Birgitte Ahring | Engineering and Technology | Best Researcher Award

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Prof. Birgitte Ahring | Engineering and Technology | Best Researcher Award

Professor ,Washington State University ,United States

Dr. Birgitte Kiær Ahring is a distinguished global expert in biofuels, renewable energy, and clean technologies. Currently a Professor at Washington State University (WSU) and Head of the BioScience & Technology Group at the Bioproducts, Science & Engineering Laboratory (BSEL), she has led pioneering research in cellulosic ethanol, biogas, and renewable natural gas. With a career spanning decades, she has held prominent roles across academia, industry, and policy—including as founder of BioGasol Aps and advisor to international organizations such as the UNDP and World Bank. Dr. Ahring’s leadership in Denmark and the U.S. has driven the advancement of sustainable energy systems globally. Her commitment to translating science into practice has earned her numerous accolades, including Washington State’s Research Excellence Award and a gubernatorial honor as “Washingtonian for the Day.” With over 555 scientific contributions and 11 patents, she remains a driving force in the bioeconomy and environmental innovation.

Professional Profile

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🎓 Education

Dr. Birgitte Kiær Ahring holds a Ph.D. in a life sciences field related to biotechnology or bioengineering, though her exact alma mater and thesis details are not listed. Her academic trajectory is rooted in biotechnology and chemical/biological engineering, fields that underpin her extensive contributions to renewable energy and clean technologies. Her foundational education laid the groundwork for a multifaceted career that bridges science, engineering, policy, and industrial application. She has also been involved in academic leadership and curriculum development through professorships at institutions such as the Technical University of Denmark (DTU), University of California, Los Angeles (UCLA), and Washington State University. Her interdisciplinary background and international engagements—ranging from Denmark to the U.S., and from Africa to Asia—reflect a rich academic foundation and lifelong commitment to sustainable energy research and education.

💼 Experience

Dr. Ahring’s professional journey reflects over three decades of leadership in biotechnology and renewable energy. Since 2008, she has served as Professor at WSU and previously directed the BSEL, where she established state-of-the-art research facilities. She founded and led BioGasol Aps and was CEO of the Maxifuel Pilot Plant in Denmark. From 2002–2008, she led the Danish Centre for Biofuels and BST division at DTU. At UCLA, she served as Professor of Civil & Environmental Engineering. Her governmental and advisory roles include being a Board Member of Energinet.dk and a consultant to USDA and multiple UN agencies. She has contributed to renewable energy implementation across Latin America, Africa, and Asia. She continues to advise research campaigns and editorial boards internationally. Through this experience, she has merged policy, practice, and research into a cohesive and influential professional impact.

🏆 Awards and Honors

Prof. Birgitte Ahring has earned numerous prestigious awards that honor her transformative research and global influence in bioengineering. In 2008, she received the Washington State Star Researcher Award valued at $2.5 million for excellence in renewable energy innovation. In 2021, she was recognized with the WSU Chancellor’s Distinguished Research Excellence Award. She was named “Washingtonian for the Day” by Governor Jay Inslee in 2022, acknowledging her service to the state’s clean energy transition. In 2023, she received the Anjan Boise Outstanding Research Award, and in 2024, she earned WSU’s Research Excellence Award. These accolades reflect her leadership in scientific discovery, commercialization, and sustainability-focused innovation. Additionally, her numerous editorial and board appointments in academia and industry further affirm her authority in the global bioeconomy and her role as a mentor and policy influencer.

🔍 Research Focus

Prof. Ahring’s research centers on clean technology for biofuels, biochemicals, and renewable natural gas (RNG). She is a world leader in cellulosic ethanol production, thermophilic anaerobic digestion, and advanced wet oxidation (AWOEx) pretreatment technologies. Her work explores the decarbonization of energy systems through biological and chemical conversion of lignocellulosic biomass, waste feedstocks, and CO₂ into fuels and valuable bio-products. She is especially focused on microbial consortia engineering and syngas fermentation to develop sustainable aviation fuel (SAF) and medium-chain volatile fatty acids. She has significantly advanced microbial hydrogen kinetics and homoacetogenesis, aiming to optimize the energy yields and carbon efficiencies in bioreactors. Her integrated approach—spanning lab research, pilot plants, and industrial applications—bridges science, engineering, and policy. Through over 555 publications and collaborative global research, Prof. Ahring is reshaping bioresource technology and offering scalable solutions for climate-resilient energy systems.

