جستجوی استاد راهنمای دانشگاهی

Yüksel Yurtayمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Data Science
• +۸ مورد دیگر

Assoc. Prof. Dr. Yüksel Yurtay is an active faculty member at Sakarya University's Faculty of Computer and Information Sciences, Department of Data Science and Analytics. With a career spanning over three decades at the university since 1993, he has established himself as a prominent researcher and educator in the fields of data science, artificial intelligence, and business analytics. Education: Doctorate (2011-2020): Sakarya University, Institute of Business Administration/Production Management and Marketing, Thesis: "An empirical study on the impact of the dashboard on decision processes in the context of supply chain management" Master's (1996-1998): Sakarya University, Institute of Social Sciences/Production Management and Marketing, Thesis: "Activity based costing system and an application in electro-mechanical industry" Bachelor's (1987-1991): Anadolu University, Faculty of Arts and Sciences/Mathematics Dr. Yurtay's research focuses on the intersection of data science and business applications, with particular emphasis on dashboard systems, key performance indicators, and supply chain management. His work bridges theoretical computer science with practical business applications, developing innovative solutions for performance monitoring, decision support, and process optimization. His research portfolio demonstrates consistent productivity with publications spanning from 2018 through 2025, showing no signs of slowing down. Analysis of Dr. Yurtay's recent publications (2018-2025) reveals several key research trajectories: a strong focus on dashboard and KPI systems for business decision-making, growing interest in AI applications for emotion recognition (particularly in call center contexts), development of novel metaheuristic algorithms for optimization problems, and application of computer vision techniques for specialized detection tasks. His work consistently combines theoretical algorithm development with practical business applications. Dr. Yurtay has successfully secured research funding from prestigious sources including TÜBİTAK (project 1505) and industry partnerships with companies like Turkcell Global Bilgi. His current projects focus on real-time emotion recognition using deep learning and business process optimization. As an educator, Dr. Yurtay teaches core courses in numerical analysis, software engineering, computer engineering design, and data science. He has supervised graduate theses, including Akın YAŞAR's work on real estate photo quality evaluation using deep learning. His teaching portfolio reflects his expertise across both theoretical computer science and applied data analytics.

Erdal Erelمشاهده پروفایل

استاد

• Production Operations Management
• Manufacturing Systems Design
• Assembly and Disassembly Line Balancing
• +۴ مورد دیگر

Erdal Erel is a Professor of Operations Management (OM) and currently serves as the Vice Rector in charge of administrative and financial affairs at Bilkent University's Faculty of Business Administration. He holds a B.S. in Industrial Engineering from Istanbul Technical University (1981), an M.S. from Stanford University (1983), and a Ph.D. from Virginia Polytechnic Institute and State University (1987). His academic career has been dedicated to advancing research in Production Operations Management, focusing on manufacturing systems design, assembly/disassembly line balancing, scheduling, and project management. Erel's educational background includes: B.S. in Industrial Engineering, Istanbul Technical University (1981) M.S. in Industrial Engineering, Stanford University (1983) Ph.D. in Industrial Engineering and Operations Research, Virginia Polytechnic Institute and State University (1987) His research interests span several critical areas of operations management, including manufacturing systems design, assembly and disassembly line balancing, scheduling and sequencing methodologies, and project management. He has made significant contributions to robust optimization techniques applied to time-cost trade-offs and stochastic modeling in production systems. His work emphasizes practical solutions for complex operational challenges through advanced algorithms like ant colony optimization and beam search methods. Erel's publications reflect a focus on optimization in production systems, scheduling algorithms, and decision models under uncertainty. His research bridges theoretical advancements with real-world applications in manufacturing and service industries, addressing issues such as cost minimization, robust scheduling, and efficiency improvements in assembly line operations. Erel has contributed extensively to his field but no specific scientific awards are mentioned in the provided text. No specific information about advising students or grants is provided in the text. Erel's involvement in collaborative projects, including work with colleagues like I. Sabuncuoglu and J.B. Ghosh, highlights his role in interdisciplinary research teams focused on operational efficiency and advanced manufacturing technologies.

