Samyar Sarraf | Engineering | Young Innovator Award

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Dr. Samyar Sarraf | Engineering | Young Innovator Award

Lab Assistant | Sharif University of Technology | Iran

Dr. Samyar Sarraf is a Ph.D. graduate in Mechanical Engineering from Sharif University of Technology, with recognized expertise spanning offshore and marine engineering, civil engineering, and applied hydrodynamics. His research focuses on experimental and numerical investigation of squat submarine hydrodynamic performance and ship–submarine interactions, with multiple peer-reviewed publications in the high-impact journal Ocean Engineering. He has authored several scholarly works, accumulating 16 citations and an h-index of 2, reflecting a growing research influence. In addition to marine hydrodynamics, his interdisciplinary contributions include innovative solutions in geotechnical and earthquake engineering, such as the development of an underground earthquake isolation system and advanced dynamic soil modeling methods. His work demonstrates strong experimental rigor, numerical proficiency, and collaborative engagement with multidisciplinary research teams, offering practical societal impact in maritime safety, offshore operations, and resilient infrastructure design at an international level.

Citation Metrics (Scopus)

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16

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Featured Publications

Yao Ni | Engineering | Editorial Board Member

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Dr. Yao Ni | Engineering | Editorial Board Member

Researcher | Guangdong University of Technology | China

Dr. Ni Yao is a distinguished researcher at the Guangdong University of Technology, Guangzhou, China, widely recognized for his contributions to advanced materials, neuromorphic engineering, and intelligent sensing–processing systems. With an interdisciplinary focus spanning materials science, flexible electronics, artificial intelligence hardware, and intelligent control mechanisms, his research advances next-generation photonic synaptic transistors, in-sensor reservoir computing architectures, and flexible neuromorphic devices capable of multidimensional shape morphing. Dr. Yao has authored 65 peer-reviewed publications, achieved 1,679 citations, and maintains an h-index of 23, reflecting the depth, continuity, and global influence of his scholarly work. His recent high-impact contributions include crystallized conjugated polymer-based photonic synaptic transistors, paper-based perovskite artificial neuromorphic retinas, free shape-morphing neuromorphic devices published in Nature Communications, as well as novel methodologies for industrial control deadlock avoidance, frequency-aware transformers for pipeline leak detection, and symmetric optimization models for delivery duration forecasting. Engaging in collaborations with over 160 co-authors, Dr. Yao actively contributes to multidisciplinary research communities, promoting scientific advancement across materials innovation, industrial automation, computational sensing, and AI-driven systems engineering. His work delivers broad societal impact by enabling energy-efficient intelligent devices, enhancing autonomous perception capabilities, and driving innovations that support safer, more sustainable, and technologically advanced industrial ecosystems. Through continuous innovation, rigorous scholarship, and extensive international collaboration, Dr. Ni Yao remains at the forefront of shaping future directions in intelligent materials, neuromorphic computing, and integrated sensing technologies.

Profiles: Scopus | ORCID | ResearchGate

Featured Publications

1. Wei, H., Yang, J., Fu, C., Li, Z., Ni, Y., Wang, B., He, B., Jiang, S., & He, G. (2025). ALD-driven ultra-thin ZnO channels for flexible electrolytic neuromorphic devices. IEEE Electron Device Letters.

2. Ni, Y., Zhang, Y., Lin, J., Liu, X., Yu, Y., Liu, L., Zhong, W., Chen, Y., Chen, R., Kwok, H. S., et al. (2025). Transistor-structured artificial dendrites for spatiotemporally correlated reservoir computing. IEEE Electron Device Letters.

3. Guan, X., Wu, W., & Ni, Y. (2025). A novel methodology to deadlock analysis and avoidance for automatic control systems based on Petri Net. Processes, 13(10).

4. Chen, M., Lu, Y., Wu, W., Ye, Y., Wei, B., & Ni, Y. (2025). Multi-scale frequency-aware transformer for pipeline leak detection using acoustic signals. Sensors, 25(20).

5. Ji, Z., Liu, J., He, Y., Yang, H., Zhang, L., Guan, S., Ni, Y., & Wu, T. (2025). Stretchable synaptic device with photonic–electric dual mode for sign language recognition. Advanced Materials Technologies

Farouk Zouari | Engineering | Editorial Board Member

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Assist. Prof. Dr. Farouk Zouari | Engineering | Editorial Board Member

Ecole Nationale d’Ingénieurs de Tunis | Tunisia

Dr. Farouk Zouari is a distinguished researcher at Université de Tunis El Manar, Tunisia, known for his significant contributions to control systems engineering and intelligent autonomous technologies. His research encompasses neural network–based adaptive control, nonlinear optimal control, MIMO systems, time-varying delay systems, and finite-time fuzzy synchronization of fractional-order and chaotic systems, with a strong focus on bridging theoretical advancements and real-world applications in automation, robotics, and intelligent transportation. Over his career, Dr. Zouari has produced 37 peer-reviewed publications and established a solid scholarly presence supported by 735 citations and an h-index of 17, indicating substantial impact and sustained relevance in his field. His recent works spanning robust adaptive output feedback control for time-delay MIMO systems, optimal control strategies for multi-axle autonomous vehicles, and chattering-free synchronization methods demonstrate his commitment to addressing emerging engineering challenges. With collaborations involving 30 co-authors, Dr. Zouari actively contributes to interdisciplinary progress, fostering innovation across global research communities. His work continues to support the advancement of intelligent control methodologies and their integration into next-generation dynamic and autonomous systems, contributing to both technological development and societal benefit.

