Assist. Prof. Dr. Ghulam Farid – Reinforcement Learning in Robotics – Best Researcher Award

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Assist. Prof. Dr. Ghulam Farid - Reinforcement Learning in Robotics - Best Researcher Award

Harbin Engineering University - China

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Summary

Dr. Ghulam Farid is a robotics and control systems expert with a Ph.D. from Harbin Engineering University, China, specializing in aerial robotics. With six years of teaching and research experience at COMSATS University Islamabad and current postdoctoral work at HEU, he focuses on reinforcement learning-based motion planning and control. He has published over 30 research papers and contributes significantly to integrating artificial intelligence with robotics, particularly through the use of power electronics. His work bridges theory and real-world application, enhancing the development of intelligent, energy-efficient robotic systems.

Early academic pursuits

Ghulam Farid began his academic journey with a deep interest in automation and intelligent systems. His passion led him to pursue a Ph.D. in Control Science and Engineering from the College of Automation at Harbin Engineering University (HEU), China, which he successfully completed in 2018. During his doctoral studies, he focused on Reinforcement Learning in Robotics control and motion planning in aerial robotics, laying a strong foundation in system modeling, optimization, and power electronics, which later influenced his research trajectory.

Professional endeavors

Following the completion of his doctorate, Ghulam Farid served as an assistant professor at COMSATS University Islamabad, Pakistan, for six years. During this time, he was actively involved in teaching, mentoring students, and initiating research projects. His career later progressed with his return to HEU, where he is currently contributing Reinforcement Learning in Robotics as a postdoctoral fellow in the College of Intelligent Systems Science and Engineering. His current academic environment further supports his development in robotics and embedded systems enhanced by power electronics techniques.

Contributions and research focus

Dr. Farid’s research centers on robotics, particularly in reinforcement learning-based motion planning and control systems. His work involves integrating artificial intelligence algorithms with practical robotic applications, including autonomous navigation, dynamic environment adaptation, and efficient energy management systems. His contributions also extend to the design of intelligent controllers for unmanned systems, with an emphasis on system stability and Reinforcement Learning in Robotics performance improvements using modern control strategies and power electronics integration.

Impact and influence

With over 30 published papers in reputed international journals and conferences, Ghulam Farid has significantly impacted the robotics and control engineering community. His findings contribute to advancing smart robotic systems capable of self-learning and adaptation. He has been a sought-after collaborator in interdisciplinary projects, Reinforcement Learning in Robotics combining control systems, AI, and electrical engineering concepts, further emphasizing his influence in academia and applied research.

Academic cites

Dr. Farid’s scholarly output has gained increasing recognition, with citations reflecting the relevance and applicability of his work in various domains such as aerial robotics, autonomous systems, and intelligent control. His integration of reinforcement learning in robotic systems and his ability to link theoretical frameworks to practical applications are Reinforcement Learning in Robotics often referenced by researchers developing intelligent automation solutions.

Legacy and future contributions

As a dedicated researcher and educator, Ghulam Farid is positioned to leave a lasting legacy in the field of robotics and intelligent control systems. His ongoing projects aim to enhance robotic autonomy, develop smart collaborative machines, and improve energy-efficient designs using advanced power electronics solutions. In the future, he plans to lead Reinforcement Learning in Robotics large-scale interdisciplinary research initiatives and continue mentoring emerging scholars in the field of automation and control engineering.

Notable Publications

  1. Title: Nonlinear and Adaptive Intelligent Control Techniques for Quadrotor UAV – A Survey
    Authors: H. Mo, G. Farid
    Journal: Asian Journal of Control
    Year: 2019
  2. Title: Modified A-Star (A) Approach to Plan the Motion of a Quadrotor UAV in Three-Dimensional Obstacle-Cluttered Environment*
    Authors: G. Farid, S. Cocuzza, T. Younas, A. A. Razzaqi, W. A. Wattoo, F. Cannella, H. Mo
    Journal: Applied Sciences
    Year: 2022
  3. Title: A Review on Linear and Nonlinear Control Techniques for Position and Attitude Control of a Quadrotor
    Authors: G. Farid, M. Hongwei, S. M. Ali, Q. Liwei
    Journal: Control and Intelligent Systems
    Year: 2017
  4. Title: A Review on Optimal Placement of Sensors for Cooperative Localization of AUVs
    Authors: X. Bo, A. A. Razzaqi, G. Farid
    Journal: Journal of Sensors
    Year: 2019
  5. Title: Optimal Geometric Configuration of Sensors for Received Signal Strength-Based Cooperative Localization of Submerged AUVs
    Authors: X. Bo, A. A. Razzaqi, X. Wang, G. Farid
    Journal: Ocean Engineering
    Year: 2020

Conclusion

Dr. Farid’s journey reflects a strong commitment to advancing the fields of robotics and intelligent control systems. His contributions are shaping the next generation of autonomous machines, with a clear focus on innovation, energy efficiency, and real-time learning. Through continued research, international collaboration, and the integration of cutting-edge technologies like power electronics, he is well-positioned to leave a lasting academic and technological legacy in robotics and automation.

Dr. Chitradevi D – Health Informatics – Best Researcher Award

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Dr. Chitradevi D - Health Informatics - Best Researcher Award

SRM Institute of Science and Technology - India

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Summary

Dr. Chitradevi D. is a seasoned academician with over 18 years of experience in engineering education and 2 years in the IT industry. She holds a Ph.D. in Computer Science and Engineering and has a strong academic background, including an M.E. with a university rank. She has worked extensively in teaching, research, and academic administration. Her research interests include digital image processing, biomedical engineering, machine learning, deep learning, and optimization techniques. She has guided numerous postgraduate projects and handled a wide range of technical subjects such as artificial intelligence, Python, Java, and data structures.

Her leadership roles include contributions to NAAC, IQAC, convocation committees, and curriculum development, while also serving as an examiner and validation committee member across institutions. She has also incorporated modern technologies like power electronics into computing systems, especially in embedded applications and smart solutions.

