developing frameworks like RIGOLETTO for hybrid scientific workflows and FRESCO for edge offloading. Her work bridges theoretical advancements with practical applications in environmental monitoring and energy efficiency.

Fantahun M. DefershaView profile

Professor

• Manufacturing system analysis
• Flexible and cellular manufacturing systems
• Reconfigurable manufacturing systems
• +7 more

Fantahun M. Defersha is a Full Professor in the Department of Mechanical and Industrial Engineering at the University of Guelph, Ontario, Canada. He holds a PhD in Mechanical Engineering from Concordia University (2006) and has over 28 years of academic experience, including roles as Area Head in Mechanical Engineering. His research focuses on manufacturing systems optimization, cellular manufacturing, supply chain modeling, meta-heuristics, and parallel computing applications. Education: B.Sc. Mechanical Engineering (1995), Addis Ababa University MEng. Mechanical Engineering (2000), University of Roorkee (IIT Roorkee) PhD Mechanical Engineering (2006), Concordia University Research Interests: Manufacturing system analysis, flexible/cellular manufacturing systems, reconfigurable manufacturing systems, supply chain optimization, meta-heuristics, parallel computing, and additive manufacturing sustainability. His work integrates computational methods like genetic algorithms and machine learning to solve complex industrial problems. Publications: Over 50 peer-reviewed journal articles, emphasizing sustainable manufacturing, optimization algorithms, and industrial systems. Recent work includes hybrid machine learning approaches for additive manufacturing and cloud-based digital twin systems. Honors: Campaign for a New Millennium Graduate Scholarship (2004–2005) Concordia University International Tuition Fees Remission Award (2004–2005) Concordia University Graduate Fellowship (2004–2005) Teaching & Advising: Taught over 25 courses, including Optimization in Engineering, Discrete Event Simulation, and Manufacturing Systems Design. Actively advises graduate students in mechanical and industrial engineering. Current research funding includes NSERC grants for Industry 4.0 integration and digital twin technologies. Labs/Teams: Leads research on smart manufacturing systems, digital twins, and sustainable production processes through collaborations with industry partners like AVL Manufacturing Inc.

Yalçın AçıkgözView profile

Associate Professor

• Employee Recruitment
• Job Search Behavior
• Applicant Decision-Making
• +6 more

Dr. Yalçın Açıkgöz is an Associate Professor at Appalachian State University's Department of Psychology. He holds a Ph.D. from Middle East Technical University (2016), an M.A. from Appalachian State University (2013), and a B.S. from Turkish Military Academy (2004). His research focuses on employee recruitment dynamics, applicant decision-making, social media applications in HR, and workplace professionalism. He leads a research lab with active projects on safety analytics and ethical AI in selection processes. Research Interests: Employee recruitment strategies, social media in talent acquisition, applicant reactions to modern selection tools, and occupational safety analytics. His work bridges organizational behavior, industrial-organizational psychology, and data-driven HR practices. Publications Trends: Recent work emphasizes safety analytics frameworks, AI ethics in hiring, and SDG alignment in organizational practices. His research often involves collaborations with industry partners to address real-world challenges in workplace safety and recruitment innovation. Awards: None explicitly listed. Advising & Grants: Mentors students in I-O psychology programs; no grant details provided. Lab Activities: Maintains an active research lab exploring cutting-edge topics in recruitment technology and occupational health analytics.

Nikolay SimakovView profile

Researcher

• High-Performance Computing
• Machine Learning
• Scientific Software Optimization
• +3 more

Dr. Nikolay Simakov is a Computational Scientist at the University at Buffalo's Center for Computational Research (CCR), joining in 2012. He holds a PhD in Computational Chemistry from Carnegie Mellon University, alongside BA and MA degrees in Applied Physics and Mathematics from Moscow Institute of Physics and Technology. Research Interests: High-Performance Computing (HPC), Machine Learning, Scientific Software Optimization, Data Analytics for Large Datasets, and Simulation of Biomolecular Systems Teaching: Taught graduate courses like EAS509 Statistical Learning and Data Mining-II and CDA501 Introduction to Data Driven Analysis, mentoring undergraduate interns at CCR Key Contributions: Developed Slurm Simulator for HPC scheduling, contributed to XDMoD/ACCESS Metrics for resource auditing, optimized GPU-based Poisson equation solvers, and advanced multi-rheology geophysical flow modeling Technical Focus: Performance monitoring of HPC systems, node sharing analysis, and ARM architecture benchmarking His work bridges computational infrastructure optimization and biological system modeling, with publications spanning HPC resource management, biomolecular simulations, and parallel computing frameworks.