Profiles: Google Scholar | Scopus | ORCID

Featured Publications

1. Zouari, F., Ibeas, A., Boulkroune, A., Cao, J., & Arefi, M. M. (2018). Adaptive neural output-feedback control for nonstrict-feedback time-delay fractional-order systems with output constraints and actuator nonlinearities. Neural Networks, 105, 256–276. Cited by: 82

2. Zouari, F., Ibeas, A., Boulkroune, A., Cao, J., & Arefi, M. M. (2021). Neural network controller design for fractional-order systems with input nonlinearities and asymmetric time-varying pseudo-state constraints. Chaos, Solitons & Fractals, 144, Article 110742. Cited by: 65

3. Boubellouta, A., Zouari, F., & Boulkroune, A. (2019). Intelligent fuzzy controller for chaos synchronization of uncertain fractional-order chaotic systems with input nonlinearities. International Journal of General Systems, 48(3), 211–234. Cited by: 65

4. Zouari, F., Boulkroune, A., & Ibeas, A. (2017). Neural adaptive quantized output-feedback control-based synchronization of uncertain time-delay incommensurate fractional-order chaotic systems with input nonlinearities. Neurocomputing, 237, 200–225. Cited by: 64

5. Zouari, F., Ibeas, A., Boulkroune, A., Cao, J., & Arefi, M. M. (2019). Neuro-adaptive tracking control of non-integer order systems with input nonlinearities and time-varying output constraints. Information Sciences, 485, 170–199. Cited by: 56

Genfeng Liu | Engineering | Best Researcher Award

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Dr. Genfeng Liu | Engineering | Best Researcher Award

Research Scholar at Henan University of Technology, China

Genfeng Liu is a highly qualified candidate for the Best Researcher Award, with a strong background in control science and engineering, specializing in data-driven control, adaptive control, and fault-tolerant systems. His research spans intelligent transportation, multiagent systems, and nonlinear systems, contributing to high-impact IEEE journals such as IEEE Transactions on Cybernetics (IF: 19.118) and IEEE Transactions on Neural Networks and Learning Systems (IF: 14.255). As a reviewer for leading journals, he holds strong academic credibility. His work on model-free adaptive control and cybersecurity applications demonstrates real-world relevance. To enhance his profile, he could expand international collaborations, increase industry applications, and lead large-scale research projects. While his contributions are highly significant, further engagement in technology transfer and interdisciplinary research would strengthen his impact. Overall, his extensive publication record and research influence make him a strong contender for the award, with potential for even greater contributions in the future.

Professional Profile

Education

Genfeng Liu received his Ph.D. in Control Science and Engineering from Beijing Jiaotong University, China, in 2021. His doctoral research focused on advanced control methodologies, including data-driven control, iterative learning control, and fault-tolerant control, which have significant applications in intelligent transportation and nonlinear systems. Throughout his academic journey, he developed expertise in adaptive control and multiagent systems, contributing to cutting-edge research in automation and cybernetics. His education provided a strong foundation in both theoretical and applied control engineering, enabling him to publish in prestigious IEEE journals. Additionally, his academic background equipped him with the analytical and problem-solving skills necessary to address complex challenges in system automation and intelligent control. His commitment to continuous learning and research excellence is evident in his contributions to high-impact scientific literature and his role as a reviewer for renowned international journals, solidifying his reputation as an expert in his field.

Professional Experience

Genfeng Liu is currently a Lecturer at the College of Electrical Engineering, Henan University of Technology, Zhengzhou, China. His professional experience revolves around advanced control engineering, with a focus on data-driven control, adaptive control, and fault-tolerant systems. As a researcher, he has made significant contributions to intelligent transportation systems, multiagent systems, and nonlinear control, publishing extensively in high-impact IEEE journals. Beyond his research, he actively participates in academic peer review for prestigious journals such as IEEE Transactions on Cybernetics and IEEE Transactions on Intelligent Vehicles, reinforcing his role as a respected scholar in the field. His expertise extends to supervising students and collaborating on interdisciplinary projects, bridging the gap between theoretical advancements and practical applications. His ongoing work in model-free adaptive control and cybersecurity-related control mechanisms further strengthens his impact in academia and industry, positioning him as a leader in modern control systems and intelligent automation research.