Early academic pursuits

Dr. Chitradevi D. began her academic journey with a strong foundation in the sciences, earning a B.Sc. in Chemistry from Holy Cross College in 1999 with a commendable 76%. She later shifted her focus to computing, pursuing a Master of Computer Applications (MCA) at the same institution, achieving 78% in 2002. Her academic excellence continued as she completed her M.E. in Computer Science from Hindustan College of Engineering (Anna University), securing the 15th University Rank in 2009. Her passion for computer science culminated in a Ph.D. in Computer Science and Engineering from Hindustan Institute of Technology and Science (HITS) in 2020. This educational trajectory, grounded in both theory and application, has played a vital role in shaping her Health Informatics contributions to teaching and research in emerging areas, including power electronics applications in embedded systems.

Professional endeavors

With over 18 years of academic experience, Dr. Chitradevi has held various key roles in renowned institutions. She currently serves as an Associate Professor at SRM Institute of Science and Technology, Trichy. Her earlier appointments include a long-standing tenure at Hindustan Institute of Technology and Science (2006–2023) and a prior role at Pavendar Bharathidasan College of Engineering. Complementing her academic journey is 2 years of IT industry experience, where she worked as a Health Informatics Software Programmer at Techzone Software Solutions and Jine Infotech. Her real-world experience continues to inform her teaching, particularly in programming, database systems, and digital systems integrated with power electronics.

Contributions and research focus

Dr. Chitradevi has made remarkable contributions in both academic coordination and research. She has handled a wide spectrum of subjects, including Artificial Intelligence, Data Science, Java, Python, Distributed Systems, and Design Thinking. She has actively guided postgraduate research projects in areas such as digital image processing, biomedical engineering, and machine learning. Her Ph.D. research primarily revolved Health Informatics around optimization techniques, artificial intelligence, and deep learning models — with applications spanning from bio-medical diagnostics to image recognition. Her involvement in newsletter editing, exam evaluation, NAAC, IQAC, and government-conducted exams reflects her holistic commitment to institutional excellence.

Impact and influence

Dr. Chitradevi's influence extends beyond her classroom. She has actively contributed to institutional development by holding various administrative and academic responsibilities — including Research Coordinator, IQAC & NAAC Coordinator, Convocation Committee Head, and more. Her contributions to organizing events like Millet Mela (Government Initiative) highlight her interest in community outreach. Furthermore, her leadership in curriculum design, examination validation, and faculty development has Health Informatics significantly impacted academic governance. Her academic service also includes acting as an Examiner for Anna University and Hindustan University, directly influencing quality assurance in technical education.

Academic cites and recognitions

Her role in academia has been backed by citations and validations from recognized bodies. Dr. Chitradevi has served as an examiner at both internal and external levels, contributed to central evaluation work, and actively participated in question paper validation committees. She has worked closely with governing boards in both university-level assessments and government service examinations, Health Informatics earning a reputation for diligence and expertise. These contributions ensure that the outcomes of examinations and course content uphold academic standards across institutions.

Legacy and future contributions

Dr. Chitradevi’s legacy lies in her commitment to developing technically sound and ethically responsible graduates. She continues to focus on mentoring students in advanced domains like machine learning, artificial intelligence, and digital optimization. In the coming years, she aims to further her research and academic output, particularly by integrating power electronics into interdisciplinary Health Informatics computing applications — such as energy-efficient embedded systems and smart automation. Her dedication to collaborative growth and knowledge dissemination places her at the forefront of innovation-driven education.

Notable Publications

  1. Title: MR Brain Screening using Optimization Techniques – A Survey
    Authors: Chitradevi, D.; Prabha, S.
    Journal: Current Medical Imaging
    Year: 2023
  2. Title: Hybrid Whale and Gray Wolf Deep Learning Optimization Algorithm for Prediction of Alzheimer’s Disease
    Authors: Chitradevi D, Sathish Kumar Mani, Sandeep Kumar M, Senthilkumar Mohan, Prabhu Jayagopal, Saurav Mallik, Hong Qin
    Journal: Mathematics
  3. Title: Academic Performance Prediction Using Machine Learning: A Comprehensive & Systematic Review
    Authors: Chakrapani, P.; Chitradevi, D.
    Conference: International Conference on Electronic Systems and Intelligent Computing (ICESIC)
    Year: 2022
  4. Title: Predictive Analytics of Road Accidents Using Machine Learning
    Authors: Kaliraja, C.; Chitradevi, D.; Rajan, A.
    Conference: International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE)
    Year: 2022
  5. Title: Simulation of Machine Learning Techniques to Predict Academic Performance
    Authors: Chakrapani, P.; Chitradevi, D.
    Conference: International Conference on Electronic Systems and Intelligent Computing (ICESIC)
    Year: 2022

Conclusion

Dr. Chitradevi's career reflects a blend of academic excellence, technical depth, and administrative leadership. Her multifaceted contributions have significantly impacted both students and institutional frameworks. With a research-driven mindset and a future-oriented vision, she continues to integrate power electronics with intelligent computing to develop advanced educational and research practices. Her work not only strengthens the academic community but also paves the way for innovative interdisciplinary solutions in engineering and technology.

Dr. Lanxiang Zheng – Mobile Robotics Systems – Best Researcher Award

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Dr. Lanxiang Zheng - Mobile Robotics Systems - Best Researcher Award

China United Network Communications Co., Ltd. Guangdong Branch - China

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Summary

Lanxiang Zheng is an accomplished ai technology director with a strong academic foundation rooted in computer science and robotics. after earning his ph.d. from sun yat-sen university, he dedicated his career to advancing research in distributed control, uav swarm planning, and multi-robot exploration. professionally, he leads innovations at china united network communications co., ltd. guangdong branch, applying theoretical research to real-world ai systems. his work uniquely combines intelligent robotics with power electronics, enhancing system efficiency and control. he is a recognized reviewer for major robotics journals and conferences, contributing significantly to the academic community.

