Wolfgang Härdle | Industrial and Manufacturing Applications | Outstanding Contribution Award

Prof. Dr. Wolfgang Härdle | Industrial and Manufacturing Applications | Outstanding Contribution Award

Humboldt-Universität zu Berlin | IDA Inst Digital Assets | Germany

Prof. Wolfgang Karl Härdle, Ladislaus von Bortkiewicz Professor of Statistics at Humboldt-Universität zu Berlin, is an internationally recognized leader in modern statistics, digital finance, machine learning, and smart data analytics. With an exceptional body of work spanning more than three decades, he has shaped the global landscape of statistical science through groundbreaking contributions to nonparametric statistics, multivariate analysis, econometrics, and quantitative finance. His academic influence is reflected in an outstanding scholarly output of 994 documents which have collectively amassed over 48,217 citations, supported by a remarkable h-index of 93 and i10-index of 311.A pioneer of applied nonparametric regression Prof. Härdle’s seminal works such as Applied Nonparametric Regression Applied Multivariate Statistical Analysis and Nonparametric and Semiparametric Models remain foundational references used across statistics econometrics  and data science. His highly cited research on smoothing techniques bandwidth selection average derivatives and optimal smoothing rules has advanced the theoretical and practical understanding of regression modeling. Additionally his contributions to wavelets financial econometrics copula theory tail-risk modeling and network risk analysis have had significant implications for financial stability risk assessment and decision analytics.Prof. Härdle has collaborated extensively with leading scholars worldwide producing influential publications that continue to guide contemporary methodological innovations. His interdisciplinary reach includes co-authoring major handbooks such as the Springer Handbook of Computational Statistics and the Handbook of Data Visualization which broaden access to advanced analytical methodologies for global researchers and practitioners.Beyond scholarly impact his work plays a vital societal role by strengthening statistical foundations for digital finance  high-dimensional modeling and smart data solutions helping institutions and industries make informed data-driven decisions. Through his research leadership mentorship and high-impact publications Prof. Härdle continues to advance statistical science and shape the future of data-centric research worldwide.

Profile:  Googlescholar

Featured Publications

1.Härdle, W. (1990). Applied nonparametric regression. Cambridge University Press. Cited By: 6559

2.Härdle, W., & Simar, L. (2007). Applied multivariate statistical analysis. Springer Berlin Heidelberg.Cited By: 3465

3.Härdle, W., Werwatz, A., Müller, M., & Sperlich, S. (2004). Nonparametric and semiparametric models. Springer Berlin Heidelberg.Cited By: 2006

4.Härdle, W., & Mammen, E. (1993). Comparing nonparametric versus parametric regression fits. The Annals of Statistics, 21(4), 1926–1947.Cited By: 1558

5.Härdle, W. (2012). Smoothing techniques: With implementation in S. Springer Science & Business Media.Cited By: 1529

Prof. Wolfgang Karl Härdle’s pioneering contributions in nonparametric statistics, digital finance, and machine learning have transformed data-driven decision-making across science, industry, and global financial systems. His methods for robust modeling, risk analytics, and smart data solutions empower researchers, policymakers, and institutions to navigate complex, high-dimensional data with greater accuracy, transparency, and resilience. He envisions a future where advanced statistical intelligence drives safer financial ecosystems and more equitable, evidence-based innovation worldwide.

Gehendra Sharma | Manufacturing Science | Best Researcher Award

Mr. Gehendra Sharma | Manufacturing Science | Best Researcher Award

Research Engineer at Mississippi State University, United States

Mr. Gehendra Sharma is a mechanical engineer and research professional with extensive experience in designing, optimizing, and analyzing complex mechanical systems. He has a strong background in coupled system design, robust design, surrogate modeling, finite element modeling, data analysis, and machine learning approaches applied to engineering design. Over his career, he has contributed to national defense projects, biomedical device development, and advanced manufacturing research, demonstrating his ability to translate theoretical methods into practical solutions. He has an impressive publication record, including research in high-quality journals and conferences, reflecting his commitment to advancing engineering knowledge. Alongside his technical expertise, he has been actively involved in mentoring students, leading academic initiatives, and volunteering in social and educational programs. His professional achievements are complemented by his dedication to teaching and knowledge sharing, making him a well-rounded researcher with strong leadership, innovation, and societal impact potential.

