Darío Fernando Yépez Ponce | Robotics and Automation | Editorial Board Member

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Prof. Darío Fernando Yépez Ponce | Robotics and Automation | Editorial Board Member

Docente Investigador | Instituto Superior Universitario Central Técnico | Ecuador

Darío Fernando Yépez Ponce is a mechatronics and automation engineer and academic from Ecuador, currently working as a faculty member in electronics at Instituto Superior Universitario Central Técnico in Quito (since October 2024). His background includes an engineering degree in mechatronics (2016) from Universidad Técnica del Norte, plus ongoing postgraduate studies (Master’s in Electronics and Automation) at Universidad Politécnica Salesiana. Over the years he has served as a lecturer in various institutions across Ecuador teaching mechatronics, electronics, and automation engineering.Professor Yépez’s research interest concentrates on robotics, control systems (notably PID control), autonomous systems (including unmanned ground vehicles), microgrids and power electronics, IoT-based automation, and applications of mechatronics in agriculture and automation systems. His work shows a recurrent focus on optimization algorithms, control strategies, mobile robotics, and intelligent systems for automation and smart farming. Notable recent outputs include a 2025 journal article titled “Route Optimization for UGVs: A Systematic Analysis of Applications, Algorithms and Challenges,” which analyses algorithms for path planning in autonomous ground vehicles. In terms of research productivity and impact: according to his publicly visible profile, he has a Google Scholar citation count of about 113 citations.Publications span journal articles, conference papers, and book chapters. For example, his 2025 UGV-optimization article is indexed in major journals. The breadth of his work — from control system tuning (e.g., PID controllers via hybrid optimization strategies) to IoT-based systems and robotics — reflects a versatile research skill set in automation, control, robotics, power electronics, and applied mechatronics.Although I could not find a definitive public value for his Scopus h-index or total Scopus-document count (his Scopus Author ID is 57220807265), the combination of his journal-indexed articles, book chapters and recent contributions suggests a growing research profile, particularly in robotics, automation, and sustainable/renewable-power applications.In conclusion, Darío Fernando Yépez Ponce represents a dynamic and interdisciplinary researcher bridging mechatronics, control systems, automation, and robotics — with an orientation toward real-world applications such as autonomous vehicles and smart farming. His emerging publication record and international-indexed works position him as an active contributor in automation and mechatronics research circles.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

  1. Yépez-Ponce, D. F., Salcedo, J. V., Rosero-Montalvo, P. D., & Sanchis, J. (2023). Mobile robotics in smart farming: Current trends and applications. Frontiers in Artificial Intelligence, 6, 1213330.
    Citations: 99

  2. Ponce, H. M. Y., & Yépez-Ponce, D. F. (2020). Control de modo deslizante para microrredes: Una revisión. Investigación Tecnológica IST Central Técnico, 2(1), 14–14.
    Citations: 5

  3. Yépez Ponce, D. F., & Montalvo López, W. M. (2021). Development of a hybrid optimization strategy based on a bacterial foraging algorithm (BFA) and a particle swarming algorithm (PSO) to tune the PID controller of a ball and plate system. In XV Multidisciplinary International Congress on Science and Technology (pp. 15–29).
    Citations: 3

  4. Yépez-Ponce, D. F., Montalvo, W., Guamán-Gavilanes, X. A., & Echeverría-Cadena, M. D. (2025). Route optimization for UGVs: A systematic analysis of applications, algorithms and challenges. Applied Sciences, 15(12), 6477.
    Citations: 2

  5. Yépez Ponce, H. M., Yépez Ponce, D. F., Proaño Lapuerta, E. A., Mosquera Bone, C. E., & Alarcón Angulo, M. L. (2022). Open-source platform for development of taximeters: Adjustment software. In International Conference on Applied Technologies (pp. 532–544).
    Citations: 1

 

Farhan Nisar | Computer Science | Best Researcher Award

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Dr. Farhan Nisar | Computer Science | Best Researcher Award