📚 Publication Top Notes

 Membrane Technologies for Separating Volatile Fatty Acids Produced Through Arrested Anaerobic Digestion: A Review

  • Journal: Clean Technologies, June 2025

  • Authors: Angana Chaudhuri, Budi Mandra Harahap, Birgitte K. Ahring

  • Summary:
    This review explores state-of-the-art membrane-based separation technologies for volatile fatty acids (VFAs) derived from arrested anaerobic digestion. It emphasizes operational efficiency, selectivity, and integration potential in biorefineries, highlighting nanofiltration, pervaporation, and forward osmosis as promising routes for sustainable VFA recovery.

Advancing Thermophilic Anaerobic Digestion of Corn Whole Stillage: Lignocellulose Decomposition and Microbial Community Characterization

  • Journal: Fermentation, June 2024

  • Authors: Alnour Bokhary, Fuad Ale, Richard Garrison, Birgitte K. Ahring

  • Summary:
    The study investigates thermophilic anaerobic digestion (AD) of corn whole stillage, focusing on lignocellulosic breakdown and microbial dynamics. It reveals enhanced methane yield and stable digestion due to synergistic microbial interactions, underlining the importance of community structure in optimizing AD processes.

 Acetate Production by Moorella thermoacetica via Syngas Fermentation: Effect of Yeast Extract and Syngas Composition

  • Journal: Fermentation, September 2023

  • Authors: Budi Mandra Harahap, Birgitte K. Ahring

  • Summary:
    This paper examines acetate production from syngas using Moorella thermoacetica. It discusses how varying yeast extract concentrations and syngas composition affect yields, emphasizing the role of nutrient balance and gas ratios in optimizing microbial fermentation for bio-based acetic acid.

 Enhancing Acetic Acid Production in In Vitro Rumen Cultures by Addition of a Homoacetogenic Consortia from a Kangaroo

  • Journal: Fermentation, September 2023

  • Authors: Renan Stefanini Lopes, Birgitte K. Ahring

  • Summary:
    Innovative research demonstrating the enhancement of acetic acid production in rumen cultures by adding kangaroo-derived homoacetogens. The study also investigates methanogen inhibition and almond biochar’s role in altering fermentation profiles, suggesting applications in livestock and bioenergy.

 Acetate Production from Syngas Produced from Lignocellulosic Biomass Materials along with Gaseous Fermentation of the Syngas: A Review

  • Journal: Microorganisms, April 2023

  • Authors: Budi Mandra Harahap, Birgitte K. Ahring

  • Summary:
    This comprehensive review analyzes the full cycle of acetate production from biomass-derived syngas. It discusses gasification parameters, microbial strain selection, and bioreactor design, proposing integrated systems for sustainable acetate generation from lignocellulosic residues.

Conclusion

Engineering Award, Technology Award, Best Engineering Award, Global Technology Award, Engineering Innovation Award, Technology Excellence Award, Emerging Engineer Award, Tech Pioneer Award, Digital Engineering Award, STEM Innovation Award, Engineering and Technology Recognition, Academic Technology Award, Young Engineer Award, Women in Engineering Award, Smart Tech Award, Mechanical Engineering Award, Electrical Engineering Award, Civil Engineering Award, Software Engineering Award, Engineering Leadership Award, AI Technology Award, Robotics Award, Engineering Design Award, Sustainable Engineering Award, Innovative Engineer Award, Best Technologist Award, Engineering R&D Award, Engineering Educator Award, Future Tech Award, Engineering Breakthrough Award, Global Engineering Talent Award, Tech Achievement Award, Industry Technology Award, Next Gen Engineering Award, Excellence in Technology Award, Engineering Startup Award, Engineering Invention Award, Engineering Visionary Award, Lifetime Achievement in Engineering Award, Engineering and Technology Research Award