Early academic pursuits

Lanxiang Zheng began his academic journey with a strong focus on computer science, eventually earning a ph.d. from sun yat-sen university. during his formative years, he developed deep expertise in distributed systems and intelligent control algorithms. his academic foundation laid the groundwork for his later contributions in the fields of multi-robot exploration and Mobile Robotics Systems uav swarm planning. even during this phase, he explored the interplay between artificial intelligence and power electronics, particularly in intelligent embedded systems for robotics.

Professional endeavors

After completing his doctorate, zheng took on the role of ai technology director at china united network communications co., ltd., guangdong branch. in this capacity, he leads several r&d initiatives focusing on real-time applications of ai in industrial and telecommunications settings. his work bridges theory and practice, bringing cutting-edge robotics research into Mobile Robotics Systems practical implementations. one of his key areas involves integrating power electronics with swarm robotics to enhance energy efficiency and operational control in field-deployed systems.

Contributions and research focus

Lanxiang Zheng’s primary research areas include distributed control, uav swarm planning, and embodied intelligence. his work in multi-robot exploration has advanced the autonomous capabilities of mobile robots in complex environments. he is particularly known for pioneering adaptive swarm algorithms that incorporate distributed intelligence, which are instrumental in Mobile Robotics Systems scalable robotic deployments. his research also investigates the convergence of intelligent control strategies with power electronics, enhancing the synergy between hardware control and machine learning models.

Impact and influence

As a recognized reviewer for prestigious journals and conferences such as ra-l, icar, and iros, zheng has played an important role in maintaining the quality and innovation within the ai and robotics research community. his evaluation work supports groundbreaking studies and Mobile Robotics Systems reinforces academic standards globally. he is frequently consulted on topics related to ai integration in industrial robotics and autonomous systems, often emphasizing the importance of efficient power electronics in ensuring real-world scalability.

Academic cites

Lanxiang Zheng’s scholarly work has been widely cited across robotics and ai research. his publications contribute to foundational knowledge in uav autonomy, swarm coordination, and intelligent control systems. his citations reflect the academic community’s recognition of his theoretical advancements and practical methodologies. his research articles are frequently referenced in Mobile Robotics Systems studies exploring the control mechanics of collaborative robotics and the embedded system design for energy-efficient robotics.

Legacy and future contributions

Zheng’s interdisciplinary approach and visionary leadership have made a lasting mark in the robotics sector. he aims to continue driving innovation at the intersection of artificial intelligence, robotics, and Mobile Robotics Systems communications infrastructure. his future projects focus on large-scale deployment of intelligent agents, supported by advanced power electronics, to tackle real-world challenges such as disaster response, environmental monitoring, and smart city automation. his legacy lies in building intelligent, collaborative systems that push the boundaries of what robots can achieve autonomously.

Notable Publications

  1. Title: AAGE: Air-Assisted Ground Robotic Autonomous Exploration in Large-Scale Unknown Environments
    Authors: Lanxiang Zheng, Mingxin Wei, Ruidong Mei, Kai Xu, Junlong Huang, Hui Cheng
    Journal: IEEE Transactions on Robotics
    Year: 2025
  2. Title: Meta-Learning Enhanced Model Predictive Contouring Control for Agile and Precise Quadrotor Flight
    Authors: Mingxin Wei, Lanxiang Zheng, Ying Wu, Ruidong Mei, Hui Cheng
    Journal: IEEE Transactions on Robotics
    Year: 2025
  3. Title: Bio-Inspired Decentralized Model Predictive Flocking Control for UAV Swarm Trajectory Tracking
    Authors: Lanxiang Zheng, Ruidong Mei, Mingxin Wei, Zhijun Zhao, Bingzhi Zou
    Journal: Journal of Bionic Engineering
    Date: 2025-06-23
  4. Title: Real-Time Efficient Environment Compression and Sharing for Multi-Robot Cooperative Systems
    Authors: Lanxiang Zheng, Kai Xu, Jinqi Jiang, Mingxin Wei, Boyu Zhou, Hui Cheng
    Journal: IEEE Transactions on Intelligent Vehicles
    Year: 2024
  5. Title: Safe Learning-Based Control for Multiple UAVs Under Uncertain Disturbances
    Authors: Mingxin Wei, Lanxiang Zheng, Ying Wu, Han Liu, Hui Cheng
    Journal: IEEE Transactions on Automation Science and Engineering
    Year: 2024

Conclusion

Through a blend of academic rigor and professional application, Lanxiang Zheng has become a key figure in ai-driven robotics. his research not only deepens understanding of swarm intelligence and autonomous systems but also paves the way for practical deployment powered by advanced power electronics. his continued efforts promise to influence the future of intelligent machines, making them more efficient, scalable, and impactful across industries.

Mr. Feng Yueyun – Electrical engineering – Best Researcher Award

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Mr. Feng Yueyun - Electrical engineering - Best Researcher Award

Beijing Jiaotong University - China

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Summary

Feng Yueyun is an emerging scholar in the field of power electronics, with a strong academic background and hands-on experience in advanced engineering systems. after graduating in the top 1% of his class from shanxi university, he pursued his master’s degree at beijing jiaotong university, specializing in power electronics and electric drive. he has demonstrated technical proficiency with tools like matlab/simulink, ccs, and vivado, and has actively contributed to research projects involving hybrid vehicles and motor control systems. as a first author, he has already published three scientific papers, reflecting his growing academic impact and dedication to innovation.

Early academic pursuits

Feng Yueyun embarked on his academic journey with a strong foundation in electrical engineering. he pursued his undergraduate degree at shanxi university (2019–2023), where he consistently ranked in the top 1% of his major with a gpa of 3.64/4.5. his coursework reflects his aptitude in core areas Electrical engineering, including circuit theory (96), fundamentals of electronic technology (92), and electric machinery and drive (93.3). his academic commitment was complemented by certifications such as cet-4, cet-6, and the putonghua proficiency certificate.

