جست‌وجوی استاد و پژوهشگر

Briana Wellmanمشاهده پروفایل

استاد

• Robotics
• Artificial Intelligence
• Cybersecurity
• +۳ مورد دیگر

Briana Wellman is a Professor and Associate Dean for Academics at the School of Engineering and Applied Sciences, University of the District of Columbia (UDC). She leads academic affairs while maintaining active roles in research and teaching, particularly in robotics, artificial intelligence (AI), and cybersecurity. Her academic career includes chairing the Department of Computer Science and Information Technology from 2017 to 2024. Education: Earned a Doctor of Philosophy in Computer Science from the University of Alabama. Research Interests: Focus on multi-robot systems, AI-driven cybersecurity solutions, computer science education innovation, and applying robotics in interdisciplinary contexts like fashion and disaster relief. Recent work emphasizes post-pandemic learning strategies for urban commuter campuses and hybrid anomaly detection models. Publications: Recent contributions include studies on malware detection using neural networks, post-pandemic education frameworks, and multi-robot coordination algorithms. Her work bridges theoretical advancements with practical applications in security and education. Awards: Recognized with the 2023 Women of Color Rising Star Award for her contributions to STEM education and research. Grants & Leadership: Secured multiple NSF grants, including funding for HBCU learning communities in computing, cybersecurity research centers, and AI-cybersecurity partnerships. Her leadership extends to academic program development and curriculum innovation. Labs/Teams: Involved in NSF-supported initiatives such as the Cyber Security Research and Development (CSRD) Center and the AI-CyS research partnership, fostering collaborative research ecosystems.

Jun-Chau Chienمشاهده پروفایل

استادیار

• Biosystems & Computational Biology
• Bioelectronics
• Microfluidics
• +۷ مورد دیگر

Jun-Chau Chien is an Assistant Professor of Electrical Engineering and Computer Science at the University of California, Berkeley, and holds the Weber Family Engineering Faculty Fellowship. He is affiliated with the Berkeley Sensor & Actuator Center (BSAC) and the Berkeley Wireless Research Center (BWRC). His research bridges integrated circuits with bio- and quantum technologies, focusing on biosensors, molecular engineering, and mm-wave ICs for biomedical and quantum applications. Education: B.S. and M.S., National Taiwan University Ph.D. in Electrical Engineering, UC Berkeley (2015) Postdoctoral Training, Stanford University (2016–2017) Prior Experience: Research Engineer, Stanford EE (2017–2021) Assistant Professor, National Taiwan University Industrial roles at Xilinx, InvenSense, LifeSignals, and INanobio Research Interests: Analog/mixed-signal IC design for biomedical applications Bioelectronics and implantable/ wearable sensors RF/mm-wave circuits for quantum interfaces and medical imaging CMOS-microfluidics integration for point-of-care diagnostics Advanced calibration techniques for high-frequency devices Awards: 2022 IEEE BioCAS Best Paper Award 2019 IEEE CICC Outstanding Paper Award NSF CAREER Award (2025) MTT-S Graduate Fellowship (2014) Lab & Outreach: Chien Lab focuses on bio-IC convergence and quantum interfaces Develops wearable/implantable biosensors and mm-wave imagers Hosts community outreach programs for junior high/high school students He teaches EE 194 and EE 290 on integrated circuit testing and is actively involved in ISSCC technical committees.

Luca de Alfaroمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Fairness in ML
• +۱۲ مورد دیگر

