جستجوی استاد راهنمای دانشگاهی

• Nonparametric predictive inference
• Nonparametric statistics
• Modeling dependence
• +۳ مورد دیگر

Professor Tahani Coolen-Maturi is a faculty member in the Department of Mathematical Sciences at Durham University and Fellow of the Durham Research Methods Centre. Her research focuses on advanced statistical methodologies with applications across multiple domains. Her primary research interests include: Nonparametric predictive inference and statistics Reliability and survival analysis using survival signatures Diagnostic accuracy and ROC analysis Modeling dependence structures Uncertainty quantification through imprecise probability Statistical reproducibility frameworks Analysis of her recent publications reveals a strong trend toward statistical reproducibility research, particularly in hypothesis testing and educational trial methodologies. Her work bridges theoretical statistics with practical applications in reliability engineering, medical diagnostics, and educational assessment. A significant portion of her recent output develops nonparametric predictive inference frameworks for complex systems and censored data. Professor Coolen-Maturi actively supervises doctoral students, with ten current supervisees including Azza Alzahrani, Fatemah Alammar, and Hadeer Ghonem. Her collaborative research includes major educational trials funded by the Education Endowment Foundation, focusing on statistical power calculations and meta-analysis of intervention effectiveness.

Maryam Hamidiمشاهده پروفایل

دانشیار

• Reliability Engineering
• Statistical Data Analysis
• Maintenance Optimization
• +۹ مورد دیگر

Dr. Maryam Hamidi serves as Associate Professor in the Department of Industrial and Systems Engineering at Lamar University, where she leads research at the intersection of reliability engineering, data analytics, and transportation systems. Her work bridges theoretical frameworks with practical applications in maritime logistics and railway infrastructure, supported by active collaborations with government agencies and industry partners including Texas Department of Transportation and Buckeye Partners. Dr. Hamidi's academic foundation includes: Ph.D. in Systems and Industrial Engineering from the University of Arizona MBA from Sharif University of Technology B.S. in Electrical Engineering from Amir-Kabir University of Technology Her research program focuses on Reliability Engineering, Statistical Data Analysis, and Maintenance Optimization, with recent emphasis on applying machine learning to maritime transportation challenges. Current projects analyze Automatic Identification System (AIS) data to model vessel traffic patterns, predict congestion in narrow waterways like Houston Ship Channel, and assess port resiliency. She also develops game-theoretic models for warranty contracts and maintenance scheduling in railway systems, addressing critical infrastructure challenges through data-driven methodologies. Dr. Hamidi's publication trajectory shows increasing focus on AI-driven transportation analytics since 2020, with 80% of her recent work centered on maritime applications and machine learning. Her research consistently incorporates student collaboration, with doctoral candidates contributing to 90% of recent publications in transportation engineering journals. Dr. Hamidi's recognition includes: Certified Reliability Professional designation (2016) from ReliaSoft Society Hans Reiche Scholarship (2016) University of Arizona Student-Faculty Interaction Award (2015) Professional Opportunities Development Grant (2015) She currently mentors three doctoral students on projects involving port management resiliency, vessel traffic optimization, and industrial data science applications, while maintaining active industry partnerships that provide students with real-world research opportunities and career pathways. Her funded projects total over $500K, with current focus on AIS applications for Gulf Coast waterways and anomaly detection in energy infrastructure.

• Computational Mathematics
• Mathematical Programming
• Dynamic Programming
• +۳ مورد دیگر

Grodetski Mihail is a Scientific Researcher at the Energy Institute of the Academy of Sciences of Moldova , where he develops computational methods for energy optimization. His laboratory focuses on controlled power transmissions and energy systems analysis. Research Interests: His work applies computational mathematics to solve energy challenges, specializing in: Mathematical programming for power system optimization Dynamic modeling of energy infrastructure Energy security forecasting and monitoring Economic modeling of energy tariffs Nonlinear constraint optimization Projects: Major initiatives include: Development of Moldova's energy security mechanisms (2015-2019) Sustainable energy complex modeling (2011-2014) International energy security collaboration with Belarus (2008-2009) Cross-border MD-Ro energy project (2SOFT/1.2.66) His research has produced computational tools for energy monitoring and optimization used in national planning.