Waguih ElMaraghyView profile

Professor

• Manufacturing Engineering
• Industrial Engineering
• Systems Engineering
• +3 more

Waguih ElMaraghy is a Professor at the University of Windsor's Faculty of Engineering, specializing in the Department of Mechanical, Automotive, and Materials Engineering. He is a renowned academic with notable contributions to manufacturing systems, reconfigurable robotics, and Industry 4.0 technologies. ElMaraghy holds prestigious fellowships from the Canadian Academy of Engineering and the Society of Manufacturing Engineers (SME), and actively serves on professional boards like the Canadian Engineering Accreditation Board. His research focuses on advanced manufacturing paradigms, including digital twin frameworks, supply chain resilience, and cognitive manufacturing systems. He has pioneered work on adaptable assembly lines and fault detection systems, integrating machine learning into manufacturing processes. His cross-disciplinary efforts extend to biomedical applications, such as using deep learning for breast cancer biomarker identification. ElMaraghy has been honored for over three decades of volunteer service to Professional Engineers Ontario and the American Society of Mechanical Engineers (ASME). His work on sustainable supply networks and reconfigurable machinery has shaped modern industrial practices, particularly in automotive framing systems for vehicles like GO trains. Awards: Ontario Volunteer Service Award, SME College of Fellows, Canadian Academy of Engineering Fellow Key Roles: Former Head of Industrial and Manufacturing Systems Engineering, Board Member of Canadian Engineering Accreditation Research Themes: Industry 4.0, Digital Twins, Supply Chain Resilience, Biomedical Applications of AI

Sreoshi BanerjeeView profile

Research Fellow

• Mechanism Design
• Cooperative Game Theory
• Queueing Theory
• +7 more

Sreoshi Banerjee is a Research Fellow and postdoctoral researcher at the QSMS Research Centre within the Faculty of Economic and Social Sciences at Budapest University of Technology and Economics (BME). She is currently on the 2024 academic job market and previously held a visiting postdoctoral fellowship at the University of Rochester (NY), collaborating with Prof. William Thomson. Her PhD in Quantitative Economics was completed at the Indian Statistical Institute (Kolkata) under the late Prof. (HAG) Manipushpak Mitra, with additional research at the Economics and Planning Unit (EPU), Delhi, under Prof. Debasis Mishra. Education includes: B.A. Economics from Shri Ram College of Commerce (SRCC), Delhi University M.A. Economics (specialization in World Economy) from Jawaharlal Nehru University (JNU), CITD PhD in Quantitative Economics from the Indian Statistical Institute (ISI), Kolkata Her research interests span mechanism design , cooperative game theory , queueing theory , and applications to environmental economics , welfare economics , and income inequality . Recent work emphasizes sequencing problems, strategyproofness, and fair allocation mechanisms in multi-server systems. Her job market paper explores the Shapley and serial solutions in such contexts. Publications and working papers focus on theoretical economics with practical implications for fairness, sustainability, and policy. Current research collaborations include Prof. Christian Trudeau (on scheduling and divisible jobs) and Prof. Christopher Stapenhurst (marine plastics and income redistribution). No scientific awards explicitly mentioned. She has supervised seven master’s theses on Risk Management/ESG topics and taught courses on Price Forecasting (MSc Finance) and cooperative game theory workshops. Active in the QSMS Research Centre, she frequently organizes and participates in seminars and academic events.

Naveen GargView profile

Professor

• Algorithms Design
• Approximation Algorithms
• Combinatorial Optimization
• +3 more

Naveen Garg is the Usha Hasteer Chair Professor in the Computer Science and Engineering Department at IIT Delhi. He earned his Ph.D. in 1994 and joined IIT Delhi as an Assistant Professor in 1997 after postdoctoral research at MPI-Informatik, Saarbruecken. He coordinates the UQ-IITD Academy of Research (UQIDAR). His research focuses on algorithms design, approximation algorithms for NP-hard problems, combinatorial optimization, and graph theory. He advises students on research projects and mentors through the department's structured programs. Contact: naveen@cse.iitd.ac.in. Research Interests: Approximation algorithms for NP-hard problems Combinatorial optimization Graph theory applications Algorithmic game theory Publications: Over 40 papers in top venues, focusing on network optimization, scheduling algorithms, and facility location problems. Active in conferences like ICALP and APPROX/RANDOM.