 

Srinivas Tadepalli | Mechanical Engineering | Best Researcher Award

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Dr. Srinivas Tadepalli | Mechanical Engineering | Best Researcher Award 

ASSISTANT PROFESSOR,  Imam Mohammad Ibn Saud Islamic University (IMSIU), Saudi Arabia

Dr. Srinivas Tadepalli is an accomplished Assistant Professor of Chemical Engineering at Imam Muhammad Bin Saud Islamic University, Saudi Arabia. With over 9 years of teaching experience and a solid research foundation, he holds a Ph.D. in Chemical Engineering from UPES, Dehradun. His research specializes in environmental engineering, particularly in water pollution, bio-remediation, and low-cost adsorption techniques for heavy metal removal. Dr. Tadepalli has contributed significantly to the academic world with 30+ peer-reviewed publications, several books, and international conference presentations. His teaching portfolio spans undergraduate and postgraduate courses, along with lab development and coordination. He is widely recognized for his innovative teaching methodologies and extensive work on adsorption modeling and simulation. Dr. Tadepalli has also been actively involved in academic coordination, technical events, and quality assurance programs. Passionate about sustainability, he continues to mentor students and contribute to environmental research through interdisciplinary collaborations worldwide.

Professional Profile

🎓 Education 

Dr. Srinivas Tadepalli’s educational journey reflects a strong foundation in engineering disciplines. He earned his Ph.D. in Chemical Engineering (2011–2017) from the University of Petroleum & Energy Studies (UPES), Dehradun, with a focus on environmental pollution and heavy metal remediation using adsorbents. Prior to that, he completed his M.Tech in Gas Engineering (2008–2010) at UPES, achieving 85.4% and submitting a thesis on the design of compact heat exchangers. He holds a B.Tech in Chemical Engineering (2004–2008) from Bapatla Engineering College, affiliated with Acharya Nagarjuna University, where he conducted a project on xylene separation using distillation and extraction. Dr. Tadepalli also excelled in his early education, scoring 88.7% in Intermediate (2002–2004) and 84% in SSC (2001–2002). Throughout his academic path, he demonstrated excellence by securing top state ranks and qualifying national-level competitive exams like GATE and PGECET.

👨‍🏫 Experience 

Dr. Tadepalli has an extensive teaching and research career spanning over 15 years, including international appointments. Since December 2019, he has been serving as Assistant Professor at Imam Mohammad Ibn Saud Islamic University, Saudi Arabia. His past appointments include Assistant Professorships at Chandigarh University, Galgotias University, Bule Hora University (Ethiopia), and NIT Warangal. He began as a teaching assistant and research fellow at UPES Dehradun (2011–2015), where he completed his doctoral research. His responsibilities have included course instruction, lab development, curriculum design, project supervision, and academic coordination. He is adept in subjects such as Thermodynamics, Mass Transfer, Instrumentation, Wastewater Treatment, and Alternative Energy Technologies. Additionally, he has coordinated technical events, handled IPR and publications, and acted as a Department Research Committee (DRC) member. His international teaching exposure and consistent research productivity distinguish him as a versatile and committed academic professional.

🔬 Research Focus 

Dr. Srinivas Tadepalli’s research is deeply rooted in environmental and chemical engineering, with a strong emphasis on adsorption technologies for heavy metal remediation from industrial effluents. His doctoral work explored low-cost biosorbents in packed bed columns, integrating FTIR analysis, AAS, and isotherm-kinetic modeling. He has developed several models like Thomas, BDST, Yoon-Nelson, and Adam–Bohart for batch and continuous adsorption processes. His current interests extend to nanomaterials, biopolymers, biochar, wastewater treatment, thermodynamic modeling, sorption capacity enhancement, and green technologies. Dr. Tadepalli’s collaborative projects have included CFD simulations, composite fiber development, and bioremediation techniques using agricultural and industrial waste. His publications also focus on kinetic studies, statistical optimization, and comparative evaluations of adsorbents. With a practical approach, he links experimental data to real-world industrial solutions. Through interdisciplinary collaborations, he aims to tackle global challenges in sustainable water treatment, waste valorization, and pollution control.