Luca de Alfaro is a Professor in the Department of Computer Science and Engineering at the University of California, Santa Cruz (UCSC), where he has been a faculty member since 2001. He is affiliated with the Baskin School of Engineering and conducts interdisciplinary research at the intersection of computer science and real-world applications. Education: Ph.D. in Computer Science, Stanford University, 1998 Undergraduate studies, Politecnico di Torino, Italy Postdoctoral research, UC Berkeley Research Interests: His current research spans three major areas: (1) Machine Learning and AI, with a focus on fairness, subgroup performance analysis, data drift, and model improvement; (2) Computational Ecology, where he collaborates with ecologists to model animal habitats (e.g., birds, pumas) and support conservation using ML and optimization; and (3) Networks, where he applies reinforcement learning to design adaptive, efficient, and fair network protocols. His earlier work contributed to formal methods, software engineering, and reputation systems. Publication Trends: His recent publications (2020–2024) emphasize subgroup analysis in ML, particularly for fairness in speech and classification models, and reinforcement learning applications in wireless networks. Tools like DivExplorer and NotebookGrader reflect his commitment to practical, accessible research software. Scientific Awards: Fellow of the Association for Computing Machinery (ACM) Foreign Member of the Turin Academy of Sciences Four test-of-time awards for foundational work in formal methods, software engineering, and game theory Advising and Grants: Luca has advised over ten Ph.D. students whose work spans reinforcement learning, crowdsourcing, reputation systems, and educational technology. He has mentored postdoctoral researchers including Krishnendu Chatterjee and Mariëlle Stoelinga. While specific grants are not listed, his sustained research output and tool development (e.g., NotebookGrader) suggest active funding support. He leads projects integrating AI with ecology and education, indicating interdisciplinary grant involvement. Labs and Teams: He leads research initiatives in ML fairness and computational ecology, often in collaboration with Elena Baralis, Eliana Pastor, and ecologist Natalia Ocampo-Peñuela. He is the primary developer of NotebookGrader, an open-source platform for teaching Python via Google Colab, hosted on GitHub and used at UCSC.

• AI
• Machine Learning
• Software Engineering
• +۲ مورد دیگر

Juan Jenny Li is an Associate Professor at the Department of Computer Science and Technology at Kean University , focusing on AI and machine learning research with applications in software engineering, health, and cybersecurity. She teaches courses in Data Structures and Algorithms, Artificial Intelligence, and Machine Learning. NSF reviewer Member of ICSE/AST steering committee Special-issue editor for Springer Software Quality Journal 20 patents in software technology Her research integrates automated software testing methodologies with security frameworks, emphasizing test data generation and secure wireless systems. While no scientific awards are listed, her editorial and committee roles demonstrate leadership in academic circles.

• Electronics Engineering
• Digital Systems Design
• Embedded Systems
• +۱۲ مورد دیگر

Julio Martos Torres is an Associate Professor in the Department of Electronic Engineering at the School of Engineering, Universitat de València (UV). His work is centered in the DSDC Communications and Digital Systems Design Group, where he conducts research in embedded systems, condition monitoring, and educational technologies. He earned his PhD from UV in 2004 with a thesis on biomechanical measurement systems for wheelchair users. His research interests span electronics engineering , industrial monitoring , visible light communication , electromagnetic compatibility , geothermal energy systems , and engineering education . He has developed real-time systems for welding processes, sensor networks for thermal monitoring, and FPGA-based medical instrumentation. His recent work extends into interdisciplinary medical applications, particularly in gastroenterology, suggesting strong collaboration with clinical researchers. The most recent publications show a consistent trend in real-time monitoring systems , sensor design , and educational innovation in engineering. His work bridges theoretical electronics with practical industrial and medical applications, and he actively contributes to pedagogical advancements in STEM education through robotics and remote laboratories. Scientific awards are not mentioned in the provided text. Julio Martos Torres advises students and leads research within the DSDC group, focusing on applied electronics and digital systems. While specific grants are not listed, his involvement in high-profile projects like the ATLAS Tile Calorimeter suggests participation in large-scale collaborative funding initiatives. His work integrates industry collaboration and educational innovation, particularly in resistance welding monitoring and teaching methodologies. He is an active member of the DSDC Communications and Digital Systems Design Group , where his team develops advanced digital systems, wireless sensors, and educational platforms. The group emphasizes practical, industry-aligned research and innovative teaching tools, including robotic platforms and remote laboratories for STEM disciplines.

Joao Henrique Inacio de Souzaمشاهده پروفایل

پژوهشگر ارشد

• Wireless Communications
• Reconfigurable Intelligent Surfaces
• Signal Processing
• +۴ مورد دیگر