Lecturer | The University of Agriculture | Pakistan

Dr. Farhan Nisar, affiliated with Qurtuba University of Science & Information Technology, Peshawar, Pakistan, is an emerging scholar and researcher in wireless communications, Internet of Things (IoT) networks, and machine learning applications for network optimization. He has made notable contributions to the field through his research on Low Power Wide Area Networks (LPWANs), particularly LoRaWAN, focusing on improving network efficiency, energy consumption, scalability, and reliability. Dr. Nisar’s educational background and professional trajectory have equipped him with a solid foundation in computer science and telecommunications, enabling him to apply advanced machine learning techniques for adaptive network parameter optimization, such as spreading factor adjustment, which enhances IoT network performance in dynamic real-world environments. Professionally, he has been involved in academic research, teaching, and applied projects that bridge theoretical knowledge with practical deployment of intelligent network solutions. His research interests include wireless communication protocols, IoT architectures, network security, data-driven network management, and intelligent device integration, reflecting a multidisciplinary approach that combines computer science, engineering, and data analytics. Dr. Nisar has developed strong research skills in machine learning modeling, algorithm development, network simulation, data analysis, and performance evaluation, contributing to both academic publications and open-access research outputs. His scholarly work has resulted in six published documents, with 18 citations to date and an h-index of 3, as indexed in Scopus, demonstrating early yet impactful contributions to his field. While still in the early stages of his career, he has received recognition for his innovative approaches to network optimization and IoT research, highlighting his potential for future academic and industrial leadership. In conclusion, Dr. Farhan Nisar represents a forward-looking researcher whose interdisciplinary expertise, rigorous methodology, and practical focus on intelligent, self-optimizing networks position him as a valuable contributor to the advancement of next-generation IoT and wireless communication technologies.

Profiles: Scopus

Featured Publications

  1. Nisar, F., & [Co-authors]. (2016). Green cloud computing approaches with respect to energy saving to data centers. Journal of Information, 6(2).

  2. Nisar, F., & [Co-authors]. (2017). Native approach security issue. In Proceedings of the IEEE Comtech Conference.

  3. Nisar, F., & [Co-authors]. (2019). Location-based authentication service in smartphones. In Proceedings of the IEEE Comtech Conference.

  4. Nisar, F., & [Co-authors]. (2019). Apply ARIMA model for data center with respect to different architecture. In Proceedings of the IEEE Raees Conference.

  5. Nisar, F., & [Co-authors]. (2019). Resource utilization in data center by applying ARIMA approach. In INTAP 2019.

 

 

Zhaoxia Duan | Robotics and Automation | Best Researcher Award

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Assoc. Prof. Dr. Zhaoxia Duan | Robotics and Automation | Best Researcher Award

Associate Professor | Hohai University | China

Assoc. Prof. Dr. Zhaoxia Duan is a distinguished researcher whose academic journey began with a B.Sc. in Automation (2007-2011) and a Ph.D. in Control Science and Engineering (2011-2017) from Nanjing University of Science and Technology, including a visiting research fellowship at Shibaura University of Technology in Japan (2013-2014). Currently a tenured associate professor at the School of Artificial Intelligence and Automation, Hohai University, she earlier served as a lecturer in the College of Energy and Electrical Engineering (2017-2023) and has also been a postdoctoral researcher at the School of Mathematics, Southeast University since 2019. Her research interests encompass multi-agent network systems, path planning for robots and autonomous underwater vehicles (AUVs), multi-dimensional / 2D system theory and applications, switching system theory, and positive system theory; she has developed strong research skills in stability analysis, finite-frequency control, fuzzy hybrid system modeling, fault detection observers, optimization via machine-learning (e.g. multi-objective PSO + Q-learning), and observer/controller synthesis for 2D positive / Markov jump / delayed / hybrid systems. Over her career, she has led multiple funded projects including national, postdoctoral, and central university grants, supervised research, and contributed to theoretical advances in control and automation. Her publication record is robust, with over 30+ journal articles, two authorized invention patents, and the compilation of a university textbook. She has been recognized with numerous awards and honors such as teaching excellence, thesis supervision awards, lecture competition prizes, and reviewer excellence. According to Scopus metrics, she has authored approximately 64 documents, has received around 710 citations, and has an h-index of 17. In conclusion, Dr. Duan is a well-rounded scholar who bridges rigorous theoretical research with practical intelligent automation applications, and continues to make impactful contributions to control theory, robotics and multi-agent systems.