Professional Profile 

Google Scholar | Scopus Profile | ORCID Profile

Education

Mr. Gehendra Sharma earned his Master of Science in Mechanical Engineering from the University of Oklahoma, where he focused on designing coupled engineered systems under uncertainty and studied multi-criteria optimization, design theory, data-driven decision making, and applied statistical methods. His research involved integrating robust design methodologies into cloud-based systems to archive design knowledge and support design exploration. Prior to his master’s, he completed his Bachelor of Technology in Mechanical Engineering from Motilal Nehru National Institute of Technology, where he worked on mechanization and prototyping of a domestic roti roller and studied a wide range of mechanical engineering topics including machine design, thermodynamics, fluid mechanics, material science, and computer-aided design. His academic journey has been marked by consistently high performance, merit scholarships, and practical projects that combined theoretical knowledge with hands-on design and experimentation, providing him with a strong foundation in engineering principles, modeling, and system-level problem solving.

Professional Experience

Mr. Gehendra Sharma has worked as a research engineer at the Center for Advanced Vehicular Systems, contributing to projects that enhance defense capabilities, optimize additive manufacturing processes, and develop protective barriers and biomedical devices. He has implemented design optimization, robust design, finite element modeling, surrogate modeling, and machine learning approaches across diverse projects. His earlier experience as a graduate research assistant involved exploring robust solutions for coupled engineered systems, developing decision frameworks, and advancing composite structure design under uncertainty. He has also interned at Tata Research Development & Design Centre, applying robust design methods to composite structures, thermal power plant modeling, and gearbox analysis. Before his research career, he worked as a design engineer at Esco Couplings & Transmissions, leading product development, experimental testing, and manufacturing improvements. Throughout his career, he has consistently bridged academic research and industrial applications, demonstrating expertise in engineering design, analysis, prototyping, and innovation.

Research Interest

Mr. Gehendra Sharma’s research interests focus on design and optimization of mechanical and coupled systems under uncertainty, robust design exploration, surrogate modeling, finite element analysis, data-driven decision making, and machine learning applications in engineering. He has applied these methods in defense-related projects, additive manufacturing optimization, biomedical device design, and lightweight protective structures. He is particularly interested in integrating robust design methodologies with simulation, experimental testing, and predictive modeling to create efficient and reliable solutions for complex engineering problems. His work spans multi-objective optimization, system-level modeling, and development of decision support frameworks to guide engineers in exploring high-dimensional design spaces. He also explores the translation of theoretical methods into practical applications, including real-time monitoring, predictive modeling, and design automation, reflecting a commitment to advancing both the scientific understanding and industrial implementation of innovative engineering solutions.

Award and Honor

Mr. Gehendra Sharma has received multiple recognitions for his contributions to engineering research and innovation. He has been awarded cash prizes for competitions such as hydropower optimization challenges and received distinctions for his papers at international conferences. He has consistently earned merit scholarships and awards during his academic career for outstanding performance and innovation. His research projects have been recognized for excellence in design, robust optimization, and multi-objective engineering solutions. Additionally, he has been acknowledged for leadership in student committees, teaching, and mentoring roles, demonstrating a combination of technical skill and commitment to academic and community development. These awards and honors reflect both his technical expertise and his dedication to advancing engineering knowledge while contributing positively to professional and educational communities.