Joao Henrique Inacio de Souza is a Postdoctoral Researcher at the Department of Electronic Systems within the Faculty of IT and Design at Aalborg University, Denmark. Based at Fredrik Bajers Vej 7C, C1-105, 9220 Aalborg Øst, he operates under the Connectivity section with research focusing on advanced wireless communication systems. His work bridges theoretical signal processing with practical network optimization challenges in next-generation telecommunications. Research Focus: Dr. Souza specializes in temporal dynamics within wireless networks, particularly preserving simultaneity and chronology for sensing applications. His expertise spans reconfigurable intelligent surfaces (RIS), quality of service optimization in crowded XL-MIMO environments, and non-stationary channel modeling for 5G/6G systems. Key methodologies include temporal window integration techniques and multiplexing strategies for eMBB/URLLC services, addressing critical gaps in real-time wireless sensing and ultra-reliable communications. Publication Trends: His 2023-2025 output reveals a concentrated trajectory toward solving temporal coherence challenges in perceptive networks. Six publications demonstrate progressive refinement of RIS-assisted control mechanisms, with increasing emphasis on simultaneity preservation (2025) after foundational work on QoS-aware scheduling (2023). The research consistently targets 6G-enabling technologies through novel approaches to time-varying channel management and spatial multiplexing. Scientific Recognition: No formal awards or fellowships documented in current records Collaborative Framework: Active collaborations with Popovski, Soret, and Abrao indicate integration within Aalborg University's wireless research ecosystem. No student advisement or grant management details are publicly available. Research Infrastructure: Works within the Connectivity section's experimental framework for wireless temporal coherence testing, leveraging university resources for RIS prototyping and channel emulation.

• Embedded Systems
• Indoor Localization
• Internet of Things
• +۲ مورد دیگر

Marek Bawiec serves as an Assistant Professor in the Department of Technical Informatics at the Faculty of Computer Science and Telecommunications, Wrocław University of Science and Technology. His academic profile demonstrates expertise in embedded systems design and wireless communication technologies with particular focus on practical implementations in resource-constrained environments. Dr. Bawiec's research interests center around three main pillars: Embedded Systems Development for specialized applications Indoor Localization Technologies for GPS-denied environments Internet of Things (IoT) communication protocols and implementations His work addresses critical challenges in wireless networking, particularly Bluetooth Low Energy optimization for large-scale sensor deployments where conventional communication approaches fail. Analysis of his publication record reveals consistent focus on wireless communication systems with strong emphasis on experimental validation. His research demonstrates expertise in both theoretical modeling and practical implementation of communication protocols, with applications spanning emergency response systems, health monitoring solutions, and precision agriculture. The interdisciplinary nature of his work connects computer engineering with real-world problem solving across multiple domains. Dr. Bawiec maintains active research collaborations across disciplines, as evidenced by his contributions to pandemic forecasting models and biomedical applications. His technical approach combines rigorous experimental methodology with practical system design, resulting in publications that address both theoretical challenges and implementation constraints in wireless sensor networks.

• Embedded Automation
• Mechatronics Systems
• Educational Autonomous Robotic Systems
• +۵ مورد دیگر

Avraam Hatzopoulos is an Assistant Professor at the Department of Industrial Design and Production Engineering of the University of West Attica. His academic work focuses on Embedded Automation, Mechatronics Systems, and Educational Autonomous Robotic Systems within the broader field of Industrial Production Systems. He leads the Industrial Systems and Mechatronics Applications Research Laboratory. Mechanical Automation Degree Master of Telematics Project Management (Danube University of Krems, Austria) Master of Information and Communication Technologies for Education (National and Kapodistrian University of Athens) PhD in Industrial Systems (University of West Attica) His research spans multiple domains including: Embedded systems with automation emphasis Industrial mechatronics applications Small-scale educational robotics STEM education methodologies Predictive maintenance techniques IoT applications in agriculture and smart homes His recent publications analyze trends in: Open-source drone development for engineering education Big data in pharmaceutical sector optimization Low-cost robotics platforms using Arduino Technology Acceptance Model (TAM) evaluations Predictive maintenance with neural networks IoT agricultural education tools Scientific achievements include: Patent on polymorphic robotics testing base (2005) Founder of University of Piraeus Robotics Academy (2017) Contributor to Mechatron educational platform (since 2000) Teaching portfolio includes: Undergraduate: Microcontroller Design, Mechatronics, Robotics, Automotive Design Postgraduate: UAV Applications, Embedded Systems, Production Automation

