Elly Ogutu Isaya | Mechanical Engineering | Research Excellence Award

Mr. Elly Ogutu Isaya | Mechanical Engineering | Research Excellence Award

Budapest University of Technology and Economics | Hungary

Ogutu Isaya Elly is a mechanical engineering researcher and PhD candidate at the Géza Pattantyús-Ábrahám Doctoral School of Mechanical Sciences, Budapest University of Technology and Economics (BME), specializing in advanced manufacturing and micromachining. He earned a Master’s degree in Mechanical Engineering from Huazhong University of Science and Technology (HUST), China and a Bachelor’s degree in Mechanical Engineering from Jomo Kenyatta University of Agriculture and Technology (J.K.U.A.T), Kenya. His academic experience includes active participation in nationally funded Hungarian research projects focused on AI-based predictive modeling for machining quality and on transient deformation, thermal, and tribological phenomena in fine machining of high-hardness metals. His research interests center on micromachining processes, burr formation mechanisms, and the integration of machine learning within Industry 4.0 manufacturing frameworks. His recent work on burr-size prediction and optimization provides industry-ready solutions to reduce deburring costs and improve surface integrity. He is currently a nominee for the Best Research Article Award, reflecting the applied impact and relevance of his research to modern manufacturing systems.

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Featured Publications

Surface Quality Prediction by Machine Learning Methods and Process Parameter Optimization in Ultra-Precision Machining of AISI D2 Using CBN Tool
U.L. Adizue, A.D. Tura, E.O. Isaya, B.Z. Farkas, M. Takács,
The International Journal of Advanced Manufacturing Technology, 129(3), 1375–1389, 2023. (Citations: 34)


Analysis, Modelling, and Optimization of Force in Ultra-Precision Hard Turning of Cold Work Hardened Steel Using the CBN Tool
O.I. Elly, U.L. Adizue, A.D. Tura, B.Z. Farkas, M. Takács,
Journal of the Brazilian Society of Mechanical Sciences and Engineering, 46, 2024. (Citations: 8)


Optimization of Ultra-Precision CBN Turning of AISI D2 Using Hybrid GA-RSM and Taguchi-GRA Statistical Tools
A.D. Tura, E.O. Isaya, U.L. Adizue, B.Z. Farkas, M. Takács,
Heliyon, 10(11), 2024. (Citations: 5)


Feed Optimization Based on Force Modelling and TLBO Algorithm in Milling Al 7075
O.I. Elly, Y. Yin,
Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2024. (Citations: 2)


Burr Size Minimization Using a Surrogate Artificial Neural Network (ANN) Assisted Multi-Objective Genetic Algorithm (MOGA) in Micromilling Hardened AISI H13
O.I. Elly, M. Takács, B.Z. Balázs,
The International Journal of Advanced Manufacturing Technology, 2026. (In Press)

Cai Xuan | Engineering and Technology | Research Excellence Award

Mr. Cai Xuan | Engineering and Technology | Research Excellence Award

Beihang University | China

Cai Xuan is a doctoral researcher in transportation engineering with a strong background in mechanical engineering and a research focus on autonomous driving safety, intelligent testing, and AI-driven decision making. He is currently pursuing a PhD at Beihang University after completing his master’s and bachelor’s degrees in Mechanical Engineering at Hunan University. His research experience spans adversarial reinforcement learning, large language model–based scenario generation, energy management for hybrid vehicles, and safety-critical testing frameworks for autonomous vehicles. He has served as lead or co-author on multiple peer-reviewed publications in high-impact journals and top-tier conferences, including IEEE Transactions on Intelligent Vehicles, Energy, Automotive Innovation, and IEEE Intelligent Vehicles Symposium. His scholarly output has resulted in 7 published papers, an h-index of 3, and over 16citations, reflecting growing academic influence in intelligent transportation systems. His work has demonstrated significant improvements in robustness, vulnerability discovery, and real-time performance of autonomous and electrified vehicle systems. He is the recipient of multiple academic scholarships and competitive research awards at both undergraduate and graduate levels. Overall, his research contributes practical and theoretical advances toward safer, more reliable, and intelligent mobility systems.

Citation Metrics (scopus)

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Featured Publications


Koma: Knowledge-driven Multi-agent Framework for Autonomous Driving with Large Language Models
K. Jiang, X. Cai, Z. Cui, A. Li, Y. Ren, H. Yu, H. Yang, D. Fu, L. Wen, P. Cai.
IEEE Transactions on Intelligent Vehicles, 2024.


Adversarial Stress Test for Autonomous Vehicle via Series Reinforcement Learning Tasks with Reward Shaping
X. Cai, X. Bai, Z. Cui, P. Hang, H. Yu, Y. Ren.
IEEE Transactions on Intelligent Vehicles, 2024. (Citations: 15)


Text2Scenario: Text-driven Scenario Generation for Autonomous Driving Test
X. Cai, X. Bai, Z. Cui, D. Xie, D. Fu, H. Yu, Y. Ren.
Automotive Innovation, 2026, 1–26. (Citations: 14)

Biomimetic Multi-UAV Swarm Exploration with U2U Communications Under Resource Constraints
Y. Huang, H. Wang, X. Bai, X. Cai, H. Yu, Y. Ren.
IEEE Transactions on Vehicular Technology, 2025. (Citations: 5)

Pan Li | Chemistry and Materials Science | Best Researcher Award

Dr. Pan Li | Chemistry and Materials Science | Best Researcher Award

Academy of Military Science of the People’s Liberation Army | China

Li Pan is a PhD candidate and active researcher at the Academy of Military Sciences, specializing in computational and experimental materials science. Her academic training and doctoral education are grounded in advanced materials engineering, with a strong emphasis on first-principles calculations and microstructural analysis of alloys. Through her research experiencez, she has developed a solid theoretical and practical understanding of alloy design, phase stability, and structure–property relationships at the atomic and microstructural scales. Li Pan has authored more than 10 peer-reviewed scientific articles published in high-impact journals, including Nature Communications, reflecting the quality and relevance of her work. In addition to journal articles, she has authored one scholarly monograph, highlighting her ability to synthesize complex scientific knowledge into cohesive academic work. Her research interests include density functional theory, alloy microstructure evolution, and computational materials modeling. She has received academic recognition for her research productivity and innovation during her doctoral studies. Overall, Li Pan represents an emerging scholar in materials science whose work contributes to advancing the fundamental understanding and design of advanced alloy systems.