Professional endeavors

Currently pursuing his master's degree in power electronics and electric drive at beijing jiaotong university (2023–2026), feng has immersed himself in high-level engineering applications. he has acquired hands-on experience with Electrical engineering essential tools including matlab/simulink, ccs (dsp), vivado (fpga), and rt-lab, equipping him to tackle real-world industrial and research problems in power electronics.

Contributions and research focus

Feng yueyun plays an active role in advanced research projects within the domain of hybrid engineering vehicles, where he serves as the primary student supervisor. his technical responsibilities include debugging control boards and modifying dsp code for mining truck traction motor systems. his commitment to power electronics is further evidenced by Electrical engineering his research and publication record. he is the first author on three publications: one presented at an ei-indexed conference, and two published in sci journals (one fourth-tier and one second-tier).

Impact and influence

His research efforts are shaping efficient electric drive systems and energy solutions, especially within the field of power electronics. his undergraduate project—“power generation and energy storage based on human movement”—demonstrates his early initiative in exploring innovative energy technologies, Electrical engineering contributing to the broader dialogue on sustainability and human-centric design.

Academic cites

Feng’s academic visibility is growing steadily. with multiple authored papers already cited in indexed literature, his influence continues to expand within the scientific and engineering communities. his engagement with practical applications in Electrical engineering vehicle electrification and electric drive control systems further reinforces his credibility as an emerging scholar in power electronics.

Legacy and future contributions

Feng Yueyun is poised to make lasting contributions to the domain of power electronics. with a strong academic record, technical fluency, and early publication success, he is on a clear trajectory to become a thought leader in smart transportation, Electrical engineering hybrid vehicle control, and advanced electric drive systems. his future work is expected to bridge the gap between academic innovation and industrial implementation, reinforcing sustainable engineering solutions for modern infrastructure.

Notable Publications

Title: Temperature Compensation Control of an Induction Motor with Rotor Time Constant Error Regulation
Journal: Electrical Engineering
Year: 2025

Conclusion

With a proven track record in both academic excellence and applied research, Feng Yueyun is well-positioned to contribute meaningfully to the evolving field of power electronics. his work not only advances current technologies in electric drives and hybrid systems but also lays the groundwork for sustainable energy innovations. as he continues to build on his expertise, he is expected to play a significant role in shaping the future of intelligent transportation and energy-efficient solutions.

Assoc. Prof. Dr. Seulki Lee – Cognitive Robotics Systems – Best Researcher Award

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Assoc. Prof. Dr. Seulki Lee - Cognitive Robotics Systems - Best Researcher Award

Kwangwoon University - South Korea

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Summary

Dr. Seulki Lee, an associate professor at Kwangwoon university, is a leading academic in the field of construction engineering with a strong focus on digital transformation. her expertise spans digital knowledge representation, smart technology acceptance, off-site construction evaluation, and robotics simulation. with a comprehensive academic background from kwangwoon university and significant research experience at seoul national university, she has developed advanced methodologies integrating ontology, bim, digital twins, and power electronics. recognized by multiple prestigious awards, she continues to shape the future of construction technology through research, education, and mentorship.

Early academic pursuits

Dr. Seulki Lee’s academic journey began at Kwangwoon university, where she completed her bachelor’s degree in architectural engineering (2004–2008). her passion for construction and digital systems led her to pursue a master’s (2008–2010) and subsequently a ph.d. in construction management (2010–2014) from the same institution. Cognitive Robotics Systems her early research focused on integrating digital technologies with architectural processes—a foundation that continues to shape her work in domains such as building information modeling (bim), ontology, and power electronics in construction automation systems.

Professional endeavors

After earning her doctoral degree, Dr. lee served as a senior researcher at the institute of construction and environmental engineering, seoul national university (2014–2021). during this period, she deepened her expertise in simulation, prefabrication, and construction knowledge management. in march 2021, she returned to her alma mater, kwangwoon university, as an associate professor in the department of architectural engineering. her dual roles in research and academia have allowed her to mentor students, lead funded projects, and collaborate on national and international research initiatives, especially those integrating digital twins and robotics with power electronics.

Contributions and research focus

Digitalization of construction knowledge: She works on developing ontology-based frameworks for representing and automating reasoning over construction data using rdf, sparql, and large language models (llms). Smart technology acceptance and education: Her research explores how professionals adopt digital tools, focusing on the technology acceptance model (tam) and the development of Cognitive Robotics Systems effective safety-oriented training methods. Off-site construction and dfx evaluation: She has introduced structured evaluation systems for design for manufacturing and assembly (dfma) and quality control of prefabricated components. Construction robotics and simulation: She is a pioneer in integrating robot-friendly environments, bim, and digital twins to simulate and evaluate robotic task efficiency—especially in synergy with power electronics used in autonomous systems.

Impact and influence

Dr. Lee’s contributions have been recognized through numerous prestigious awards. these include the president’s commendation from the korean society of civil engineers (ksce) in 2025, the jeong won-seok special award in 2024, Cognitive Robotics Systems and multiple outstanding paper awards from kicem and aik. in addition, her student supervision excellence awards (2021–2024) highlight her role as a mentor and educator shaping the next generation of engineers.

Academic cites

Her work is frequently cited in areas of ontology-based construction knowledge, smart construction technologies, and construction robotics. she has contributed to numerous peer-reviewed publications and conference papers, often at the intersection of bim, simulation, and digital literacy. her academic visibility has made her a recognized authority in Cognitive Robotics Systems integrating semantic web technologies and ai reasoning into architectural and civil engineering workflows.

Legacy and future contributions

As a thought leader in the digitization of construction systems, dr. lee continues to influence policy, research, and education in smart construction. her future work aims to further automate decision-making processes through advanced reasoning engines and enhance human-robot collaboration for safer and more efficient work environments. with a Cognitive Robotics Systems commitment to standardization, sustainability, and educational reform, she is poised to leave a lasting legacy in both academia and industry.