• Embedded Systems
• Fault Tolerance
• Precision Agriculture
• +۵ مورد دیگر

Maurizio Rebaudengo is a Full Professor at the Department of Control and Computer Science (DAUIN) of the Polytechnic University of Turin. He is a member of the PIC4SeR Interdepartmental Center for Service Robotics and holds expertise in embedded systems, fault tolerance, and sensor network applications. Research Interests: Embedded systems, fault tolerance, precision agriculture, RFID technology, wireless sensor networks, and system dependability Scientific Awards: Ramamoorthy Best Paper Award (1997) Leadership Roles: Program Chair for the 4th International EURASIP Workshop on RFID, Committee Member for Public Administration Agreements (2020-2024) Projects: Scientific Director for HONEY (Hybrid ONline tEchnologY for particle therapy), FDM (Food Digital Monitoring), IDEM (Internet of Data for Environmental Monitoring), and OPLON (Healthy Longevity Opportunities). Teaching: Course lecturer for Electronic Calculators, Computer Science, Systems Programming, and Cybersecurity at both undergraduate and postgraduate levels. His work spans IoT applications in agriculture and healthcare, focusing on low-cost sensor networks , RFID-based traceability , and cyber-physical system resilience . Recent publications emphasize particulate matter monitoring and secure communication protocols in wireless environments.

• Mechatronics
• Industrial Robotics
• Robotic Vision Systems
• +۵ مورد دیگر

Aleksandr Sergeyev is a Professor in the College of Computing at Michigan Technological University , with affiliations in the Electrical and Computer Engineering department. He serves as Graduate Program Director for the MS in Mechatronics and Director of the FANUC Certified Industrial Robotics Training Center. PhD in Electrical and Computer Engineering, Michigan Tech MS in Physics, Michigan Tech BS in Electrical Engineering, Moscow University of Electronics and Automation Research Interests focus on Mechatronics Systems , Industrial Robotics , Robotic Vision Systems , Automation and Controls , and Optics/Image Processing . He actively develops curriculum frameworks for robotics education and explores complex control systems in industrial applications. Recent publications demonstrate expertise in robotics education , curriculum development , PLC systems , robotic vision , and industrial automation . His work emphasizes interdisciplinary collaboration and industry partnerships . Professional affiliations include membership in SPIE , IEEE , and ASEE . He collaborates with industry leaders like GM , Ford , FANUC Robotics , Edmund Optics , and Bosch . Grants and Funding : • Development of the Teleoperated Robotic Workcell ($80,775) • NSF-sponsored robotics education partnership ($702,324) • Industrial Automation and Control Laboratory ($255,000) • Collaborative projects with major corporations including FORD ($20,000), GM, and BAE ($48,500)

Andreas Johannsenمشاهده پروفایل

استاد

• System development and integration
• Business application systems
• Value-oriented corporate management
• +۱۲ مورد دیگر

Prof. Dr. Andreas Johannsen is a Professor of System Development and Integration at the Brandenburg University of Technology (FH Brandenburg) in Germany. He serves as the Managing Director of the Institute for Business Application Systems (IBAW) and has been actively involved in teaching, research, and industry collaboration since joining the university in 2006. His academic journey includes an MBA from the University of Edinburgh (1993-1994) and Business Administration studies at Eberhard Karls University Tübingen (1991-1993). Prior to his academic career, he accumulated substantial industry experience at SAP Deutschland, Mummert Consulting, and KPMG Consulting/BearingPoint, bringing practical insights to his academic work. Member of the IPv6 Council at the Hasso-Plattner-Institute since 2014 Board member of the Computer Science Department Conference (2014-2016) Managing Director of the Institute for Business Application Systems since 2011 Practical Affairs Representative for Business Informatics since 2009 Professor Johannsen's research spans system development and integration, business application systems, and value-oriented corporate management with particular focus on telecommunications and energy supply industries. His recent work emphasizes IT-Governance, Risk and Compliance Management (IT-GRC) for small and medium enterprises, sustainable logistics solutions using machine learning, and security challenges in digital cooperation. His publication pattern reveals consistent contributions across multiple domains with recent emphasis on: ERP system implementation methodologies and evaluation IT security frameworks for resource-constrained organizations Machine learning applications for sustainable logistics optimization Cloud computing and cooperative business models for SMEs API security and IoT security vulnerabilities Digital sovereignty concerns in business contexts Professional Contributions Professor Johannsen has led numerous research projects including the development of the reference model 'Service- and Cloud-Oriented Architectures for Storage Management' (DICAS) with Berliner Verkehrsbetriebe (BVG) in 2017, Business Process Management implementation with Brandenburg's Central IT Service Provider (2013-2014), and multiple studies on ERP system performance in various business contexts. Teaching and Academic Leadership He has taught a wide range of courses including Information Management, ERP Reporting, Project and Risk Management, and Value-Oriented IT Management. His teaching approach integrates theoretical foundations with practical applications, drawing from his extensive industry experience. He has served in various academic leadership roles including program director for Business Informatics master's and bachelor's programs and as a member of the department council. Research Infrastructure Professor Johannsen leads the 'Process Integration and ERP Systems' competence field which maintains ERP laboratories at FH Brandenburg featuring various ERP installations, particularly SAP and Microsoft systems. This infrastructure supports hands-on teaching and applied research on enterprise systems implementation and integration.