Research Interest

Genfeng Liu’s research interests lie in advanced control engineering, with a strong focus on data-driven control, adaptive control, and fault-tolerant control. His work explores iterative learning control and model-free adaptive control techniques, particularly in applications related to intelligent transportation systems, nonlinear systems, and multiagent systems. He is also interested in cybersecurity aspects of control systems, such as defense mechanisms against false data injection attacks. His research aims to enhance the efficiency, safety, and reliability of automation in modern transportation and industrial systems. By integrating artificial intelligence with control theory, he seeks to develop innovative solutions for complex, real-world engineering challenges. His studies have been published in top-tier journals, reflecting his commitment to advancing theoretical and applied knowledge in control science. Additionally, his expertise in intelligent transportation and system optimization continues to drive impactful contributions to the fields of automation, cybernetics, and industrial informatics.

Award and Honor

Genfeng Liu has received several accolades and recognition for his outstanding contributions to the field of control science and engineering. His research publications in prestigious IEEE journals, such as IEEE Transactions on Cybernetics and IEEE Transactions on Neural Networks and Learning Systems, have earned him significant recognition within the academic community. As an active reviewer for renowned international journals, he has been acknowledged for his critical evaluations and contributions to the peer-review process. His innovative work in data-driven control, adaptive control, and fault-tolerant systems has positioned him as a leading researcher in intelligent transportation and nonlinear systems. Additionally, his participation in high-profile conferences and collaborations with esteemed researchers further highlight his impact in the field. While his research achievements are commendable, pursuing national and international research grants and awards would further enhance his recognition and establish him as a distinguished leader in control engineering and automation.

Research Skill

Genfeng Liu possesses strong research skills in advanced control engineering, specializing in data-driven control, adaptive control, and fault-tolerant control. He is proficient in developing and implementing iterative learning control and model-free adaptive control strategies for complex nonlinear and multiagent systems. His expertise extends to intelligent transportation systems, where he applies innovative control techniques to enhance automation and safety. He is highly skilled in mathematical modeling, algorithm development, and system optimization, enabling him to solve real-world engineering challenges effectively. His ability to conduct in-depth theoretical analysis and translate findings into practical applications is evident in his numerous high-impact publications in top-tier IEEE journals. Additionally, his experience as a reviewer for prestigious academic journals demonstrates his critical thinking and analytical skills. His research capabilities, combined with his ability to collaborate on interdisciplinary projects, make him a valuable contributor to the fields of cybernetics, automation, and industrial informatics.

Conclusion

Genfeng Liu is a highly suitable candidate for the Best Researcher Award due to his exceptional research output, high-impact publications, and contributions to control engineering and intelligent transportation systems. To further strengthen his candidacy, increasing international collaborations, practical industry applications, and leadership roles in large-scale projects would make his research even more impactful.

Publications Top Noted

  • Title: Improved Model-Free Adaptive Predictive Control for Nonlinear Systems with Quantization Under Denial of Service Attacks
    Authors: Genfeng Liu, Jinbao Zhu, Yule Wang, Yangyang Wang
    Year: 2025
    Citation: DOI: 10.3390/sym17030471

  • Title: Adaptive Iterative Learning Fault-Tolerant Control for State Constrained Nonlinear Systems With Randomly Varying Iteration Lengths
    Authors: Genfeng Liu, Zhongsheng Hou
    Year: 2024
    Citation: DOI: 10.1109/TNNLS.2022.3185080

  • Title: Cooperative Adaptive Iterative Learning Fault-Tolerant Control Scheme for Multiple Subway Trains
    Authors: Genfeng Liu, Zhongsheng Hou
    Year: 2022
    Citation: DOI: 10.1109/TCYB.2020.2986006

  • Title: RBFNN-Based Adaptive Iterative Learning Fault-Tolerant Control for Subway Trains With Actuator Faults and Speed Constraint
    Authors: Genfeng Liu, Zhongsheng Hou
    Year: 2021
    Citation: DOI: 10.1109/TSMC.2019.2957299

  • Title: Adaptive Iterative Learning Control for Subway Trains Using Multiple-Point-Mass Dynamic Model Under Speed Constraint
    Authors: Genfeng Liu, Zhongsheng Hou
    Year: 2021
    Citation: DOI: 10.1109/TITS.2020.2970000

  • Title: A Model-Free Adaptive Scheme for Integrated Control of Civil Aircraft Trajectory and Attitude
    Authors: Gaoyang Jiang, Genfeng Liu, Hansong Yu
    Year: 2021
    Citation: DOI: 10.3390/sym13020347

  • Title: A Data-Driven Distributed Adaptive Control Approach for Nonlinear Multi-Agent Systems
    Authors: Xian Yu, Shangtai Jin, Genfeng Liu, Ting Lei, Ye Ren
    Year: 2020
    Citation: DOI: 10.1109/ACCESS.2020.3038629

  • Title: Model-Free Adaptive Direct Torque Control for the Speed Regulation of Asynchronous Motors
    Authors: Ziwei Zhang, Shangtai Jin, Genfeng Liu, Zhongsheng Hou, Jianmin Zheng
    Year: 2020
    Citation: DOI: 10.3390/pr8030333

Anuj Kumar | Engineering | Best Researcher Award

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Mr. Anuj Kumar | Engineering | Best Researcher Award

Assistant Professor at Management Education & Research Institute, Janakpuri, India