Fehmi Tanrıseverمشاهده پروفایل

دانشیار

• Operations Management
• Finance
• Commodity Risk Management
• +۷ مورد دیگر

Dr. Fehmi Tanrısever is an Associate Professor at Bilkent University's Faculty of Business Administration. He specializes in Operations Management and Finance, with research focusing on commodity risk management, start-up operations, and the interface between operational and financial decisions. He previously served at Eindhoven University of Technology until 2013 and holds a PhD from the University of Texas at Austin. Education: PhD in Supply Chain and Operations Management, McCombs School of Business, University of Texas at Austin (2009) Research Interests: Commodity Risk Management Operations-Finance Interface Start-up Operations Supply Chain Finance Fintech Energy Operations His work bridges operational decisions with financial implications, particularly in energy markets and pandemic scenarios. Publications Trends: Recent work emphasizes pandemic management strategies, energy market optimization, and financial hedging mechanisms. Papers often combine stochastic modeling with real-world applications in supply chain resilience and policy design. He is a Senior Editor for Production and Operations Management and has advised on energy market reforms like the Turkish Day-Ahead Electricity Market. No formal student advisees are listed in the provided materials.

• Supply Chain Management
• Logistics
• Artificial Intelligence
• +۳ مورد دیگر

Batin Latif AYLAK serves as Associate Professor in the Department of Industrial Engineering at the Faculty of Engineering, Turkish-German University, Turkey. Previously, he held an Assistant Professor position at Hitit University starting in 2015. His academic career spans over a decade of research at the intersection of industrial engineering, logistics, and artificial intelligence. His educational foundation includes: Doctorate in Mechanical Engineering from University of Duisburg-Essen (2010-2015) Master's degree in Mechanical Engineering from University of Duisburg-Essen (2008-2010) Bachelor's degree in Industrial Engineering from Istanbul Kültür University (2001-2006) with full scholarship Dr. AYLAK's research pioneers the integration of artificial intelligence in supply chain optimization, with particular emphasis on sustainable logistics systems. His work bridges theoretical advancements with practical applications in blockchain implementation for supply chain transparency, machine learning-driven energy forecasting, and intelligent warehouse management. He has developed novel frameworks like SustAI-SCM for agentic AI in sustainable supply chains and contributed significantly to understanding digital transformation in Turkey's logistics sector. His publication trajectory (2021-2025) reveals a strategic evolution from foundational logistics research toward cutting-edge AI applications. Early work focused on optimization algorithms and blockchain integration, while recent publications demonstrate leadership in agentic AI systems for sustainability, advanced predictive modeling for renewable energy, and pandemic-responsive supply chain solutions. This progression highlights his adaptation to emerging technological paradigms while maintaining core focus on supply chain resilience. No scientific awards or fellowships were documented in the provided materials. Dr. AYLAK has secured competitive research funding including project BAP TAÜ - 2018BM0028 for digital trend analysis in Turkey's logistics sector. While his publications indicate collaborative research with multiple co-authors across institutions, no formal graduate student advisement relationships were specified in the available documentation.

• Simulation
• Optimization
• Reliability Engineering
• +۵ مورد دیگر

Dr. Merve Uzuner is an Assistant Professor in the Department of Industrial Engineering at the Faculty of Engineering, Başkent University. She maintains an active research and teaching profile with significant contributions to simulation, optimization, and reliability engineering. Her research focuses on several critical areas: Simulation and modeling of complex production systems Optimization techniques including genetic and memetic algorithms Reliability engineering and system availability analysis Fuzzy logic applications in manufacturing environments Redundancy allocation problems with repairable components Dr. Uzuner's scholarly work demonstrates a consistent pattern of applying advanced analytical methods to solve real-world industrial problems. Her publications reveal a strong emphasis on combining simulation techniques with optimization algorithms to enhance system performance and reliability. She frequently addresses challenges related to uncertainty in production systems through fuzzy logic approaches. Her research has been published in reputable journals including the Journal of the Faculty of Engineering and Architecture of Gazi University, European Journal of Industrial Engineering, and Journal of Turkish Operations Management, as well as numerous conference proceedings from the Operations Research and Industrial Engineering National Congress. As an educator, Dr. Uzuner teaches core industrial engineering courses such as Introduction to Probability and Statistics, Simulation, Simulation Languages, and Statistical Analysis. Her teaching schedule shows active engagement with students across multiple courses including END 320, END 422, END 450, END 513, and END 588, demonstrating her commitment to both undergraduate and graduate education.