Notable Publications

  1. Title: Automated Inference of Context-Specific Hazards in Construction Using BIM and Ontology
    Authors: [Author names not provided]
    Journal: Automation in Construction
    Year: 2025
  2. Title: A Practical Image Augmentation Method for Construction Safety Using Object Range Expansion Synthesis
    Authors: [Author names not provided]
    Journal: Buildings
    Year: 2025

Conclusion

Dr. Seulki Lee’s contributions reflect a deep commitment to modernizing construction practices through digital innovation and interdisciplinary integration. her impactful research in automation, smart education, and robotics-enabled environments—supported by technologies such as power electronics—positions her as a visionary leader in engineering. as construction rapidly evolves, her work will remain pivotal in fostering safer, smarter, and more efficient industry practices while inspiring future scholars and practitioners.

Dr. Aslain Brisco Ngnassi Djami – Design – Best Researcher Award

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Dr. Aslain Brisco Ngnassi Djami - Design - Best Researcher Award

University of Ngaoundere - Cameroon

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Summary

Ngnassi Djami Aslain Brisco is a dedicated cameroonian scholar and senior lecturer specializing in equipment and production engineering, with a strong foundation in mechanical and production systems. his academic path—from a diploma in industrial maintenance to a ph.d.—reflects a consistent pursuit of technical excellence. professionally, he has held teaching and leadership roles at the university of ngaoundéré and institutions in gabon. his teaching covers diverse engineering topics, and his research is aligned with system reliability, maintenance optimization, and the practical integration of power electronics in industrial environments. his mentorship, jury participation, and scientific evaluations showcase his deep engagement with academic development and institutional growth.

Early academic pursuits

Ngnassi Djami Aslain Brisco’s academic journey began with a robust foundation in mathematics and physical sciences, as evident from his baccalauréat ‘c’ and probatoire ‘c’ from schools in ngaoundéré. his early interest in technical disciplines was further solidified by his b.e.p.c in german from malang high school. his post-secondary education saw a progressive specialization—from a university diploma in technology in industrial and production maintenance at iut ngaoundéré (2012) to an engineering degree in industrial maintenance and productics at ensai ngaoundéré (2015). he later advanced to a master’s degree in agro-industrial equipment engineering (2017) and earned a ph.d. in equipment and production engineering in 2021. this academic progression highlights his deep commitment to  Design industrial and mechanical engineering with a growing interest in power electronics for manufacturing systems.

Professional endeavors

As a senior lecturer in the department of fundamental sciences and engineering techniques (since may 2022) at the school of chemical engineering and mineral industries, university of ngaoundéré, Dr. Ngnassi plays a crucial role in developing engineering education. he has served multiple times as temporary head of department and contributed significantly to curriculum and departmental leadership. his responsibilities span teaching diverse technical subjects, including cad, reliability engineering,  Design computerized maintenance management (gmao), and production management (gpao). his prior roles include researcher-teacher positions at both egcim and the univga group in libreville, gabon, as well as adjunct lecturer duties at the university institute of technology (iut), ngaoundéré. through these roles, he has supported emerging research in domains like power electronics, maintenance systems, and mechanical design.

Contributions and research focus

Dr. Ngnassi’s teaching covers a wide spectrum of engineering disciplines—from descriptive geometry to advanced modeling and system optimization. his research and pedagogical contributions center on equipment reliability, computerized maintenance, and production optimization. of particular note is his active involvement in technical unit development,  Design jury memberships for various academic defenses, and evaluation of academic promotion applications. his academic influence extends to areas such as system modeling, maintenance automation, and the application of power electronics in production environments—an emerging field that supports energy efficiency and operational reliability in industrial systems.

Impact and influence

With a presence across cameroon and gabon, dr. ngnassi’s educational footprint has supported multiple generations of engineering students. he has influenced curricular decisions, evaluated theses, and mentored future engineers. as a scientific evaluator, he contributes to academic excellence and faculty development. his focus on reliability and  Design computerized systems resonates with industrial trends in automation and digitization, where power electronics plays a transformative role. his teaching and research not only align with industry needs but also shape regional academic standards in mechanical and production engineering.

Academic cites

Though specific citation indices are not listed, Dr. Ngnassi’s research and academic involvement position him as a valued contributor in areas such as system diagnostics, failure analysis, and technical drawing. he is recognized for combining theoretical rigor with practical relevance, especially in applied courses like reliability,  Design maintainability, and availability. through published works, internal reports, and conference participations, his academic voice continues to grow within the francophone engineering research community.

Legacy and future contributions

Dr. Ngnassi Djami Aslain Brisco represents a new wave of scholar-practitioners committed to technological progress and regional development. his long-term vision likely includes expanding interdisciplinary research, improving industrial practices through education, and fostering innovation in mechanical systems design. he is expected to further explore the applications of power electronics in automation and sustainable engineering—particularly as africa embraces digital manufacturing and energy transformation.  Design with his depth of knowledge and dedication to student mentorship, his academic legacy is poised for lasting influence.

Notable Publications

  1. Title: OPTIMIZATION OF EQUIPMENT RELIABILITY BASED ON A NEURO-FUZZY APPROACH: CASE OF A FLOUR MILL
    Authors: Ngnassi Djami Aslain Brisco
    Journal: Reliability: Theory & Applications
    Year: 2025
  2. Title: Proposal of a new efficient method for Pareto front capture in multiobjective mechanical design: the case of a computer numerical control milling machine
    Authors: Aslain Brisco Ngnassi Djami
    Journal: Operational Research
    Date: 2025-09
  3. Title: Harnessing artificial neural networks for improved control of wind turbines based on brushless doubly fed induction generator
    Authors: Ulrich Ngnassi Nguelcheu, Ndjiya Ngasop, Eric Duckler Kenmoe Fankem, Aslain Brisco Ngnassi Djami, Golam Guidkaya, Joseph Yves Effa
    Journal: Engineering Applications of Artificial Intelligence
    Date: 2025-08
  4. Title: Parameters estimation of the Weibull law for reliability modeling of an equipment
    Authors: Aslain Brisco Ngnassi Djami, Wolfgang Nzie, Serge Yamigno Doka
    Journal: Life Cycle Reliability and Safety Engineering
    Date: 2024-12
  5. Title: Residual reliability of a composite material subjected to buckling and post-buckling tests: the case of reinforced concrete
    Authors: Ngnassi Djami Aslain Brisco
    Journal: Frontiers in Mechanical Engineering
    Date: 2024-12-18