Anuj Kumar is an accomplished academic and researcher in Computer Science & Engineering, currently pursuing a Ph.D. in Image Processing at AKTU, Lucknow. With over a decade of teaching experience at institutions like Guru Gobind Singh Indraprastha University and IIMT College of Engineering, he has significantly contributed to education and research. His expertise spans artificial intelligence, computer graphics, and data structures, complemented by proficiency in programming languages such as Python, C++, and MATLAB. He has published research papers in Scopus-indexed journals, IEEE Explorer, and Elsevier, along with a book chapter on distributed artificial intelligence. Recognized for his contributions, he was awarded at the Smart India Hackathon 2018 and qualified GATE 2012 with an 85.04 percentile. Anuj is actively involved in academic leadership, faculty development, and university assessments. With a commitment to innovation and interdisciplinary research, he aspires to advance computational methodologies and industrial applications in artificial intelligence and image processing.

Professional Profile 

Education

Anuj Kumar has a strong academic background in Computer Science & Engineering. He is currently pursuing a Ph.D. in Image Processing from Dr. A.P.J. Abdul Kalam Technical University (AKTU), Lucknow, Uttar Pradesh, demonstrating his commitment to advanced research. He earned his M.Tech in Computer Science & Engineering from Guru Gobind Singh Indraprastha University, Delhi, in 2014, securing a first division. His undergraduate studies include a B.Tech in Computer Science & Engineering from the Institution of Electronics & Telecommunication Engineers (IETE), Delhi, in 2011, also with first-division honors. Additionally, he holds a Three-Year Diploma in Computer Science & Engineering from IETE, Delhi (2006). His early education was completed under the U.P. Board, where he finished 10th grade (2000) and 12th grade (2003) in the second division. His educational journey, enriched with technical certifications like MCAD (Microsoft Certified Application Developer) in 2006, has laid a strong foundation for his expertise in computing and research.

Professional Experience

Anuj Kumar has extensive academic experience as an Assistant Professor in Computer Science & Engineering, with a teaching career spanning over a decade across prestigious institutions. Since July 2023, he has been serving at MERI College of Engineering and Technology, Haryana. Prior to this, he worked at IIMT College of Engineering, Greater Noida (2022–2023) and Greater Noida Institute of Technology, GGSIPU (2018–2022), where he contributed to curriculum development and research initiatives. He also held academic positions at USIC&T, Guru Gobind Singh Indraprastha University (2017–2018) and Ram-Eesh Institute of Engineering & Technology (2017). Earlier in his career, he served at Baba Saheb Ambedkar Institute of Technology & Management (2014–2016) and The Institution of Electronics & Telecommunication Engineers, Delhi (2011–2012). His vast experience includes mentoring students, conducting faculty development programs, and leading academic audits, showcasing his commitment to education, research, and institutional development.

Research Interest

Anuj Kumar’s research interests lie at the intersection of computer vision, image processing, artificial intelligence, and computational methods. Currently pursuing a Ph.D. in Image Processing, he focuses on developing advanced techniques for image enhancement, noise removal, and forgery detection using deep learning algorithms. His expertise extends to computer graphics, formal language automata, database management systems (DBMS), data structures, and discrete mathematics, which serve as the foundation for his research innovations. He has actively contributed to AI-driven industrial systems, biodiversity assessment using hyperspectral imaging, and disruptive innovations in tech-business analytics. His work has been published in Scopus-indexed journals, IEEE conference proceedings, and reputed international journals, reflecting the impact of his research. Additionally, he explores the applications of distributed artificial intelligence (DAI) for document retrieval, emphasizing intelligent data processing techniques. His dedication to cutting-edge research strengthens his role as a mentor and academician in the field of computer science and engineering.

Award and Honor

Anuj Kumar has been recognized for his academic excellence and research contributions through various awards and honors. He was awarded in the Smart India Hackathon 2018, a prestigious national-level competition promoting innovation and problem-solving skills. Demonstrating strong technical acumen, he qualified GATE 2012 with an impressive 85.04 percentile and a score of 302, showcasing his expertise in computer science and engineering. His achievements extend beyond academics, as he was the runner-up in the 100m race at IETE, New Delhi, in 2005, highlighting his diverse talents. Additionally, he has played a significant role in academia as a convener of the Joint Assessment Committee (JAC) for academic audits, deputy center superintendent for examinations, and university representative in various assessment programs. His dedication to research and education is further reflected in his memberships on editorial boards and professional organizations, solidifying his reputation as a distinguished academic and researcher.

Research Skill

Anuj Kumar possesses a strong research skillset that spans multiple domains within computer science and engineering, particularly in image processing, artificial intelligence, and computational methods. His expertise in deep learning, fuzzy techniques, and hyperspectral imaging enables him to develop innovative solutions for image enhancement, noise removal, and forgery detection. He is proficient in Python, MATLAB, C++, and various database management systems (DBMS), which support his research in data analysis, automation, and intelligent computing. His ability to critically analyze complex problems, design experiments, and implement advanced algorithms has led to multiple Scopus-indexed publications, IEEE conference presentations, and book chapters. Additionally, his role in academic audits, faculty development programs, and technical training workshops demonstrates his leadership in research and education. His strong analytical thinking, problem-solving capabilities, and hands-on approach to emerging technologies make him a highly skilled researcher in the field of computer vision and artificial intelligence.