• Decision Analysis
• Multiple Criteria Decision Making
• Product Development
• +۴ مورد دیگر

Eyüp Ertuğrul Karsak is a Professor in the Industrial Engineering department at Galatasaray University , Turkey. He holds the UNESCO Chair in Computer-Integrated Manufacturing and has served in numerous administrative roles including Dean (2008-2014), Vice Rector (2014-2015), and Rector (2015-2023) at the same institution. His academic journey began with B.S. and Ph.D. degrees from Istanbul Technical University , followed by an M.S. from the University of Southern California . As a Chartered Financial Analyst (CFA) , he uniquely bridges industrial engineering with financial decision-making frameworks. Doctorate: Industrial Engineering, Istanbul Technical University (1994) M.S.: Industrial and Systems Engineering, University of Southern California (1990) B.S.: Industrial Engineering, Istanbul Technical University (1989) His research focuses on Multi-Criteria Decision Making (MCDM) , Data Envelopment Analysis (DEA) , and Fuzzy Logic Applications to complex systems. This spans supplier selection, healthcare performance evaluation, educational metrics, and sustainable technology assessment. His work has been published in leading journals such as Expert Systems with Applications , Computers & Industrial Engineering , and Resources, Conservation and Recycling . Karsak’s scientific impact is evidenced by his inclusion in the world’s top scientists list (PLOS Biology 2019, Elsevier 2021). He has led 14 research projects and advised 21 graduate students , particularly in fuzzy MCDM applications. His methodological contributions include novel frameworks combining QFD , DEA , and nonlinear programming for resource allocation and performance measurement. UNESCO Chairholder in Computer-Integrated Manufacturing Ranked among world’s top scientists (PLOS Biology 2019, 2020; Elsevier 2021) His managerial experience includes leadership roles across academic governance and departmental operations. Publications demonstrate consistent application of quantitative methods to real-world challenges in manufacturing, healthcare, and education sectors. For detailed project descriptions and grant information, please refer to the full description section.

Deniz Aksenمشاهده پروفایل

استاد

• Operations Research
• Logistics
• Vehicle Routing Problems
• +۳ مورد دیگر

Deniz Aksen is a Professor in the Department of Business - Operations Management and Information Systems at Koç University's College of Administrative Sciences and Economics. His research focuses on optimization problems in logistics, supply chain management, and facility location, with particular expertise in vehicle routing problems and interdiction models. Education: PhD in Operations Research from Purdue University (2003) Master's Degree in Industrial Engineering from Boğaziçi University (1996) Bachelor's Degree in Industrial Engineering from Boğaziçi University (1994) Professor Aksen's research centers on combinatorial optimization with applications in logistics and supply chain management. His work spans vehicle routing problems , facility location , interdiction models , and metaheuristic solution methods . He has made significant contributions to the understanding of r-interdiction problems where facilities must be protected against potential attacks, and has applied his methods to practical contexts including election logistics and waste collection systems . His approach often combines mathematical modeling with innovative heuristic and metaheuristic techniques to solve complex optimization problems that arise in real-world settings. Analysis of Professor Aksen's recent publications reveals a strong focus on bilevel and trilevel optimization models applied to security and logistics problems. His work frequently addresses the interdiction theme - studying how to optimally protect facilities against potential attacks or disruptions. The research shows increasing sophistication in modeling approaches, moving from basic vehicle routing problems to complex multi-level decision frameworks that incorporate protection and interdiction considerations. His applications span diverse domains including election logistics, waste management, and critical infrastructure protection, demonstrating the versatility of his methodological contributions to operations research. Professional Activities: Member of editorial boards for operations research journals Reviewer for leading journals in operations research and management science Active participant in international conferences on optimization and logistics

Faruk Polatمشاهده پروفایل

استاد

• Artificial Intelligence
• Reinforcement Learning
• Multiagent Systems
• +۶ مورد دیگر