Profile: Scopus 

Featured Publications

Duan, Z., Zhang, Y., Xu, Z., & Xiang, Z. (2025). Path planning problem in rough terrain by multi-objective PSO algorithm combined with Q-learning and crossover operator. Applied Soft Computing Journal, 184, 113798.

Duan, Z., Fu, Y., Wang, R., & Xiang, Z. (2025). l₁-gain control for delayed 2-D Markov jump positive systems in the Fornasini–Marchesini model. Journal of the Franklin Institute, 362(13), 107907.

Duan, Z., Zhang, Y., Wang, R., Xu, Z., & Xiang, Z. (2025). Robot path planning in rough terrain based on multi-objective crossover-mutation particle swarm optimization. Evolutionary Intelligence, 18, 64.

Duan, Z., Shao, Z., & Xiang, Z. (2025). A collaborative command and allocation model for manned and unmanned maritime forces. Journal of Army Engineering University of PLA, 3(4), 98–104. (In Chinese).

Duan, Z., Chu, C., Ghous, I., & Xiang, Z. (2024). On the l∞-gain of 2-D positive Roesser systems with bounded time-varying delays. Journal of the Franklin Institute, 361, 106819.

 

Keun Chang Kwak | Robotics and Automation | Best Researcher Award

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Prof. Keun Chang Kwak | Robotics and Automation | Best Researcher Award

Professor | Chosun University | South Korea

Professor Keun-Chang Kwak is a distinguished researcher in the fields of computational intelligence, biometrics, and robotic vision systems, with extensive expertise in granular and neuro-fuzzy modeling, face and speaker recognition, knowledge extraction, behavior recognition, and auditory signal processing. He earned his Ph.D. in Electrical Engineering from Chungbuk National University, Korea, in 2002, following an MS in 1998 and a BS in 1996 from the same institution. Over his career, Prof. Kwak has held several prominent positions, including Professor at Chosun University, Korea (2007–present), Visiting Professor at California State University Fullerton, USA (2014–2015), Senior Researcher at the Intelligent Robot Research Division, Electronics and Telecommunications Research Institute (ETRI), Korea (2005–2007), and Postdoctoral Fellowships at the University of Alberta, Canada (2003–2005) and Chungbuk National University, Korea (2002–2003). He has also served as Project Manager of the AI Convergence University Project Division (2021–present) and Vice Director of the National Center of Excellence in Software at Chosun University (2018–2020), leading numerous national and international research initiatives. His research interests include computational intelligence, deep learning, speech emotion recognition, ECG-based biometrics, human-robot interaction, and knowledge extraction using fuzzy clustering. Prof. Kwak’s prolific publication record includes 138 Scopus-indexed documents, 1,667 citations, and an h-index of 21, reflecting high-impact contributions to journals such as IEEE Access, Applied Sciences, Electronics, and Sensors. He has led and mentored research teams, collaborated internationally, and contributed significantly to the robotics and AI communities. Prof. Kwak’s achievements are recognized through multiple awards, leadership roles, and professional memberships, highlighting his influence on research, education, and technology advancement. His work demonstrates exceptional innovation, academic excellence, and the potential to drive future breakthroughs in AI, robotics, and computational intelligence, making him highly deserving of the Best Researcher Award.

Profiles: Scopus | Google Scholar

Featured Publications

  1. Pedrycz, W., & Kwak, K. C. (2006). Linguistic models as a framework of user-centric system modeling. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 36(2), 187–200. [Citations: 187]

  2. Kwak, K. C., & Pedrycz, W. (2005). Face recognition using a fuzzy fisherface classifier. Pattern Recognition, 38(10), 1717–1732. [Citations: 185]

  3. Kwak, K. C., & Pedrycz, W. (2007). Face recognition using an enhanced independent component analysis approach. IEEE Transactions on Neural Networks, 18(2), 530–541. [Citations: 167]