Conclusion

Anuj Kumar has a strong academic foundation, technical expertise, and a growing research portfolio in computer science and engineering. His contributions to image processing, artificial intelligence, and industrial automation position him as a promising candidate for the Best Researcher Award. However, enhancing high-impact publications, research collaborations, and funding contributions would further strengthen his profile for this recognition.

Publications Top Noted

  • P., Jaidka, Preeti, P., Upadhyay, Prashant, A., Kumar, Aman, A.S., Kumar, Anuj Shiva, S.P., Yadav, Satya Prakash (2024). Transforming Coconut Farming with Deep Learning Disease Detection. Evergreen. Citations: 0

  • D., Sharma, Deepak, A.S., Kumar, Anuj Shiva, N., Tyagi, Nitin, S.S., Chavan, Sunil S., S.M.P., Gangadharan, Syam Machinathu Parambil (2024). Towards intelligent industrial systems: A comprehensive survey of sensor fusion techniques in IIoT. Measurement: Sensors. Citations: 3

  • S., Singh, Sandeep, B.K., Singh, B. K., A.S., Kumar, Anuj Shiva (2024). Multi-organ segmentation of organ-at-risk (OAR’s) of head and neck site using ensemble learning technique. Radiography. Citations: 3

  • R., Naz, Rahat, A.S., Kumar, Anuj Shiva (2024). Surveying Quantum-Proof Blockchain Security: The Era of Exotic Signatures. Conference Paper. Citations: 1

 

Miroslav Kelemen | Engineering | Best Researcher Award

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Prof. Dr. Miroslav Kelemen | Engineering | Best Researcher Award

Vice-Rector for Education at TECHNICAL UNIVERSITY OF KOSICE, FACULTY OF AERONAUTICS , Slovakia

Miroslav Kelemen is an experienced aviation professional with over 22 years of expertise as a pilot, flight instructor, and air traffic controller. With a solid background in managerial roles, including his time as an Air Force Base Commander, Kelemen has developed a deep understanding of aviation education, flight training, aeronautical engineering, and air transport systems. His research interests encompass interdisciplinary topics such as decision-making processes, risk assessment, human performance, and safety in transportation. He has also contributed to studies on the impact of aviation activities on the environment and health, small and medium enterprises in transport and tourism, and innovations in aviation education. Kelemen holds key academic positions, including Vice-Rector for Education at the Technical University of Košice, where he continues to shape the future of aviation education.

Professional Profile

Education

Kelemen’s educational journey is distinguished by numerous advanced degrees and specialized training. He holds a DrSc. from Slovenská komisia pre vedecké hodnosti, Bratislava, and a Ph.D. from the Air Force Academy Košice in flight training. Additionally, Kelemen obtained his Associate Professorship at the University of Žilina, Slovakia. His academic qualifications are complemented by his professorship at the Academy of the Police Force in Bratislava, focusing on public administration and crisis management. His rigorous education laid the foundation for his multifaceted expertise in aviation, air transport, and safety, influencing both academic curricula and industry standards.

Professional Experience

Kelemen’s professional experience spans across various roles in aviation and academia. Since 2018, he has served as a Professor at the Faculty of Aeronautics, Technical University of Košice, where he specializes in flight training. In August 2023, he became the Vice-Rector for Education at the university, overseeing educational reforms and initiatives. Kelemen’s previous leadership role as an Air Force Base Commander allowed him to hone his managerial skills in high-pressure environments. His career also includes significant work in air traffic control, aviation safety, and flight training, contributing to both military and civil aviation sectors.

Research Interests

Miroslav Kelemen’s research interests are broad and interdisciplinary, with a strong focus on aviation education, flight training, and air transport systems. His work delves into decision-making processes, risk assessment, and human performance in transportation, particularly in aviation. He is deeply invested in understanding the environmental and health impacts of aviation activities, exploring sustainable practices and innovations in aviation. Kelemen also studies small and medium enterprises in transport, logistics, and tourism, with an emphasis on their role in economic development. His research is grounded in applying advanced methodologies, including fuzzy decision support models and artificial intelligence, to address complex challenges in aviation and related fields. Through these studies, Kelemen contributes to the improvement of aviation safety, security, and overall operational efficiency.

Awards and Honors

Throughout his career, Miroslav Kelemen has received numerous accolades for his academic and professional contributions to aviation and transport. He has been recognized for his pioneering work in flight training, risk assessment, and aviation education, earning him a reputation as a leader in these fields. His involvement in interdisciplinary research has garnered recognition from various academic and industry bodies. Kelemen’s achievements extend beyond the classroom, with contributions to publications in respected journals and books, further solidifying his influence in academia. His expertise in aviation safety and the impact of aviation on human health and the environment has earned him prestigious awards and honors, reflecting his commitment to advancing both the academic and practical aspects of aviation.