Research Skill

Mr. Gehendra Sharma possesses a diverse set of research skills, including design of coupled systems, robust and multi-objective design optimization, surrogate modeling, finite element analysis, data analysis, and predictive modeling using machine learning. He is proficient in programming languages such as Python, MATLAB, C, R, and VBA and is skilled in CAD and simulation tools including SolidWorks, Creo, ANSYS, Abaqus, and AutoCAD. He has experience in prototyping, experimental testing, and both destructive and non-destructive testing of components and materials. His research skills also include data-driven decision-making, algorithm development, and integrating theoretical methods into practical engineering solutions. In addition, he has mentoring and teaching skills that support knowledge transfer, enabling others to explore design problems, conduct simulations, and apply advanced methodologies, reflecting his comprehensive capability as a researcher and educator.

Publications Top Notes

Title: An ontology for representing knowledge of decision interactions in decision-based design
Authors: Z Ming, G Sharma, JK Allen, F Mistree
Year: 2020
Citation: 32

Title: A method for robust design in a coupled decision environment
Authors: G Sharma, JK Allen, F Mistree
Year: 2021
Citation: 17

Title: Template-based configuration and execution of decision workflows in design of complex engineered systems
Authors: Z Ming, G Sharma, JK Allen, F Mistree
Year: 2019
Citation: 16

Title: Data driven integrated design space exploration using iSOM
Authors: RR Sushil, M Baby, G Sharma, AB Nellippallil, P Ramu
Year: 2022
Citation: 11

Title: Design of composite structures through decision support problem and multiscale design approach
Authors: RK Pathan, SB Beemaraj, A Salvi, G Sharma, JK Allen, F Mistree
Year: 2019
Citation: 11

Title: Inverse multi-scale robust design of composite structures using design capability indices
Authors: SB Beemaraj, RK Pathan, AG Salvi, G Sharma, F Mistree, JK Allen
Year: 2020
Citation: 8

Title: Classification and execution of coupled decision problems in engineering design for exploration of robust design solutions
Authors: G Sharma, JK Allen, F Mistree
Year: 2019
Citation: 8

Title: Designing concurrently and hierarchically coupled engineered systems
Authors: G Sharma, JK Allen, F Mistree
Year: 2023
Citation: 7

Title: Exploring robust decisions in the design of coupled engineered systems
Authors: G Sharma, JK Allen, F Mistree
Year: 2023
Citation: 6

Title: Designing coupled engineered systems under uncertainty
Authors: G Sharma
Year: 2020
Citation: 5

Title: Multi-objective robust design exploration of a canine ventricular shunt for managing hydrocephalus
Authors: G Sharma, AB Nellippallil, R Yingling, NY Lee, A Shores, R Miralami
Year: 2021
Citation: 3

Title: Thermal Calibration of Finite Element Models in Wire Arc Directed Energy Deposition of ER-120S-G Using Thermocouples and Infrared Cameras
Authors: J Bassett, G Sharma, J Xie, J Storey, HG Kim, T Stone, H Dozier, S Mun
Year: 2025
Citation: 2

Conclusion

Mr. Gehendra Sharma stands out as a deserving candidate for the Best Researcher Award due to his impactful contributions to engineering research, defense applications, and innovative design methods that address real-world challenges. His work demonstrates a balance of academic excellence, industrial relevance, and societal benefit, particularly through projects in national defense, biomedical engineering, and advanced manufacturing. With his strong foundation in research and leadership, he has the potential to become a leading figure in multidisciplinary innovation and global collaborations, making him a valuable contributor to the advancement of science and technology.

Dr. Caizhi Li | Industrial | Industry Innovator Award

Dr. Caizhi Li | Industrial | Industry Innovator Award

Doctorate at Air Force Engineering University, China

👨‍🎓 Profiles

Scopus

Orcid

📝 Summary

Dr. Caizhi Li is a dedicated researcher in aeronautical and astronautical sciences, specializing in aerospace composites, wave-absorbing materials, and artificial intelligence applications. With a strong foundation in electrical engineering, aeronautical engineering, and cutting-edge non-destructive testing methods, Dr. Li has contributed significantly to advanced damage detection and intelligent recognition technologies.