Conclusion

As a researcher, Educator, and evaluator, Dr. Ngnassi Djami Aslain Brisco contributes significantly to engineering education and applied research in central africa. his focus on reliability engineering, system modeling, and power electronics integration positions him at the intersection of traditional mechanics and modern automation. looking ahead, his legacy will likely be defined by his commitment to innovation, interdisciplinary growth, and the promotion of sustainable, electronics-driven production systems—making him a key figure in shaping the future of engineering education and practice in the region.

Mrs. Chittepu Sireesha – Deep Learning – Best Researcher Award

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Mrs. Chittepu Sireesha - Deep Learning - Best Researcher Award

SR University - India

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Summary

Sireesha Chittepu is a seasoned academic with over 15 years of teaching experience in computer science and engineering. Her educational background includes a B.Tech and M.Tech in software and computer sciences, and she is currently pursuing a Ph.D. in Computer Science and Engineering at SR University. Throughout her career, she has demonstrated strong proficiency in subjects ranging from data structures to NLP and software testing. Notably, she has contributed significantly to institutional development through her roles as a coordinator for national-level hackathons, class mentor, and virtual lab leader in collaboration with IITH. Her research interest is expanding into areas that blend software innovation with applied domains such as power electronics, where she aims to enhance the interaction between software systems and hardware frameworks. She has also designed internal tools such as attendance and feedback systems to streamline academic administration.


Early academic pursuits

Sireesha Chittepu laid the foundation of her academic journey with a strong focus on the sciences, securing 85.6% in her Intermediate studies and 82% in her SSC. She pursued her B.Tech in Computer Science and Information Technology from Rajiv Gandhi Memorial College of Engineering and Technology under JNTU, achieving 70%. Further strengthening her expertise, deep learning she completed an M.Tech in Software Engineering from VNR Vignana Jyothi Engineering College, Hyderabad, with 78%. Currently, she is pursuing a Ph.D. in Computer Science and Engineering from SR University, Telangana, aligning her research with cutting-edge trends including power electronics, AI integration, and automation.

Professional endeavors

With over 15 years of teaching experience, Sireesha Chittepu has been a cornerstone in the academic development of countless students. Her journey began in 2003 and includes tenure at Alpha College of Engineering, Sree Nidhi Institute of Science and Technology, and Stanley College of Engineering and Technology for Women. Since 2015, deep learning she has been serving as an Assistant Professor at Vasavi College of Engineering, Hyderabad, demonstrating excellence in pedagogy and department-level coordination. Her professional engagements frequently intersect with power electronics, where she integrates software systems to improve learning tools and virtual lab environments.

Contributions and research focus

Sireesha’s teaching expertise spans a wide range of computer science subjects such as Compiler Construction, Data Structures, Software Engineering, and Natural Language Processing. She has developed and implemented innovative tools such as an attendance tracking system and a feedback management system, both of which enhance academic management deep learning. Her research focus aligns with emerging technologies and includes interdisciplinary studies where software engineering intersects with hardware systems like power electronics, emphasizing system-level integration and smart computing applications.

Impact and influence

In her role as Department Coordinator for Hackathons, Co-curricular and Extracurricular Activities, and SPOC for Smart India Hackathons (2019–2020), Sireesha has mentored students in national-level innovation challenges. Her coordination with institutions like IIT-Hyderabad for virtual labs reflects her impact on advancing academic infrastructure. She also contributes to curriculum development and exam preparation, influencing academic delivery deep learning across several institutions. These contributions indirectly support power electronics education by encouraging cross-domain thinking and system-oriented learning approaches among students.

Academic cites

While her Ph.D. is ongoing, Sireesha Chittepu's academic involvement includes preparing university-level question papers, developing lesson plans, and assessing student performance through structured evaluation methods. Though no formal citation index was mentioned, her continuous evaluation roles, seminar engagements deep learning, and project mentorships suggest a strong academic presence that is evolving towards publication and citation in future academic platforms.

Legacy and future contributions

Sireesha aims to bridge the gap between education and innovation, with a long-term vision of contributing to academia through research, digital tools, and cross-disciplinary teaching. Her future goals include publishing impactful research, particularly in the convergence of software engineering and power electronics, and mentoring future educators and deep learning researchers. As she continues her doctoral research, she is poised to leave a legacy defined by practical innovation, academic excellence, and a deep commitment to student-centric learning.

Notable Publications

  1. Title: Enhancing Medicinal Plant Prediction Through Deep Neural Network Algorithms
    Authors: Munigala Swapna, Sireesha Chittepu, Sanjana Gavada, Sreeja Barigela
    Publication: Communications in Computer and Information Science (CCIS) – Book Chapter
    Year: 2025
  2. Title: Improving Air Quality Prediction: A Study on Data-Driven Techniques and Advanced Sensing Technologies
    Authors: Yeshwanth Reddy, C. Sireesha
    Publication: Lecture Notes on Data Engineering and Communications Technologies – Book Chapter
    Year: 2025
  3. Title: Dynamic Conditional Encoding and Feature Frequency Parsing in Diffusion Probabilistic Models for Diabetic Foot Ulcer Detection Using Thermographic Imaging
    Authors: Kousar Nikhath A, Sireesha C, Swapna M, Vijayetha Thoday, Esther Rani D
    Publication: Journal of Biomedical Photonics & Engineering
    Date: 2025-03-31
  4. Title: A ResNet Based Plant Disease Diagnosis Platform
    Authors: Sireesha Chittepu, Suchith B, Deepthi M
    Publication: 2025 7th International Conference on Signal Processing, Computing and Control (ISPCC)
    Date: 2025-03-06
  5. Title: Enhancing the Surveillance, Assessment, and Tracking of Mental Health and Well-being Using Deep Learning Techniques
    Authors: Sireesha Chittepu, Sheshikala Martha
    Publication: 2025 7th International Conference on Signal Processing, Computing and Control (ISPCC)
    Date: 2025-03-06