Publications Top Noted

  • A fuzzy model of risk assessment for environmental start-up projects in the air transport sector
    Authors: V. Polishchuk, M. Kelemen, B. Gavurová, C. Varotsos, R. Andoga, M. Gera, …
    Year: 2019
    Citation Count: 76
  • Fuzzy model for quantitative assessment of environmental start-up projects in air transport
    Authors: M. Kelemen, V. Polishchuk, B. Gavurová, S. Szabo, R. Rozenberg, M. Gera, …
    Year: 2019
    Citation Count: 67
  • Expert model of risk assessment for the selected components of smart city concept: From safe time to pandemics as COVID-19
    Authors: B. Gavurova, M. Kelemen, V. Polishchuk
    Year: 2022
    Citation Count: 59
  • The suitability of UAS for mass movement monitoring caused by Torrential Rainfall—A study on the Talus Cones in the Alpine Terrain in High Tatras, Slovakia
    Authors: R. Urban, M. Štroner, P. Blistan, Ľ. Kovanič, M. Patera, S. Jacko, I. Ďuriška, …
    Year: 2019
    Citation Count: 53
  • Monitoring of low-level wind shear by ground-based 3D lidar for increased flight safety, protection of human lives and health
    Authors: P. Nechaj, L. Gaál, J. Bartok, O. Vorobyeva, M. Gera, M. Kelemen, …
    Year: 2019
    Citation Count: 46
  • Patterns of interdependence between financial development, fiscal instruments, and environmental degradation in developed and converging EU countries
    Authors: M. Zioło, K. Kluza, J. Kozuba, M. Kelemen, P. Niedzielski, P. Zinczak
    Year: 2020
    Citation Count: 36
  • Technology improving safety of crowdfunding platforms functioning in the context of the protection of the start-up investors in the financial and transport sectors
    Authors: V. Polishchuk, M. Kelemen, J. Kozuba
    Year: 2019
    Citation Count: 30
  • Enhancing of security on critical accident locations using telematics support
    Authors: R. Dvorak, Z. Cekerevac, Z. Kelemen, M. Sousek
    Year: 2010
    Citation Count: 30
  • Security Management Education and Training of Critical Infrastructure Sectors’ Experts
    Authors: M. Kelemen, J. Jevčák
    Year: 2018
    Citation Count: 29
  • Assessing the contribution of data mining methods to avoid aircraft run-off from the runway to increase the safety and reduce the negative environmental impacts
    Authors: O. Vorobyeva, J. Bartok, P. Šišan, P. Nechaj, M. Gera, M. Kelemen, …
    Year: 2020
    Citation Count: 28

Tharindu Madhushanka | Engineering | Best Researcher Award

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Mr. Tharindu Madhushanka | Engineering | Best Researcher Award

Engineer at Browns Engineering and Construction, Sri Lanka

Mr. Tharindu Indunil Madhushanka is a promising researcher and civil engineering professional from the University of Moratuwa, Sri Lanka. He holds a Master of Science in Civil Engineering, with a focus on using artificial intelligence for flood forecasting, specifically in the Polonnaruwa region. His research integrates machine learning techniques such as LSTM, ANN, and Transformer models to predict water levels using meteorological and hydrological data. Tharindu has also contributed to sustainable construction through his undergraduate research on the thermal performance and embodied energy of precast panel buildings. His academic achievements include a GPA of 3.54 in Civil Engineering and notable publications, including a paper in the Journal of Hydrologic Engineering. He has gained hands-on experience in both teaching and industry, having worked as an instructor and research assistant at the University of Moratuwa and a trainee civil engineer. Tharindu is dedicated to advancing AI applications in civil engineering for disaster management and sustainability.

Professional Profile

Education

Mr. Tharindu Indunil Madhushanka has a strong educational background in civil engineering, having completed his Bachelor of Science in Civil Engineering (Honors) from the University of Moratuwa, Sri Lanka, where he graduated with a second-class upper division and a GPA of 3.54 out of 4.2. His undergraduate studies provided him with a solid foundation in engineering principles and practices. He further pursued a Master of Science at the same university, beginning in November 2022, with a research focus on utilizing artificial intelligence to forecast floods, particularly in the Polonnaruwa region of Sri Lanka. Under the guidance of Prof. M.T.R. Jayasinghe, his postgraduate research aims to develop machine learning models for predicting water levels using meteorological and hydrological data. This interdisciplinary approach bridges civil engineering and AI, reflecting his commitment to advancing both fields. His studies are set to culminate in July 2024, contributing valuable insights to flood risk management.

Professional Experience

Mr. Tharindu Indunil Madhushanka has gained valuable professional experience through both academic and industry roles. As a research assistant at the Department of Civil Engineering, University of Moratuwa, he contributed to various engineering modules, including Mechanics, Structural Mechanics, and the Design of Large Structures. His responsibilities included assisting in teaching and providing support for courses such as Building Construction & Materials and Design of Masonry and Timber Structures. Additionally, Tharindu worked as an instructor in the Department of Computer Science Engineering, teaching Programming Fundamentals from June to September 2024. His industry experience includes serving as a trainee civil engineer at RR Construction (Pvt) Ltd, where he was involved in significant projects such as the Mahaweli Water Security Investment Program. These projects, including the Minipe Left Bank Canal Rehabilitation and North-Western Province Canal Project, provided him with hands-on experience in large-scale civil engineering works, enhancing his practical skills.