📚Publications Top Notes

 Biosorption of toxic heavy metals on sawdust

Citation:
V. Mishra, S. Tadepalli. CLEAN – Soil, Air, Water, 43(3), 360–367, 2015
Cited by: 24
Summary:
This study explores the efficiency of sawdust as a low-cost biosorbent for the removal of heavy metals like lead and cadmium from contaminated water. The adsorption mechanisms, equilibrium models, and reusability aspects were evaluated to determine its suitability in industrial wastewater treatment.

Synthesis and suitability characterization of microcrystalline cellulose from Citrus x sinensis sweet orange peel fruit waste-based biomass for polymer composite applications

Citation:
M. Palaniappan, S. Palanisamy, R. Khan, N. H. Alrasheedi, S. Tadepalli, et al. Journal of Polymer Research, 31(4), 105, 2024
Cited by: 18
Summary:
This research highlights the extraction of microcrystalline cellulose (MCC) from sweet orange peel waste. The resulting MCC was characterized and tested for compatibility in polymer composite applications, offering a sustainable path for waste valorization and advanced material design.

Novel Ficus retusa L. aerial root fiber: a sustainable alternative for synthetic fibres in polymer composites reinforcement

Citation:
M. Palaniappan, S. Palanisamy, T.M. Murugesan, N.H. Alrasheedi, S. Ataya, S. Tadepalli, et al. Biomass Conversion and Biorefinery, 15(5), 7585–7601, 2025
Cited by: 16
Summary:
The study introduces aerial root fiber from Ficus retusa as a green reinforcement material in polymer composites. Mechanical, thermal, and morphological analyses confirmed its potential as an eco-friendly alternative to synthetic fibers.

 Potential for hydrothermally separated groundnut shell fibers for removal of methylene blue dye

Citation:
D. Sachdev, H. Shrivastava, S. Sharma, S. Srivastava, S. Tadepalli, et al. Materials Today: Proceedings, 48, 1559–1568, 2022
Cited by: 15
Summary:
This paper evaluates the adsorption capacity of groundnut shell fibers, treated hydrothermally, for removing methylene blue dye. It investigates isotherms and kinetics to demonstrate the fiber’s potential in textile effluent remediation.

Removal of Cu(II) and Fe(II) from industrial wastewater using orange peel as adsorbent in batch mode operation

Citation:
S. Tadepalli, K.S.R. Murthy, N.N. Rakesh. International Journal of ChemTech Research, 9(5), 290–299, 2016
Cited by: 12
Summary:
This work examines the batch adsorption of copper and iron ions from wastewater using orange peel. The findings support its cost-effectiveness, with modeling of adsorption behavior using Freundlich and Langmuir isotherms.

🏅 Conclusion

Dr. Srinivas Tadepalli’s distinguished career reflects a steadfast commitment to academic excellence, impactful research, and sustainable innovation in chemical and environmental engineering. His work on low-cost adsorption technologies, wastewater treatment, and environmental remediation has contributed significantly to solving pressing industrial challenges. With a strong foundation in teaching, mentoring, and interdisciplinary collaboration, he continues to bridge the gap between science and society. Looking ahead, Dr. Tadepalli remains devoted to advancing green technologies, guiding future engineers, and fostering global research partnerships that promote cleaner, safer, and more sustainable solutions for the world.

Kai Zhang | Mechanical Engineering | Best Researcher Award

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Assoc. Prof. Dr. Kai Zhang | Mechanical Engineering | Best Researcher Award

Associate Professor, Shenyang University of Chemical Technology, China

ZHANG Kai is an accomplished Associate Professor at Shenyang University of Chemical Technology, specializing in artificial intelligence algorithms, robotics, and mechanical system optimization. With a doctoral degree in mechanical engineering, he has made significant contributions to intelligent fault diagnosis, machine vision, and the reliability of rotating machinery. Over the past five years, he has authored more than 30 academic papers, including 9 SCI-indexed and 11 EI-indexed articles, with 7 appearing in top-tier JCR Q1 journals. Dr. Zhang has led a sub-project under China’s National Key R&D Program and participated in several National Natural Science Foundation initiatives. His innovative research in adaptive optimization algorithms has also resulted in four patents. Committed to academic excellence and engineering innovation, Dr. Zhang continues to mentor students and lead pioneering research that bridges AI and mechanical design. His work enhances predictive maintenance, system reliability, and intelligent manufacturing technologies.