  4. Byeon, Y. H., Pan, S. B., & Kwak, K. C. (2019). Intelligent deep models based on scalograms of electrocardiogram signals for biometrics. Sensors, 19(4), 935. [Citations: 138]

  5. Kwak, K. C., & Pedrycz, W. (2005). Face recognition: A study in information fusion using fuzzy integral. Pattern Recognition Letters, 26(6), 719–733. [Citations: 112]

 

Jiatao Ding | Robotics and Automation | Best Researcher Award

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Dr. Jiatao Ding | Robotics and Automation | Best Researcher Award

Postdoctoral Researcher | University of Trento | Italy

Dr. Jiatao Ding is an accomplished robotics researcher whose work focuses on optimal control, robot learning, and legged robotics, with a strong record of international collaborations and impactful scientific contributions. He obtained his Bachelor’s degree in Mechanical Engineering from Wuhan University in 2014 (Cum Laude), followed by a Doctorate in Mechatronics Engineering from Wuhan University in 2020, during which he also served as a Ph.D. Fellow at the Italian Institute of Technology (2018–2020), gaining valuable international exposure. Professionally, Dr. Ding has held prestigious research appointments including Research Assistant Scientist at the Chinese University of Hong Kong (2020–2022), Postdoctoral Researcher at Delft University of Technology (2022–2025), and currently, Postdoctoral Researcher at the University of Trento, Italy (2025–present). His research interests lie in humanoid and quadruped locomotion, reinforcement learning, and bio-inspired robotic control, where he has actively contributed to major EU H2020 projects such as Inverse, Nature Intelligence, and CogIMon, along with NSFC-funded projects in China. Dr. Ding’s research skills span advanced reinforcement learning, trajectory optimization, hierarchical and model predictive control, and adaptive locomotion strategies, which have enabled breakthroughs in versatile bipedal and quadrupedal robotic systems. His scholarly output is extensive, with publications in flagship robotics venues such as IEEE ICRA, IROS, IEEE Transactions on Robotics, IEEE/ASME Transactions on Mechatronics, and Advanced Robotics, reflecting both quality and global reach. He has served the academic community as a reviewer for leading journals and conferences, session chair at AIM 2025, associate editor at UR 2025, and guest editor for special issues in reputed journals, demonstrating leadership and commitment to advancing robotics research. His awards and honors include invited talks, editorial board appointments, and recognition through collaborative project leadership across Europe and Asia. According to Scopus, Dr. Ding has achieved 262 citations across 241 documents with an h-index of 11, underscoring both productivity and research impact. In conclusion, Dr. Jiatao Ding exemplifies an emerging global leader in robotics whose academic excellence, technical expertise, and dedication to collaborative research position him strongly for future innovations in intelligent robotic systems, making him a deserving candidate for international recognition.

Profile: Google Scholar

Featured Publications

Atanassov, V., Ding, J., Kober, J., Havoutis, I., & Della Santina, C. (2024). Curriculum-based reinforcement learning for quadrupedal jumping: A reference-free design. IEEE Robotics & Automation Magazine, 32(2), 35–48. Citations: 24

Ding, J., Han, L., Ge, L., Liu, Y., & Pang, J. (2022). Robust locomotion exploiting multiple balance strategies: An observer-based cascaded model predictive control approach. IEEE/ASME Transactions on Mechatronics, 27(4), 2089–2097. Citations: 24

Ding, J., Wang, Y., Yang, M., & Xiao, X. (2018). Walking stabilization control for humanoid robots on unknown slope based on walking sequences adjustment. Journal of Intelligent & Robotic Systems, 90(3), 323–338. Citations: 16

Ding, J., Zhou, C., Xin, S., Xiao, X., & Tsagarakis, N. G. (2021). Nonlinear model predictive control for robust bipedal locomotion: Exploring angular momentum and CoM height changes. Advanced Robotics, 35(18), 1079–1097. Citations: 26*

Ding, J., Atanassov, V., Panichi, E., Kober, J., & Della Santina, C. (2024). Robust quadrupedal jumping with impact-aware landing: Exploiting parallel elasticity. IEEE Transactions on Robotics, 40(1), 3212–3231. Citations: 13