Research Interest

Mr. Tharindu Indunil Madhushanka’s research interests lie at the intersection of civil engineering and artificial intelligence, with a focus on disaster risk management and sustainable construction. His primary research area is the use of machine learning techniques, particularly deep learning models like LSTM, ANN, and Transformer, to forecast floods and predict water levels in flood-prone regions, such as Polonnaruwa, Sri Lanka. By utilizing meteorological and hydrological data, Tharindu aims to enhance flood prediction systems, providing valuable insights for mitigating the impacts of natural disasters. Additionally, he is interested in sustainable building practices, as demonstrated by his undergraduate research on the thermal performance and embodied energy of precast panel buildings. Tharindu’s work seeks to improve the environmental efficiency of construction materials and methods, making buildings more energy-efficient over their life cycles. His research reflects his commitment to advancing both AI applications and sustainability within the civil engineering field.

Award and Honor

Mr. Tharindu Indunil Madhushanka has achieved notable academic recognition throughout his educational journey. He graduated with a second-class upper division in his Bachelor of Science in Civil Engineering (Honors) from the University of Moratuwa, Sri Lanka, with a commendable GPA of 3.54 out of 4.2. This achievement underscores his strong academic performance and dedication to his studies. Tharindu has also earned recognition for his research contributions, particularly in the field of flood forecasting using artificial intelligence. His publication, “Multiple-Day-Ahead Flood Prediction in the South Asian Tropical Zone Using Deep Learning,” in the Journal of Hydrologic Engineering, demonstrates the impact of his work on flood management. Although his H-index is currently 1, it reflects his emerging influence in the research community. Tharindu’s research on sustainable building practices, including the thermal performance of precast panel buildings, has been presented at international conferences, further highlighting his growing recognition within the civil engineering and AI research communities.

Conclusion

Tharindu Indunil Madhushanka demonstrates a strong foundation in innovative, interdisciplinary research, particularly in leveraging artificial intelligence for flood forecasting and sustainable building practices. His academic achievements, technical expertise, and impactful research in disaster management are highly commendable.

Publications Top Noted

  • Title: Multi Day Ahead Flood Prediction in South Asian Tropical Zone Using Deep Learning
    Authors: T Madhushanka, T Jayasinghe, R Rajapakse
    Year: 2024
    Cited by: 1
  • Title: Multiple-Day-Ahead Flood Prediction in the South Asian Tropical Zone Using Deep Learning
    Authors: G Madhushanka, MTR Jayasinghe, RA Rajapakse
    Journal: Journal of Hydrologic Engineering 30 (1), 04024054
    Year: 2025
    Cited by: Not available
  • Title: Behavior of LSTM and Transformer Deep Learning Models in Flood Simulation Considering South Asian Tropical Climate
    Authors: G Madhushanka, MTR Jayasinghe, RA Rajapakse
    Year: 2024
    Cited by: Not available
  • Title: Transformer & LSTM Based Models for Multi-Day Ahead Flood Prediction in Tropical Climates
    Authors: T Madhushanka, T Jayasinghe, R Rajapakse
    Year: 2024
    Cited by: Not available
    Available at: SSRN 4746297
  • Title: Flood Prediction for Tropical Climates Using LSTM and Transformer Machine Learning Models
    Authors: T Madhushanka, T Jayasinghe, R Rajapakse
    Year: 2024
    Cited by: Not available
    Available at: SSRN 4736261
  • Title: LONG SHORT-TERM MEMORY (LSTM) & FEEDFORWARD ARTIFICIAL NEURAL NETWORK (ANN) FOR FLOOD PREDICTION
    Authors: G.W.T.I. Madhushanka, M.T.R. Jayasinghe, R.A. Rajapakse
    Event: Proceedings of the 14th International Conference on Sustainable Built …
    Year: 2023
    Cited by: Not available
  • Title: Thermal Performance of Precast Panel Buildings
    Authors: G Madhushanka, SS Bandaranayaka, MTR Jayasinghe, H Herath
    Event: University of Ruhuna
    Year: 2023
    Cited by: Not available

João Goes | Engineering | Best Researcher Award

Published on by Global Scholar Awards

João Goes | Engineering | Best Researcher Award

João Goes , Universidade NOVA de Lisboa , Portugal

Dr. João Goes is a distinguished academic and industry professional in Electrical and Computer Engineering (ECE). He graduated from Instituto Superior Técnico (IST) in Lisbon in 1992 and obtained his M.Sc. and Ph.D. degrees from the Technical University of Lisbon in 1996 and 2000, respectively. In 2012, he earned the ‘Habilitation’ degree in Electronics from NOVA University of Lisbon (NOVA). Since 1998, Dr. Goes has been with the Department of Electrical and Computer Engineering (DEEC) at NOVA’s School of Sciences and Technology, where he is currently a Full Professor. He headed the DEEC from 2012 to 2019 and directed the Centre of Technology and Systems (CTS) at UNINOVA from 2012 to 2017. Since 2023, he has served as the Executive Director of UNINOVA. Dr. Goes has been a member of the Scientific Council of FCT NOVA for 12 years and is currently a member of the General Council of NOVA for the 2022-2025 term.