🎓 Education

  • PhD in Aeronautical and Astronautical Sciences and Technology
    Air Force Engineering University (2022.03–Present)
  • Master’s in Aeronautical Engineering
    Air Force Engineering University (2019.09–2022.01)
  • Bachelor’s in Electrical Engineering and Automation
    Air Force Engineering University (2015.09–2019.06)

💼 Professional Experience

    • Foundation of National Major Science and Technology Projects of China (No. 2019-Ⅵ-0015-0130)
    • National Science and Technology Major Project (J2019-III-0009-0053)

🔬 Research Interests

  • Aerospace Composites & Wave-Absorbing Materials
    • Damage mechanisms and detection.
  • Non-Destructive Testing (NDT)
    • Certified in Ultrasonic NDT (Level 2), Infrared NDT, and Weak Magnetic NDT.
  • Artificial Intelligence
    • Applications in object detection, image segmentation, and signal recognition.

 

Publications

TranSR-NeRF: Super-resolution neural radiance field for reconstruction and rendering of weak and repetitive texture of aviation damaged functional surface

  • Authors: HU, Q., XU, H., WEI, X., HAN, X., LI, C.
  • Journal: Chinese Journal of Aeronautics
  • Year: 2024

Aeroengine Blades Damage Detection and Measurement Based on Multimodality Fusion Learning

  • Authors: Wu, X., Wei, X., Xu, H., He, W., Zhou, L.
  • Journal: IEEE Transactions on Instrumentation and Measurement
  • Year: 2024

PointCNT: A One-Stage Point Cloud Registration Approach Based on Complex Network Theory

  • Authors: Wu, X., Wei, X., Xu, H., Yin, Y., He, W.
  • Journal: Remote Sensing
  • Year: 2023

Study on intelligent and visualization method of ultrasonic testing of composite materials based on deep learning

  • Authors: Hu, Q., Wei, X., Guo, H., He, W., Pei, B.
  • Journal: Applied Acoustics
  • Year: 2023

Study on the impact erosion wear resistance and damage evolution of TiN films under different impact cycles

  • Authors: Wang, S., He, W., Zhang, H., Li, C., Zhang, Y.
  • Journal: Thin Solid Films
  • Year: 2023

Assoc Prof Dr. Shiwei Liu | Industrial | Best Researcher Award

Assoc Prof Dr. Shiwei Liu | Industrial | Best Researcher Award

Shiwei Liu at Huazhong Agricultural University, China

Profiles

Scopus

Orcid

Education

  • Ph.D. in Mechanical Engineering – Huazhong University of Science and Technology (HUST), 2019
  • M.E. in Measurement Technology and Instrumentation – HUST, 2016
  • B.E. in Mechanical Design Manufacturing and Automation – Hubei University of Technology, 2014

💼 Professional Experience

Assoc Prof Dr. Shiwei Liu has extensive professional experience in the field of engineering and research. He has been an Associate Professor and Doctoral Supervisor at Huazhong Agricultural University since April 2022, leading the Intelligent Nondestructive Testing and Digital Equipment Group. Prior to this role, he served as a Postdoctoral Research Fellow at Huazhong University of Science and Technology from June 2019 to March 2022, focusing on advanced nondestructive testing methodologies. Liu earned his Ph.D. in Mechanical Engineering from HUST in 2019, along with a Master’s degree in Measurement Technology and Instrumentation. His academic foundation includes a Bachelor’s degree in Mechanical Design Manufacturing and Automation from Hubei University of Technology. Throughout his career, he has made significant contributions to research, teaching, and the development of innovative technologies.

🔬 Research Interests

  • Nondestructive testing (NDT) techniques
  • Structural health monitoring
  • Advanced sensor development
  • AI algorithms and pattern recognition

🏆 Honors & Awards

  • Best Researcher Award, International Research Awards on High Energy Physics and Computational Science, 2024
  • Best Paper Award, ICMSD 2023
  • National Scholarship for Doctoral Candidates, Ministry of Education of China, 2018

 

Publications

Wavelet structuring element-based morphological filtering method in wire rope inspection signal denoising

  • Authors: Liu, S., Shan, L., Liu, Y., Sun, Y., He, L.
  • Journal: Structural Health Monitoring
  • Year: 2024