Profile

Scopus

Education 

ZHANG Kai earned his Doctorate in Mechanical Engineering, focusing on intelligent systems and optimization algorithms. His academic foundation is grounded in multidisciplinary studies that bridge traditional mechanical principles with cutting-edge computer science, especially in artificial intelligence and robotics. During his postgraduate years, he explored complex optimization problems, laying the groundwork for future research in algorithm development and machine learning applications in mechanical systems. His doctoral thesis was recognized for its innovation in adaptive optimization strategies for mechanism design. Dr. Zhang’s education equipped him with both theoretical acumen and practical engineering problem-solving skills, which he has since applied across a range of high-impact projects in academia and applied research. His passion for teaching and mentoring has also led to the development of curricula that integrate AI tools into traditional mechanical engineering coursework.

Experience 

Currently serving as Associate Professor at the Shenyang University of Chemical Technology, ZHANG Kai has over a decade of experience in academia and research. He has led and participated in multiple national-level projects, including a key sub-project under the National Key Research and Development Program. Over the past five years, he has published more than 30 peer-reviewed papers, many of which have been recognized in prestigious SCI and EI journals. He specializes in intelligent fault diagnosis for rotating machinery, differential evolution algorithms, and machine vision systems. His engineering expertise extends to vibration analysis and online health monitoring technologies. Dr. Zhang is also a key contributor to various academic initiatives aimed at improving the integration of AI within traditional mechanical systems. He is deeply involved in supervising graduate students and promoting interdisciplinary research within his department.

Research Focus

ZHANG Kai’s research lies at the intersection of mechanical engineering and artificial intelligence. His primary interests include the development of adaptive evolutionary algorithms, fault diagnosis techniques for rotating machinery, and intelligent machine vision systems. He applies AI-based solutions such as particle swarm optimization and differential evolution to solve multi-constraint mechanical design problems. His studies have enhanced the accuracy and efficiency of vibration monitoring, online health diagnostics, and fault tolerance systems in industrial equipment. With a growing emphasis on smart manufacturing, Dr. Zhang aims to bridge theoretical algorithm development with real-world mechanical applications. His research has far-reaching implications in industrial automation, robotics, and mechanical system reliability. He also works on improving the robustness and flexibility of mechanical optimization through novel algorithmic approaches. As industries increasingly seek to implement predictive maintenance and automation, his research offers critical tools and strategies for system sustainability and innovation.

Publication Top Notes

  1. Zhang K, Yang M, Zhang Y, et al.
    Title: Error feedback method (EFM) based dimension synthesis optimisation for four-bar linkage mechanism
    Journal: Applied Soft Computing, 2023: 110424
    Summary: Introduced an innovative error feedback method to enhance dimension synthesis in mechanical linkages, improving mechanical efficiency through intelligent correction algorithms.

  2. Kai Zhang, Eryu Zhu, et al.
    Title: A multi-fault diagnosis method for rolling bearings
    Journal: Signal, Image and Video Processing, 2024, 18: 8413-8426
    Summary: Developed a multi-fault detection model using signal processing and AI classification to improve maintenance systems in rotating equipment.

  3. Kai Zhang, Jiahao Zhu, Yimin Zhang, Qiujun Huang
    Title: Optimization method for linear constraint problems
    Journal: Journal of Computational Science, 2021, 51: 101315
    Summary: Proposed a new optimization framework for solving mechanical design issues with linear constraints using a hybrid computational approach.

Conclusion:

Associate Professor ZHANG Kai’s academic output, innovative methodologies, and active leadership in key research initiatives position him as a highly deserving candidate for the Best Researcher Award. His contributions significantly advance knowledge in AI-based mechanical systems and engineering reliability. Recognizing his work through this award would not only honor his individual achievements but also encourage further interdisciplinary research within his field.