Publication profiles:

Education 

João Goes graduated in Electrical and Computer Engineering (ECE) from Instituto Superior Técnico (IST), Lisbon, in 1992. He obtained his M.Sc. in ECE from the Technical University of Lisbon in 1996, followed by a Ph.D. in ECE from the same institution in 2000. In 2012, he earned the ‘Habilitation’ degree in Electronics from NOVA University of Lisbon (NOVA).

Research focus

João Goes’ research focuses on analog and mixed-signal (AMS) integrated circuit design, with a special emphasis on sensor-to-digital and digital-to-actuator interfaces, data converters (ADCs and DACs), and high-performance analog frontends (AFEs). He has published over 200 papers in international journals and IEEE leading conferences, holds 4 international patents, and is co-author of 8 books. Notably, he is the Portuguese researcher with the most published papers in all IEEE flagship conferences requiring silicon-proven integrated circuits (ICs) with state-of-the-art performance, including ISSCC, VLSI, CICC, and ESSCIRC.

Experience

João Goes has had a distinguished career in academia and industry. Since 1998, he has been with the Department of Electrical and Computer Engineering (DEEC) at the School of Sciences and Technology of NOVA, where he is a Full Professor. From 2012 to 2019, he headed the DEEC, managing 50 professors and over 1000 students. Between 2012 and 2017, he was the Director of the Centre of Technology and Systems (CTS) at the Research Institute for New Technologies (UNINOVA), leading nearly 50 senior researchers with PhDs, over 70 collaborators, and more than 90 PhD students. Since 2023, he has been the Executive Director of UNINOVA.

Honors & Awards

João Goes has received numerous honors and awards throughout his career. Among several best-paper awards, he is the co-author of a journal paper that received the 2012 IEEE CASS Outstanding Young Author Award. He also co-won the first edition of the “Innovation Award INCM” in 2016. His contributions to science and engineering have been recognized internationally, showcasing his impact and leadership in the field of electrical and computer engineering

Publications Top Noted & Contributions
  • Cyber-physical systems security: A systematic review
    • Authors: Harkat, H., Camarinha-Matos, L.M., Goes, J., Ahmed, H.F.T.
    • Journal: Computers and Industrial Engineering
    • Year: 2024
    • Citations: 3
  • A PVT-Robust Open-loop Gm-Ratio ×16 Gain Residue Amplifier for >1 GS/s Pipelined ADCs
    • Authors: Dias, D., Goes, J., Costa, T.
    • Conference: Proceedings – IEEE International Symposium on Circuits and Systems
    • Year: 2024
    • Citations: 0
  • A Standard-Cell-Based Neuro-Inspired Integrate-and-Fire Analog-to-time Converter for Biological and Low-Frequency Signals – Comparison with Analog Version
    • Authors: Teixeira, M.L., Oliveira, J.P., Principe, J., Goes, J.
    • Journal: IEEE Transactions on Biomedical Circuits and Systems
    • Year: 2024
    • Citations: 0
  • IEEE SSCS-EDS ESSCIRC-ESSDERC 2023 [Conference Reports]
    • Authors: Goes, J., De La Rosa, J., Cathelin, A., De Oliveira, L.B., Paulino, N.
    • Journal: IEEE Solid-State Circuits Magazine
    • Year: 2024
    • Citations: 0
  • A Standard-Cell-Based Neuro-Inspired Integrate-and-Fire ATC for Biological and Low-Frequency Signals
    • Authors: Teixeira, M.L., Oliveira, J.P., Principe, J.C., Goes, J.
    • Conference: BioCAS 2023 – 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings
    • Year: 2023
    • Citations: 0
  • Design of an 20 GHz Wide-Band Input Buffer
    • Authors: Sebastião, D., Goes, J.
    • Conference: ICECS 2023 – 2023 30th IEEE International Conference on Electronics, Circuits and Systems
    • Year: 2023
    • Citations: 0
  • Chairs’ Message
    • Authors: Da Franca, J.E., Goes, J., De La Rosa, J.M., De Melo, J., Paulino, N.
    • Journal: European Solid-State Device Research Conference
    • Year: 2023
    • Citations: 0
  • ESSDERC 2023 Program
    • Authors: Da Franca, J.E., Goes, J., De La Rosa, J.M., De Melo, J., Paulino, N.
    • Journal: European Solid-State Device Research Conference
    • Year: 2023
    • Citations: 0
  • Chairs’ Message
    • Authors: Da Franca, J.E., Goes, J., De La Rosa, J.M., De Melo, J., Paulino, N.
    • Journal: European Solid-State Circuits Conference
    • Year: 2023
    • Citations: 0
  • Predictive Integrators with Thermal Noise Cancellation
    • Authors: Xavier, J., Leonardo, D., Barquinha, P., Goes, J.
    • Conference: Proceedings – IEEE International Symposium on Circuits and Systems
    • Year: 2023
    • Citations: 0