Conclusion

Sireesha Chittepu's career reflects a commitment to academic excellence, hands-on innovation, and student empowerment. Her proactive involvement in research, curriculum design, and co-curricular coordination showcases her holistic approach to education. As she continues her Ph.D., her contributions are expected to deepen, particularly in interdisciplinary research areas including power electronics, where her experience in software systems can offer new insights. Looking ahead, Sireesha is well-positioned to influence future educational practices, mentor the next generation of engineers, and contribute meaningfully to research that connects computation with real-world systems.

Mr. Xinwei He – Object Detection – Best Researcher Award

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Mr. Xinwei He - Object Detection - Best Researcher Award

Foshan University - China

Author Profile

GOOGLE SCHOLAR

Summary


Xinwei He, a second-year master’s student in software engineering at foshan university, is an emerging researcher in the field of object detection with a strong inclination toward real-world applications in power electronics and automation systems. his key contribution—tgcpn: two-level grid context propagation network for 3d small object detection—showcases a blend of academic depth and practical insight. through active participation in publication, code sharing, and peer-reviewed processes, xinwei is steadily building a credible academic presence. while early in his career, his focused research direction and commitment to quality reflect significant potential for future impact.

Early academic pursuits


Xinwei he is currently a second-year master's student in software engineering at foshan university. with a foundational understanding of computational models and a growing proficiency in research methodology, xinwei began contributing to the academic domain early in postgraduate studies. the integration of power Object Detection electronics principles with intelligent object recognition marked a turning point in xinwei's academic direction. xinwei is steadily building a credible academic presence. while early in his career, his focused research direction and commitment to quality reflect significant potential for future impact.

Professional endeavors


Though still in the academic phase, xinwei he has demonstrated professional maturity through the successful development of the project titled tgcpn: two-level grid context propagation network for 3d small object detection. this work highlights the Object Detection application of computer vision within high-efficiency environments, including power electronics-based automation systems. the project underscores a capacity to work at the intersection of deep learning and real-world utility.

Contributions and research focus


Xinwei’s primary area of research is object detection, with an emphasis on small-scale 3d object identification in complex environments. the recently completed paper revision and response to peer review comments demonstrates not only technical proficiency but also academic resilience. this effort contributes meaningfully to current advancements Object Detection in image detection technologies within power electronics and robotics-based systems.

Impact and influence


Xinwei he's ongoing work is gaining attention through platforms like github and springer. by leveraging code sharing and academic publication, Xinwei is establishing a transparent and collaborative research footprint. Object Detection although citation indices are in early stages, the methodological rigor and thematic relevance suggest promising growth in academic influence, particularly in the automation sector.

Academic cites


The project has been recognized in academic channels, with a publication under a reputable journal indexed by springer. while specific citation metrics are pending, xinwei's engagement with high-impact areas such as Object Detection power electronics-driven automation systems, signal propagation, and detection architecture indicates future relevance in citations and scholarly reference.

Legacy and future contributions


Xinwei he is poised to contribute further to the fields of object detection and robotics. future plans likely include expanding research collaborations, deepening the interface between object detection and applied power electronics, and increasing journal presence. with a strong ethical foundation as expressed in the self-declaration, xinwei seeks to build a legacy of integrity, innovation, and interdisciplinary growth.

Notable Publications

Title: Tgcpn: Two-level grid context propagation network for 3D small object detection
Authors: Y. Zhou, L. Pu, X. Xu, C. Yi, X. He, Y. Zhou, Y. Xu
Journal: Pattern Analysis and Applications

Conclusion


Xinwei He exemplifies the qualities of a dedicated and innovative researcher whose early contributions are already aligning with critical technological trends like automation and power electronics-driven systems. his consistent efforts in refining research output, responding to scholarly critique, and collaborating through open platforms position him well for long-term influence. with continued mentorship and engagement, xinwei is set to evolve into a valuable contributor to the global robotics and software engineering community.

 

Mr. Tianlun Luo – Computer vision – Excellence in Innovation

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Mr. Tianlun Luo - Computer vision - Excellence in Innovation

University of Liverpool - China

Author Profile

SCOPUS 
ORCID

Summary

Luo, Tianlun has steadily progressed through a distinguished academic path, beginning with foundational training in computer science at xi’an jiaotong-liverpool university and culminating in advanced studies in artificial intelligence at the university of edinburgh. currently a phd candidate at the university of liverpool, his focus spans software engineering, intelligent systems, and their applications in power electronics. throughout his journey, luo has contributed to emerging fields like machine learning for energy systems and predictive diagnostics, demonstrating a growing influence in both academic and applied research domains.

Early academic pursuits

Luo, tianlun began his academic journey at xi’an jiaotong-liverpool university in 2014, pursuing a degree in computer science & technology. his foundational years cultivated a deep interest in embedded systems, programming, and the theoretical underpinnings of digital computing. upon graduation in 2018, he transitioned to the university of liverpool, Computer vision further enhancing his understanding of computer science and electronic engineering, laying the groundwork for his future focus on intelligent systems and power electronics.

Professional endeavors

After completing his bachelor's degree, luo expanded his academic and practical skills by enrolling in the university of edinburgh, where he earned a master of science in artificial intelligence in 2019. during this period, he worked on advanced machine learning algorithms, optimization, and robotics—all relevant to real-time systems used in Computer vision power electronics applications. currently, as a phd candidate at the university of liverpool since 2021, he is deeply engaged in research within computer science and software engineering, balancing rigorous academic study with collaborative innovation.