Yue Chenمشاهده پروفایل

استاد

• Wireless Networks
• Cognitive and Cooperative Networking
• HetNet (Heterogeneous Networks)
• +۳ مورد دیگر

Professor Yue Chen is a distinguished academic at the School of Electronic Engineering and Computer Science , Queen Mary University of London , holding the title of Professor of Telecommunications Engineering and serving as Director of Education . With expertise in wireless networking and smart energy systems, his research bridges theoretical innovation with practical applications in telecommunications infrastructure. BEng, MEng, PhD Member of Institution of Engineering and Technology (MIET) Senior Member of IEEE (SMIEEE) His research interests focus on Intelligent Radio Resource Management for wireless networks, cognitive and cooperative networking, heterogeneous networks (HetNet), smart energy systems, and Internet of Things (IoT) integration. His work emphasizes machine learning-driven optimization for next-generation communication systems and energy-efficient networks. Recent publications highlight trends in reinforcement learning for UAV-NOMA networks , energy-efficient IoT systems , and data-driven educational methodologies . These demonstrate cross-disciplinary innovation, merging telecommunications research with pedagogical experimentation and smart grid optimization.

Karl Norrmanمشاهده پروفایل

پژوهشگر

• Cryptography
• Formal Methods
• Network Security
• +۴ مورد دیگر

Karl Norrman is an Industry doctoral student and Researcher at the Department of Theoretical Computer Science (TCS) at KTH Royal Institute of Technology, concurrently working as a Security Researcher at Ericsson Research since 2001. His academic appointment at KTH is part-time (20% time allocation), while he spends the majority of his time (80%) at Ericsson, where he holds the formal title of Expert Mobile Network Security. He is supervised by Professor Mads Dam for his doctoral studies and receives partial research funding from the Wallenberg AI, Autonomous Systems and Software Program (WASP). His educational background includes: PhD candidate in Computer Science at KTH Royal Institute of Technology, Department of Theoretical Computer Science (ongoing). Research focuses on formal modeling and proofs for cryptographic protocols using pen-and-paper proofs and mechanized proof-support tools such as Tamarin and EasyCrypt. Master's degree in Computer Science from Stockholm University, Department of Mathematics (2001). Thesis: "RTP Security in 3G Networks." During this work, he contributed to the development of the Secure Real-time Transport Protocol (SRTP), standardized in IETF as RFC 3711. Norrman's research centers on formal methods for security protocol verification , with particular expertise in cryptographic protocol analysis, modeling, and mechanized proof techniques. His work bridges theoretical computer science and practical security applications, focusing on making formal verification tools accessible for industrial adoption. Key research areas include 5G/6G security architectures, privacy-preserving mechanisms for mobile networks, authentication and key agreement protocols, and software security. He advocates for "goal oriented and motivated security designs" that balance theoretical rigor with practical implementation constraints while specializing in translating complex security requirements into implementable solutions for telecommunications infrastructure. Analysis of Norrman's publication history reveals a consistent evolution from foundational work on SRTP (2002-2007) through LTE security analysis (2014-2015) to pioneering 5G security research (2016-2020) and now 6G security exploration (2024). His work demonstrates methodological progression from analyzing existing protocols to designing novel security mechanisms and developing verification frameworks like OpenSAW. A distinctive pattern is his focus on industrial applicability —ensuring theoretical security models translate to real-world implementations, particularly evident in his work on USIM-compatible protocols and error-correcting authentication for noisy wireless channels. Recent publications increasingly address cross-domain challenges like secure federated learning in mobile networks, reflecting the expanding scope of telecommunications security. Professional engagement: Reviewer for ACM CCS 2023, EURO S&P 2023, ACM CCS 2022, NordSec 2022, Vietcrypt 2006, IEEE Telecommunications Journal Active contributor to 3GPP security standardization processes Co-author on multiple Ericsson whitepapers shaping industry security practices Norrman maintains a unique dual affiliation that enables direct translation of academic research into industrial security solutions. At KTH, he contributes to the Theoretical Computer Science group's formal methods research, while at Ericsson he applies these techniques to real-world security challenges in mobile network development. His work on OpenSAW exemplifies this bridge between academia and industry, creating practical tools for automated security testing of component-based software systems. This position allows him to identify emerging security challenges in next-generation networks while maintaining theoretical rigor in his approach.