Faruk Polat is a Professor of Computer Science at the Department of Computer Engineering, College of Engineering, Middle East Technical University (METU) in Ankara, Turkey. He has been serving at METU since 1994, progressing from Assistant Professor (1994-1996) to Associate Professor (1996-2002) and then to full Professor (2002-present). He received his B.S. in Computer Engineering from METU in 1987, followed by M.S. and Ph.D. degrees from Bilkent University in 1989 and 1994 respectively, with a visiting scholar period at the University of Minnesota (1992-1993). His primary research interests include Artificial Intelligence, Reinforcement Learning, Multiagent Systems, Markov Decision Processes, and Partially Observable Markov Decision Processes. His work significantly contributes to computational biology applications, particularly in gene regulatory network modeling, and to multiagent path finding in virtual simulations and computer games. He has published extensively in top-tier journals and conferences, with recent publications extending into 2025. Professor Polat has supervised numerous graduate students who have gone on to successful careers in academia and industry, including positions at Meta, Google, Apple, Microsoft, and various universities. His research group continues to be highly active, with current PhD students working on reinforcement learning, multiagent path planning, and gene regulatory networks. His scientific contributions span multiple domains, with a clear trajectory from foundational work in multiagent systems to increasingly sophisticated applications in computational biology and autonomous systems. His recent publications indicate continued innovation in reinforcement learning techniques, particularly in handling partial observability and complex path planning problems. NATO Science Scholar at University of Minnesota (1992-1993) Member and Team Leader/Deputy Team Leader of National Informatics Olympiad Group (1995-2011) Professor Polat has advised numerous PhD and Master's students who have secured positions at leading technology companies and academic institutions worldwide. His research has been supported by grants including Tubitak 1001 Project (Grant No. 115G086). His work bridges theoretical advances in artificial intelligence with practical applications in computational biology and autonomous systems.

M. Ural Uluerمشاهده پروفایل

استادیار

• Manufacturing Engineering
• Energy Efficient Manufacturing
• Energy Monitoring of CNC Machine Tools
• +۲ مورد دیگر

M. Ural Uluer serves as an Assistant Professor at Middle East Technical University (METU) in Ankara, Turkey, with his academic base in the university's engineering programs. He maintains an active office in room A-209 and can be reached at uluer@metu.edu.tr. Dr. Uluer's entire academic formation occurred at METU: Bachelor of Science (B.Sc.) - 2003 Master of Science (M.Sc.) - 2007 Doctor of Philosophy (Ph.D.) - 2024 His research program targets critical sustainability challenges in industrial manufacturing through: Real-time energy monitoring of CNC machine tools Theoretical modeling of process energy consumption Carbon footprint assessment for production systems Life cycle analysis methodologies Decision frameworks for eco-efficient manufacturing This work consistently bridges theoretical innovation with industrial applications, particularly in Turkish manufacturing sectors. Analysis of his publication timeline (2007-2016) reveals an evolving research trajectory from virtual factory systems for SMEs toward sophisticated energy prediction models using STEP standards. His most impactful contributions focus on quantifiable energy reduction in manufacturing process chains, exemplified by the 2016 E-MPC framework applied in household appliance production. The research demonstrates strong methodological continuity in applying computational modeling to sustainable manufacturing challenges. No major scientific awards are documented in publicly available sources at this stage of his career. As a newly appointed Assistant Professor following his 2024 Ph.D., Dr. Uluer is establishing his academic mentorship profile. Current public records contain no listings of graduate students or externally funded research grants.

• Audio and Speech Processing
• Signal Processing
• Image Processing
• +۳ مورد دیگر