Magnetic focusing sensor and its characterizations of defect non-destructive testing for ferromagnetic steel plate

  • Authors: Liu, S., Hua, X., Liu, Y., Lin, W., Wang, Q.
  • Journal: NDT and E International
  • Year: 2024

Nondestructive testing of runny salted egg yolk based on improved ConvNeXt-T

  • Authors: Chen, H., Chang, Y., Chen, Y., Liu, S., Wang, Q.
  • Journal: Journal of Food Science
  • Year: 2024

Brownian motion based multi-objective particle swarm optimization methodology and application in binary classification

  • Authors: Liu, S., Liu, Y., Wang, Q., Sun, Y., He, L.
  • Journal: Applied Soft Computing
  • Year: 2024

Hybrid Conditional Kernel SVM for Wire Rope Defect Recognition

  • Authors: Liu, S., Liu, Y., Shan, L., Sun, Y., He, L.
  • Journal: IEEE Transactions on Industrial Informatics
  • Year: 2024

Prof Dr. Imane Nait Irahal | Biomedical | Best Scholar Award

Prof Dr. Imane Nait Irahal, Biomedical , Best Scholar Award

 Mustapha Serhani at Université Hassan II de Casablanca, France

Professional Profile

Summary:

Dr. Imane Nait Irahal is a skilled biochemist with expertise in mitochondrial stress control, molecular diagnostics of cancer, and biochemistry analysis techniques. She holds a doctoral degree in Biochemistry from Hassan II University of Casablanca and has conducted extensive research in medical biology and general biology.

🎓 Education:

  • Ph.D. in Biochemistry, Hassan II University of Casablanca, 2018-2022
  • Master’s degree in Medical Biology, Hassan II University of Casablanca, 2016-2018
  • Bachelor’s degree in General Biology, Hassan II University of Casablanca, 2013-2016

💼 Professional Experience:

  • Medical Analysis Laboratory El Joulane (2015, 2018, 2021-2021)
    • Specialization in Biochemistry, Microbiology, and Immunology analysis techniques.
  • Laboratoire Santé et Environnement, UHII/FSAC (2018)
    • Conducted research on extraction techniques and biological activity of essential oils.
  • Centre Hospitalier Universitaire Ibn Rochd (2021)
    • Worked in anatomical pathology focusing on histology, cytology, immunohistochemistry, and molecular diagnostics of cancer.

🔬 Research Interest:

Dr. Nait Irahal’s research interests include mitochondrial dysfunction, cellular and molecular biology, and the biochemical mechanisms underlying disease pathology. She has expertise in enzyme assays, flow cytometry, and confocal microscopy, contributing significantly to the understanding of cellular processes and disease mechanisms.

Publications Top Noted:

Paper Title: Exploration of Na2CaP2O7 as a Nanocatalyst for Eco-conscious Synthesis of 4H-Pyran Derivatives: Computational Examination Utilizing DFT and Docking …
  • Authors: Redouane Achagar, Abdelhakim Elmakssoudi, Abderrahmane Thoume, Zouhair Ait-Touchente, Abdellah Anouar El Foulani, Imane Nait Irahal, Zineb Loukhmi, Mohamed Zahouily, Mohamed M Chehimi, Mohamed Dakir, Jamal Jamaleddine
  • Pages: 1-20
  • Year: 2024
Paper Title: Macromolecules from mushrooms, venoms, microorganisms, and plants for diabetes treatment-Progress or setback?
  • Authors: Asmaa Chbel, Ayoub Lafnoune, Imane Nait Irahal, Noureddine Bourhim
  • Journal: Biochimie
  • Year: 2024
Paper Title: The chemical composition, in vitro, and in silico studies of Lavandula mairei essential oil
  • Authors: Fatima Ez-zahra Ousaid, Ismail Guenaou, Imane Nait Irahal, Fatima Azzahra Lahlou, Ahmed Errami, Lamiaa Ait Si, Fatima Abdou-Allah, Khadija Ridaoui, Yassine Zouheir, Fouzia Hmimid, Noureddine Bourhim
  • Year: 2024
  • Citations: 1
Paper Title: In vitro and in silico antibacterial and anti-corrosive properties of Persea americana leaves extract as an environmentally friendly corrosion inhibitor for carbon steel in a …
  • Authors: A Thoume, I Nait Irahal, N Benzbiria, D Benmessaoud Left, R Achagar, A Elmakssoudi, M Dakir, M Azzi, N Bourhim, M Zertoubi
  • Year: 2023
  • Citations: 9
Paper Title: Therapeutic Potential of Clove Essential Oil in Diabetes: Modulation of Pro‐Inflammatory Mediators, Oxidative Stress and Metabolic Enzyme Activities
  • Authors: Imane Nait Irahal, Dounia Darif, Ismail Guenaou, Fouzia Hmimid, Fatima Azzahra Lahlou, Fatima Ez‐zahra Ousaid, Fatima Abdou‐Allah, Lamiaa Aitsi, Khadija Akarid, Noureddine Bourhim
  • Year: 2023
  • Citations: 7