• Automating Design and Diagnosis of Information Systems
• Computer Graphics
• Web Technologies

Konstantin Nikolaevich Kasyan serves as Associate Professor at the Department of Computer Systems and Networks within the Faculty of Computer Science and Technologies at Zaporizhzhia National Technical University, where he has maintained academic activity since 1998. He graduated with honors from Zaporizhzhia Machine-Building Institute's Faculty of Electronic Engineering in 1993, specializing in Radio Engineering with qualification as Radio Engineer. His Candidate of Sciences degree (defended 1998/1999) established his expertise in diagnostic methodologies for electronic systems. His research spans three core domains: automating design and diagnosis of information systems, computer graphics methodologies, and web technologies. This interdisciplinary focus manifests in practical applications ranging from hardware diagnostics to smart home systems. His work demonstrates consistent evolution from foundational electronics reliability research in the 1990s toward contemporary IoT and computer vision applications. His publication trajectory reveals distinct chronological phases: 1990s-2000s concentrated on electro-radio diagnostics and reliability engineering; 2000s-2010s expanded into computer graphics and text recognition; while 2010s-2021 shifted toward IoT integration, smart home technologies, and machine learning applications. This progression reflects both technological advancements and his adaptability across computing subfields. Kasyan teaches modern Internet technologies, computer graphics, computer systems design, and computational methods in scientific research, directly translating his research into pedagogical practice. His academic presence is maintained through Scopus, Web of Science, Google Scholar, and ORCID profiles, indicating active scholarly engagement despite the absence of formal awards or documented grants in available records.

Nejat YUMUŞAKمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Bioinformatics
• +۵ مورد دیگر

Prof. Nejat YUMUŞAK is a full Professor in the Department of Computer Engineering at Sakarya University's Faculty of Computer and Information Sciences, where he has built his academic career since 1995. His progression includes roles as Research Assistant (1993-1998), Assistant Professor (1998-2004), Associate Professor (2005-2011), and Professor (2011-present). Education PhD in Electrical-Electronics Engineering, Sakarya University (1995-1998) Thesis: Analysis of Power System Circuit Elements Using Artificial Neural Networks MSc in Electrical-Electronics Engineering, Dumlupinar University (1994-1995) Thesis: Calculation and Measurement of Transformer Parameters at High Frequencies BSc in Electrical-Electronics Engineering, Istanbul Technical University (1989-1993) Research Focus Prof. YUMUŞAK's research integrates artificial intelligence with multidisciplinary applications. Primary domains include: Bioinformatics & Medical AI : Developing deep learning models for COVID-19 mutation prediction, leukemia classification via blood smear analysis, and gastrointestinal anomaly detection using endoscopic data. Signal Processing & Security : Advancing acoustic event detection for security systems and vulnerability testing through intelligent fuzzing techniques. Optimization & Industrial Applications : Creating metaheuristic algorithms (e.g., enhanced Wild Horse Optimizer) for energy efficiency and Industry 4.0 digitalization. Publication Trends His recent articles (2022-2025) demonstrate strong emphasis on transformer architectures for virology, ensemble methods for medical diagnostics, and CNN/LSTM networks for genomic and acoustic data analysis. Over 50% of recent works focus on healthcare applications, particularly cancer and pandemic-related prediction models. Contact & Recognition Contact via nyumusak@sakarya.edu.tr or phone (0264) 264 58 94. His work has received 793 citations (Web of Science) with an H-index of 14.