Serkan KESER is an Associate Professor in the Department of Electrical and Electronics Engineering at the Faculty of Engineering and Architecture, Ahi Evran University, Turkey. He has been serving as a full-time faculty member since 2018 and previously served as Head of Department from 2018-2021. His educational background includes a PhD in Electrical and Electronics Engineering from Eskişehir Osmangazi University (2009-2018), a Master's degree in the same field from the same institution (2005-2008), and a Bachelor's degree in Electrical and Electronics Engineering from Mustafa Kemal University (1999-2005). Dr. KESER's research focuses on three main areas: Audio and Speech Processing : Including speaker identification, isolated word recognition, and speech coding techniques Signal Processing : With applications in fiber optic sensor systems and acoustic positioning Image Processing : Covering face recognition, image compression, and denoising techniques His recent publications demonstrate a strong trend toward integrating machine learning and deep learning approaches with traditional signal processing methods. He has made significant contributions in applying subspace methods to various domains including speech recognition, image processing, and sensor technologies. His work often bridges theoretical signal processing concepts with practical applications in areas like smart home systems, medical imaging, and environmental monitoring. Dr. KESER has successfully supervised five Master's students to completion, with thesis topics spanning deep learning applications for class attendance systems, photovoltaic systems, speaker identification, brain tumor classification, and speech-controlled robotic arms. He has led four research projects, including development of fiber optic motion sensors, smart home models using Arduino microcontrollers, and science outreach initiatives. His teaching portfolio includes advanced courses in digital image processing, artificial neural networks, digital signal processing, and machine learning at both undergraduate and graduate levels. Dr. KESER's research impact is reflected in his publication metrics: 30 total publications with 117 citations (h-index 5) through the UNIS system, 25 publications with 180 citations (h-index 6) on Google Scholar, and strong representation in Scopus and Web of Science databases.

Orhan Ecemişمشاهده پروفایل

دانشیار

• Quantitative Decision Methods
• Multi-Criteria Decision Making
• Data Analytics
• +۴ مورد دیگر

Orhan Ecemiş serves as an Associate Professor at Gaziantep University's Technical Sciences Vocational School within the Electronics and Automation Department, specializing in Robotics and Artificial Intelligence. His academic appointment commenced in 2024 following progression from Doctor Lecturer (2022-2024) and Lecturer (2009-2022) positions. He currently holds administrative roles as Head of Department and Deputy Director of Vocational School/College at Gaziantep University, having previously served in these capacities during 2010-2014 and 2020-2022. His educational background includes a Doctorate in Econometrics from Akdeniz University (2011-2016), a Master's in Computer Education from Gazi University (2001-2004), and undergraduate studies in Computer Teaching at Gazi University (1996-2000). Ecemiş specializes in Quantitative Decision Methods, Multi-Criteria Decision Making, Data Analytics, and Operations Research, with significant contributions to Artificial Intelligence applications. His research bridges computer science and economic modeling, focusing on practical decision support systems across diverse domains including energy policy, logistics optimization, and digital transformation. His work consistently applies advanced mathematical frameworks to real-world problems, particularly utilizing neutrosophic logic and machine learning techniques for complex decision environments. His 15 most recent publications demonstrate strong thematic continuity in applying Multi-Criteria Decision Making methods to contemporary challenges, with increasing focus on sustainability metrics, digital technologies, and economic forecasting. The research spans energy policy evaluation, cloud computing selection, green logistics, and international trade analysis, reflecting both methodological sophistication and practical relevance to Turkish and European contexts. As an academic supervisor, he has guided at least one Master's thesis to completion in 2025. His teaching portfolio encompasses computer programming, web technologies, algorithms, and data science applications across undergraduate and associate degree programs since 2014. While specific grant information isn't detailed in the source material, his extensive publication record across international journals and conference proceedings indicates substantial research activity.

Tahsin Enginمشاهده پروفایل

استاد

• Computational Fluid Dynamics
• Vibration Control
• Heat Exchangers
• +۳ مورد دیگر

Tahsin Engin is a Professor in the Department of Mechanical Engineering at Istanbul Technical University (ITU). His research focuses on Computational Fluid Dynamics (CFD), vibration control systems, heat exchanger optimization, and magnetorheological fluid applications. Engin has contributed extensively to structural dynamics, thermal systems, and fluid mechanics, with a particular emphasis on practical engineering solutions for mechanical systems. His work spans experimental and numerical methods, addressing challenges in automotive radiators, seismic protection systems, and energy-efficient heat exchangers. Engin has supervised 18 ongoing theses and holds multiple awards, including the TEÇEP Translation Work Awards (2013, 2015) and a Silver Medal from TPE (2017). His research often combines CFD modeling with real-world validation, advancing both theoretical and applied mechanical engineering. Key Research Areas: Vibration Mitigation, Heat Exchanger Design, Magnetorheological Fluids, Structural Dynamics, CFD Applications Notable Achievements: 6 TEÇEP Awards, 18 Theses in Progress, 16 h-index Engin's recent studies explore advanced damping techniques for seismic protection and optimize thermal systems using nanofluids and novel baffle designs. His interdisciplinary approach bridges mechanical engineering with energy efficiency and structural resilience.