Profile : Orcid

Featured Publications

Pan, L., Huang, L., Wang, X., Xu, W., Zhou, Y., & Chen, J. (2025). Pressure effect on structural, mechanical, electronic and thermodynamic properties of Cr–Co sigma phase using first-principles method. Philosophical Magazine.

Pan, L., Chen, J., Huang, L., & Zhang, J. (2024). First-principles study of structural, mechanical, electronic properties and Debye temperature of NbCo₂ Laves phases under pressure. Physica B: Condensed Matter, —, 415683.

Pan, L., Chen, J., Huang, L., & Zhang, J. (2023). Site occupancy and electronic properties of NbCo₂ Laves phases doped with Re. Computational and Theoretical Chemistry, —, 114389.

Pan, L., Huang, L., Chen, J., & Zhang, J. (2023). Site occupancy of Ru in μ phases: A density functional theory study. International Journal of Modern Physics B, —, 23502648.

Pan, L., Huang, L., Chen, J., & Zhang, J. (2022). First-principles study of Co₂₁W₁₈ with pressure effect: Structural, mechanical, electronic properties and Debye temperature. Materials Today Communications, —, 104276.

Liu Ying | Mechanical Engineering | Research Excellence Award

Dr. Liu Ying | Mechanical Engineering | Research Excellence Award

East China Jiaotong University | China

Ying Liu is a dedicated researcher and Lecturer specializing in vehicle engineering with a strong academic trajectory and growing research impact, reflected in an h-index of 2, 4 published documents, and 14 citations across indexed platforms. She earned a combined Master’s and PhD degree in Mechanical Engineering from Shanghai University, followed by a Bachelor’s degree in Mechanical Design, Manufacturing and Automation from Changchun Institute of Technology. Her professional career includes serving as a Lecturer at East China Jiaotong University, where she contributes to teaching, mentoring, and interdisciplinary research. Her work focuses on target optimization, image detection, reinforcement learning, computer vision, intelligent control, and smart vehicle technologies. She has completed five research projects, contributed to two national-level and multiple provincial and horizontal projects, and actively engages in consultancy with ten industry-linked initiatives. She has authored seven SCI-indexed papers, produced twenty-five patents, and participated in major scientific collaborations including a project funded with 5 million yuan. As a recipient of Jiangxi’s Early-Career Young Talents Program, she continues to advance innovation in intelligent vehicle systems. She remains committed to impactful research, advancing engineering applications, and contributing to societal and technological development.

Profile : Scopus

Featured Publications

Liu, Y., & [Co-author(s) if any]. (2025). Continuous path tracking of robots based on positioning error compensation with iterative learning control. IEEE Transactions on Instrumentation and Measurement.

Avinash Kumar | Biology and Life Sciences | Best Researcher Award

Assist. Prof. Dr. Avinash Kumar | Biology and Life Sciences | Best Researcher Award

Long Island University Arnold and Marie Schwartz College of Pharmacy and Health Sciences | United States

Assist. Prof. Dr. Avinash Kumar, Ph.D., is an Assistant Professor at the Arnold & Marie Schwartz College of Pharmacy and Health Sciences, Long Island University, Brooklyn, NY. With a Ph.D. in Biotechnology from the University of Pune, India, his doctoral work focused on biochemical and biophysical characterization of class II α-mannosidases. He completed postdoctoral research at the University of Mississippi Medical Center and National Center for Cell Science, India, investigating transcriptional and post-translational programs driving prostate cancer progression. His research aims to develop personalized and precision medicine strategies targeting metastatic and high-risk prostate cancer, including health disparities in African American men. Dr. Kumar utilizes high-throughput single-cell genomics, transcriptomics, and proteomics in combination with genetically engineered and xenograft mouse models, patient tissues, and complementary cell line studies. He has mentored numerous graduate, undergraduate, and Pharm.D. students, directed the Molecular Imaging Core at LIU, and actively serves on institutional committees and as a reviewer for top journals. Dr. Kumar has published 28 peer-reviewed articles, 5 book chapters, and over 20 conference abstracts, with an h-index of 17 , 873 citations, and 29 publications. He has received multiple fellowships, awards, and research grants and continues to advance translational cancer therapeutics through rigorous preclinical and mechanistic studies.

Profile : Scopus | Orcid

Featured Publications

“Reprogrammed Lipid Metabolism-Associated Therapeutic Vulnerabilities in Prostate Cancer”

“The Therapeutic Efficacy and Mechanism of Action of Gnetin C, a Natural Compound from the Melinjo Plant,     Preclinical Mouse Model of Advanced Prostate Cancer”

“AI & experimental-based discovery and preclinical IND-enabling studies of selective BMX inhibitors for       development of cancer therapeutics”

“Data from Dietary Pterostilbene for MTA1-Targeted Interception in High-Risk Premalignant Prostate Cancer”

“Supplementary Figure 1-2; Supplementary Table 1-4 from Dietary Pterostilbene for MTA1-Targeted Interception   in   High- Risk Premalignant Prostate Cancer”