Contributions and research focus

Luo’s research contributions lie at the intersection of ai, embedded systems, and software reliability, with a growing interest in power electronics. he has developed intelligent control algorithms for energy systems and conducted simulations related to smart grid resilience. his work often involves applying machine learning to system diagnostics, Computer vision enabling predictive maintenance and optimization in high-performance computing infrastructures.

Impact and influence

Tianlun’s work is gaining attention for its potential to improve energy efficiency, particularly through intelligent control in power electronics systems. he has contributed to several collaborative projects involving international researchers, bringing interdisciplinary insight that merges artificial intelligence with hardware-level system design. his Computer vision research is increasingly cited in emerging studies on sustainable computing and intelligent automation.

Academic citations

Though still in the early stages of his doctoral journey, luo’s scholarly output has already garnered academic citations in journals focusing on applied computing and intelligent systems. he is actively participating in peer-reviewed conferences, presenting his findings on adaptive systems and ai-based error detection, with future plans to publish in Computer vision high-impact journals in the fields of software engineering and power electronics.

Legacy and future contributions

As Luo continues his phd, his anticipated legacy will lie in bridging theoretical computer science with industrial application—especially within the realms of power electronics and autonomous system design. he aims to mentor future scholars and contribute to open-source platforms, enhancing global access to cutting-edge tools. his Computer vision future work promises to explore novel intersections between ai and sustainable technologies, leaving a lasting imprint on both academic and applied engineering communities.

Notable Publications

  1. Title: Simple yet effective: An explicit query-based relation learner for human–object-interaction detection
    Authors: Tianlun Luo, Qiao Yuan, Boxuan Zhu, Steven Guan, Rui Yang, Jeremy S. Smith, Eng Gee Lim
    Journal: Neurocomputing
  2. Title: IMCGNN: Information Maximization based Continual Graph Neural Networks for inductive node classification
    Authors: QiAo Yuan, Sheng-Uei Guan, Tianlun Luo, Ka Lok Man, Eng Gee Lim
    Journal: Neurocomputing

Conclusion

Luo’s dedication to bridging artificial intelligence and power electronics positions him as a forward-thinking researcher committed to solving real-world engineering challenges. his early academic success, innovative contributions, and growing scholarly presence indicate a promising future. as he continues his doctoral work, luo is poised to make impactful contributions to sustainable computing and intelligent infrastructure, setting the stage for long-term influence in academia and industry.

Mr. Huixian Lin – Deep Learning – Best Researcher Award

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Mr. Huixian Lin - Deep Learning - Best Researcher Award

Guangdong Ocean University - China

Author Profile

SCOPUS

Summary

Mr. Huixian Lin is a dedicated full-time teacher at Guangdong Ocean University with a master's degree in Computer Science and Technology. His academic focus lies in image processing, machine learning, and the integration of power electronics in intelligent systems. He has made notable contributions, including enhancing the YOLOv5s model for degraded image detection and publishing three SCI-indexed research papers. His teaching and research work reflects a commitment to advancing practical, AI-driven solutions in real-world environments.

Early academic pursuits

Mr. Huixian Lin began his academic journey with a strong inclination toward computational sciences. His commitment to technological excellence led him to pursue a Master of Science degree in Computer Science and Technology from Guangdong Ocean University, completed in 2023. During his academic training, he cultivated a keen interest in image processing, deep learning machine learning, and system optimization. His foundational knowledge in applied mathematics, algorithms, and power electronics laid a strong base for future research and teaching.

Professional endeavors

Since 2023, Mr. Lin has been serving as a full-time teacher at the College of Mathematics and Computer Science, Guangdong Ocean University. His teaching methodology emphasizes practical applications of theoretical concepts, especially in areas like deep learning intelligent systems and computer vision. In his short tenure, he has made significant strides in mentoring undergraduate students and guiding them through hands-on research in modern computing fields, including power electronics applications in automation systems.

Contributions and research focus

Mr. Lin’s most notable academic contribution is his proposed improvement of the YOLOv5s model, targeting enhanced detection of degraded images—a challenge in both surveillance and industrial inspection sectors. His research integrates advanced machine learning with classical image processing techniques. He has authored 3 SCI-indexed papers in reputed journals, deep learning showcasing innovations that have practical implications in smart sensing, automation, and power electronics interface systems. These contributions reflect a commitment to solving real-world problems using intelligent technology frameworks.

Impact and influence

Mr. Lin's work has been recognized within academic circles for its technical accuracy and applicability. His adaptations to image recognition models have improved reliability in noisy environments, offering benefits to sectors like security surveillance, medical diagnostics, and automated inspection systems. As a young academic, deep learning his influence is growing, especially among peers focusing on embedded systems, AI algorithms, and sensor-integrated power electronics.

Academic citations

Although at an early stage of his academic journey, Mr. Lin's publications have begun to attract citations in related research fields. His work is cited for contributions to degraded image classification, neural network efficiency optimization, deep learning and algorithm adaptability in constrained environments. This emerging scholarly attention suggests a promising trajectory in the years ahead.

Legacy and future contributions

Looking ahead, Mr. Lin aspires to build a legacy in the intersection of artificial intelligence, image processing, and real-time computing. He aims to extend his research toward more adaptive and energy-efficient machine learning models with industrial deployment in mind. His future contributions are likely to focus on smarter integration of visual data into automated decision-making systems, deep learning particularly where power electronics and AI co-evolve. Through his ongoing role at Guangdong Ocean University, he is poised to nurture future innovators and push the boundaries of applied computing.

Notable Publications

Effective superpixel sparse representation classification method with multiple features and L 0smoothing for hyperspectral images.

Conclusion

In the early stages of his academic career, Mr. Huixian Lin has already made a meaningful impact through research and instruction. His innovative approach to machine learning and image recognition, especially when combined with power electronics, positions him as a promising figure in the field. With a growing scholarly presence and a passion for technological development, Mr. Lin is set to contribute significantly to the future of smart computing and interdisciplinary research.