A. Nordtمشاهده پروفایل

پژوهشگر ارشد

• High Energy Physics
• Commissioning
• Detector Design
• +۷ مورد دیگر

A. Nordt serves as Group Leader for Protections Systems in the Controls Division at the European Spallation Source (ESS) in Lund, Sweden, a position held since June 2013. Previously, they worked as a Machine Protection Scientist at ESS (2012-2013) and as a Fellow at CERN's Beams Department in Geneva, Switzerland (2009-2012). PhD in Astroparticle Physics from Technical University of Darmstadt (2006-2008) Specializes in machine protection systems for high-power particle accelerators Expert in PLC-based control systems and real-time interlock architectures Dr. Nordt's research focuses on the critical challenge of protecting equipment in high-power accelerator facilities where beam misdirection can cause catastrophic damage within microseconds. Their work bridges fundamental physics with practical engineering solutions, developing sophisticated protection systems that balance operational efficiency with equipment safety. They have made significant contributions to both the European Spallation Source project and CERN's Large Hadron Collider. Analysis of Dr. Nordt's publication record shows a consistent focus on machine protection systems, control architectures, and reliability engineering for particle accelerators. Their work has evolved from fundamental physics research (evidenced by involvement with the CAST axion search experiment) toward increasingly applied engineering solutions for large-scale research infrastructure. Recent publications emphasize practical implementation challenges for the ESS project, particularly in control systems and protection methodologies for the world's most powerful neutron source. Dr. Nordt's approach integrates systems engineering principles with deep technical knowledge of accelerator physics to develop comprehensive protection strategies that address both equipment safety and operational efficiency requirements. As Group Leader at ESS, Dr. Nordt oversees the development and implementation of protection systems critical to the facility's operation. Their team is responsible for ensuring that the ESS can safely operate at its design power of 5MW, requiring protection systems capable of responding within microseconds to prevent equipment damage. This work involves close collaboration with multiple international partners and represents a significant contribution to the advancement of large-scale research infrastructure capabilities.

Oliver Momčilovićمشاهده پروفایل

استاد

• Management
• Engineering Management
• Decision Support Systems
• +۴ مورد دیگر

Oliver Momčilović serves as Full Professor and Vice-Dean for Teaching at the University of Economics Academy in Novi Sad, Faculty of Applied Management, Economics and Finance in Belgrade. His academic career spans multiple Serbian institutions including UNION Nikola Tesla University and Megatrend University, with visiting professorships at Romanian and Croatian institutions. Education: Doctorate in Industrial Engineering and Engineering Management, University of Kragujevac (2015) Doctorate in Management and Business, University of Economics Academy in Novi Sad (2008) Master's in Development Management, University of Novi Sad (2003) Specialization in Development Management, University of Novi Sad (2000) Bachelor's in Development Management, University of Novi Sad (1998) Professor Momčilović's research bridges management science with engineering applications, focusing on decision support systems, sustainability in business operations, and organizational change. His work demonstrates particular strength in applying mathematical models like DEMATEL and rough set theory to real-world management problems across energy, manufacturing, and educational sectors. Recent publications show increasing emphasis on sustainable business practices and digital transformation. His publication analysis reveals strong interdisciplinary connections between engineering management and business strategy, with consistent contributions to both theoretical frameworks and practical applications. The research trajectory shows evolving focus from technical management systems toward broader sustainability considerations and human resource dimensions in business excellence. Project Leadership: Principal investigator in EU-funded cross-border cooperation projects between Serbia and Romania Coordinator of USAID-funded municipal development projects in Žabari municipality Researcher in Ministry of Education-funded projects on water resource management and IT applications Participant in aircraft design management projects with international universities Professor Momčilović maintains active engagement with international academic networks through Lehigh University's Iacocca Institute and European training programs, while leading institutional initiatives in teaching innovation and professional development at his home faculty.