Prof Dr. Mustapha Serhani | Industrial | Best Researcher Award

Prof Dr. Mustapha Serhani, Industrial , Best Researcher Award

 Mustapha Serhani at Université Moulay Ismail de Meknès, Morocco

Professional Profile

🌟 Summary:

Prof. Dr. Mustapha Serhani is a distinguished professor specializing in Mathematics with a focus on Optimization, Control Theory, and Numerical Analysis. He has significant teaching and research experience, contributing to various international institutions and scientific projects.

🎓 Education:

  • Ph.D. in Mathematics: Optimization and Optimal Control, Nonsmooth Analysis.
  • Master’s Degree in Mathematics: Numerical Analysis and Optimization.
  • Bachelor’s Degree in Applied Mathematics.
  • High School Diploma in Mathematical Sciences.

💼 Professional Experience:

  • Visiting Professor at IMSP, Benin (2019-2022).
  • Visiting Professor at the Institute of Mathematics, University of Burgundy, France (2011).
  • Part-time Lecturer at ENSAM Meknès, Royal Military Academy of Meknès, and multiple faculties in Morocco.
  • Postdoctoral Researcher at INRIA Sophia Antipolis, Nice, France (2003).

🔬 Research Interest:

  • Optimal Control and Calculus of Variations.
  • Nonsmooth Analysis.
  • Dynamical Systems: Modeling, Analysis, and Control with applications in Biology and Environmental Systems.

Skills:

  • Programming: C, C++.
  • Software: Matlab, Maple, LaTeX.

📖 Publications Top Noted:

Paper Title: Approximation of the HJB viscosity solutions in differential inclusion optimal control with state constraint
  • Authors: Serhani, M., Raissi, N.
  • Journal: Optimization
  • Year: 2024
Paper Title: Stability and optimal control of a prey–predator model with prey refuge and prey infection
  • Authors: Lazaar, O., Serhani, M.
  • Journal: International Journal of Dynamics and Control
  • Year: 2023
  • Citations: 1
Paper Title: On the Stability Analysis of a Reaction-Diffusion Predator-Prey Model Incorporating Prey Refuge
  • Authors: Lazaar, O., Serhani, M., Alla, A., Raissi, N.
  • Journal: International Journal of Applied and Computational Mathematics
  • Year: 2022
  • Citations: 2
Paper Title: Mathematical modeling of COVID-19 spreading with asymptomatic infected and interacting peoples
  • Authors: Serhani, M., Labbardi, H.
  • Journal: Journal of Applied Mathematics and Computing
  • Year: 2021
  • Citations: 33
Paper Title: Chemotherapy and Immunotherapy for Tumors: A Study of Quadratic Optimal Control
  • Authors: Sabir, S., Raissi, N., Serhani, M.
  • Journal: International Journal of Applied and Computational Mathematics
  • Year: 2020
  • Citations: 8