Yusuf Sinan Akgulمشاهده پروفایل

دانشیار

• Computer Vision
• Medical Image Processing
• Machine Learning
• +۷ مورد دیگر

Yusuf Sinan Akgul is an Associate Professor at the Department of Computer Engineering, Gebze Institute of Technology (GIT), Turkey. He has been affiliated with GIT since 2005 and is part of the GIT Vision Lab. His research focuses on computer vision, medical imaging, and machine learning. He holds a Ph.D. from the University of Delaware (2000), where he also earned his M.S. (1995) and B.S. (1992) in computer engineering. His work includes contributions to image segmentation, stereo vision, and 3D structure recovery, with over 30 peer-reviewed publications and multiple patents. Education Ph.D. 2000, University of Delaware, USA M.S. 1995, University of Delaware, USA B.S. 1992, Middle East Technical University, Turkey Research Interests Akgul’s research spans computer vision fundamentals and applications, including medical image analysis, image segmentation techniques, 3D reconstruction from stereo data, and real-time surveillance systems. His work integrates machine learning and statistical methods to address challenges in biomedical engineering and video analysis. Key contributions include modular frameworks for anatomical contour extraction and adaptive focus measurement algorithms. Scientific Awards Frank Pehrson Graduate Student Achievement Award (1999) TUBITAK Career Grant (2006) Advising & Grants He has supervised 3 Ph.D. and 2 M.S. theses. Current funded projects include developing X-ray baggage inspection systems and operator-performance-tuned surveillance systems. Past grants include projects on 3D structure recovery using dual meshes. Labs & Teams He leads the GIT Vision Lab, focusing on interdisciplinary computer vision research with applications in healthcare and surveillance.

• (p,q)-Calculus
• q-Difference Equations
• Fixed-Point Theory
• +۳ مورد دیگر

Nihan TURAN is an Assistant Professor of Mathematics at Istanbul Beykent University , Faculty of Arts and Sciences, Department of Mathematics. She has been affiliated with the university since at least 2022, initially as a Research Assistant and currently as a faculty member. Research Interests: Her scholarly work spans several advanced areas of pure and applied mathematics. She has made significant contributions to (p,q)-calculus , q-difference equations , and their applications to fixed-point theory . Other areas of expertise include statistical convergence in various metric spaces, particularly cone metric spaces , and the study of theta functions and their modular properties. Publications: Dr. TURAN's research output is prolific and internationally recognized. Her articles have appeared in high-impact journals indexed in SCI-Expanded , Scopus , ESCI , and MathSciNet . A recurring theme in her work is the exploration of difference equations and their analytical solutions, often with applications to operator theory and discrete dynamical systems. Administrative Role: Beyond research, she serves on the Quality Commission Measurement and Evaluation Working Group at Istanbul Beykent University, contributing to institutional quality assurance and academic standards.

İbrahim Akbenمشاهده پروفایل

دانشیار

• Logistics
• Supply Chain Management
• International Trade
• +۳ مورد دیگر

Assoc. Prof. Dr. İbrahim Akben serves as a full-time academic and Vice President of the International Trade and Logistics Department at Hasan Kalyoncu University's Faculty of Economics, Administrative and Social Sciences. Education: Doctorate (2014) - Kahramanmaraş Sütçü İmam University Master's Degree (2008) - Kahramanmaraş Sütçü İmam University Bachelor's Licence (2005) - Kahramanmaraş Sütçü İmam University Associate Degree (1999) - Kahramanmaraş Sütçü İmam University His research concentrates on modern logistics challenges, with emphasis on Industry 4.0 integration in production systems, urban delivery optimization, lean supply chain methodologies, and eco-friendly transportation solutions. His work bridges theoretical frameworks with practical applications in trade and logistics management. Analysis of his 2018 publications reveals a consistent focus on technological disruption in logistics, particularly examining Industry 4.0's impact on production models, city-specific logistics challenges in emerging economies, waste reduction in supply chains, and sustainable vehicle technologies. These studies demonstrate applied research addressing real-world industry pain points.