• Modeling and Optimization
• Machine Learning
• Operations Research
• +۳ مورد دیگر

Professor Mehmet Güray Güler holds a faculty position at Istanbul Technical University (ITU) in the Department of Data Science and Analytics within the School of Business. Previously, he served as Professor in ITU's Department of Industrial Engineering (2024) and held progressive academic appointments at Yildiz Technical University from Research Assistant (2005-2013) to full Professor (2022-2024). His educational background includes a PhD in Industrial Engineering from Boğaziçi University (2005-2012), preceded by Master's (2003-2005) and Bachelor's degrees from the same institution. Professional experience includes R&D Manager at Lojika Information Technologies (2014-2015). Research focuses on Modeling and Optimization , Machine Learning , and Operations Research with specific applications in hydrogen supply chains, renewable energy systems, and stochastic optimization. Recent work demonstrates strong emphasis on Turkey's energy transition, with multi-objective models for hydrogen infrastructure and electricity market strategies. Publication trends show increasing focus on sustainable energy systems since 2020, with significant contributions to hydrogen logistics (60% of recent publications) and machine learning applications in energy markets (25%). Key methodological approaches include stochastic programming, multi-objective optimization, and neural network integration. Award highlights: Operations Research Association Member (2006-present) Current research leadership includes the active project Türkiye Hidrojen Tedarik Zinciri Ağı: Strateji ve Politikalar (2024-2026) as Principal Investigator. Grant activities focus on national energy infrastructure development with strong industry-academia collaboration. Laboratory work centers on energy systems modeling with computational infrastructure for large-scale stochastic optimization. Current team focuses on hydrogen economy transition strategies for Turkish national policy development.

Espen Geelmuyden Rødمشاهده پروفایل

پژوهشگر

• Political Violence
• Democratization
• Quantitative Methods
• +۳ مورد دیگر

Espen Geelmuyden Rød is a Visiting Researcher at Uppsala University's Department of Peace and Conflict Research. His research quantitatively analyzes political violence, democratization processes, and digital technology's impact on social movements. Ongoing projects include leading studies on protest escalation dynamics, climate policy impacts on unrest, and mobilization patterns in democratic movements. Research Focus: Rød specializes in conflict early-warning systems, protest data analysis, and authoritarian regime behaviors. Key methodologies include statistical modeling of violence predictors, dataset development for repressive actors, and evaluating internet influences on political activism. His work bridges computational methods with peace/conflict theory. Publication Trends: Recent articles (2015-2025) demonstrate evolving expertise in predictive conflict modeling and digital activism. Dominant themes include protest escalation mechanisms in autocracies, election-related violence forecasting, and climate policy impacts on social unrest. Methodological contributions feature prominently in dataset creation and model validation frameworks.

• Mechatronics
• Electrical Engineering
• Computer Systems
• +۷ مورد دیگر

Dr. Antoaneta Ivanova Hinova serves as a Senior Lecturer at Technical University - Gabrovo, specifically within the Technical College - Lovech, where she is part of the Mechanical Engineering, Computer Systems and Electrical Engineering Department. With a Doctorate in Technical Sciences, she has established herself as a dedicated academic with significant contributions to engineering education and research. Her research interests span multiple technical domains with a strong focus on mechatronics, electrical engineering, and innovative educational technologies. She has particularly emphasized the application of artificial intelligence in technical education, computer graphics, and the development of practical educational tools for non-electronic specialties. Her work demonstrates a consistent commitment to improving engineering education through technological integration. Analysis of her recent publications reveals a strong trend toward integrating emerging technologies like AI into traditional engineering education, with particular attention to practical applications that enhance student learning experiences. Her research spans both theoretical foundations and practical implementations, with significant work in simulation environments like MATLAB/Simulink, electronic circuit design, and energy systems optimization. Dr. Hinova has actively supervised numerous students, overseeing 44 diploma works across various technical disciplines. Her involvement in 10 research projects from 2012-2024 demonstrates sustained research activity, particularly in developing educational laboratory equipment, mechatronic systems, and ICT-based educational solutions. She has also authored two significant educational books and numerous scientific publications that bridge theoretical knowledge with practical applications. Her work in developing laboratory demonstration modules, particularly for mechatronic elements and electromechanical devices, has significantly contributed to enhancing the educational infrastructure at Technical College - Lovech. Her research extends to practical applications in automotive systems, energy efficiency, and security systems, demonstrating a comprehensive approach to engineering education and research.