Gokhan Basar | Mechanical Engineering | Best Researcher Award

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Dr. Gokhan Basar | Mechanical Engineering | Best Researcher Award

Research Assistant at Industrial Engineering, Turkey

Dr. Gokhan Basar is a dedicated researcher and assistant professor in the Department of Industrial Engineering at Osmaniye Korkut Ata University, Turkey. Born on January 1, 1989, in Tarsus, Turkey, he has developed a strong academic and professional foundation in mechanical engineering. Dr. Basar holds a PhD in Mechanical Engineering, specializing in the production of reinforced aluminum matrix composites. He has contributed significantly to the field through his research on friction stir welding and optimization techniques, establishing himself as an expert in machinability and mechanical properties of materials. His commitment to advancing engineering knowledge is evident in his numerous publications and active participation in national and international conferences.

Profile:

Google Scholar

Strengths for the Award:

  1. Diverse Research Areas: Dr. Basar has an extensive range of research interests including Friction Stir Welding, machinability of materials, and optimization techniques. This diversity reflects a strong capability to contribute to various fields within engineering.
  2. Academic Qualifications: With a PhD in Mechanical Engineering and multiple relevant master’s and bachelor’s degrees, Dr. Basar possesses a solid educational foundation that underpins his research.
  3. Significant Contributions: His published works, including book chapters and numerous journal articles, indicate active engagement in research. The citation metrics (42 citations and an H-index of 4) highlight that his work is recognized and valued by the academic community.
  4. Research Methodology Expertise: Dr. Basar’s proficiency in experimental design and optimization methods, particularly the Taguchi Method and Grey Relational Analysis, showcases his ability to apply advanced statistical techniques to real-world engineering problems.
  5. Active Conference Participation: Regular attendance at national and international conferences demonstrates a commitment to staying updated with the latest developments in his field and sharing his findings with the broader scientific community.
  6. Journal Refereeing: Serving as a referee for multiple reputable journals illustrates his involvement in the academic process and recognition by peers.

Areas for Improvement:

  1. Increased Collaboration: While Dr. Basar has a solid publication record, collaboration with researchers from diverse fields could enhance the breadth and impact of his research.
  2. Enhancing Citation Impact: Although his citation metrics are commendable, focusing on publishing in high-impact journals could further increase his visibility and citation rate.
  3. Broader Public Engagement: Engaging with industry stakeholders and public forums could help translate his research findings into practical applications, increasing societal impact.
  4. Exploration of Emerging Technologies: Staying abreast of emerging technologies in materials science and mechanical engineering could provide new avenues for research and innovation.

Education:

Dr. Gokhan Basar’s educational journey began with a Bachelor’s degree in Mechanical Engineering, which laid the groundwork for his advanced studies. He earned his MSc in Mechanical Engineering from Iskenderun Technical University (2013-2016), where he focused on optimizing welding parameters in friction stir welding. His research culminated in a thesis that highlighted his proficiency in practical applications of engineering principles. Dr. Basar continued his academic pursuit at Osmaniye Korkut Ata University, where he completed his PhD in Mechanical Engineering (2017-2023). His doctoral research investigated the production of SiC and B4C particle-reinforced aluminum matrix composites through powder metallurgy, further showcasing his ability to innovate in materials engineering. Throughout his academic career, Dr. Basar has demonstrated a strong commitment to educational excellence and research development.

Experience:

Dr. Gokhan Basar has amassed extensive experience in academia, starting his career as a Research Assistant in the Department of Mechanical Engineering at Iskenderun Technical University from 2013 to 2016. His responsibilities included conducting research, assisting in teaching, and engaging in various engineering projects. In 2016, he transitioned to Osmaniye Korkut Ata University, where he currently serves as a Research Assistant in the Department of Industrial Engineering. In this role, Dr. Basar has focused on advancing knowledge in the fields of friction stir welding, materials machinability, and optimization methods. He has participated in numerous conferences, enhancing his professional network and contributing to the scientific community. His dedication to research and education has positioned him as a prominent figure in mechanical engineering, with a strong emphasis on innovative practices and experimental design.

Research Focus:

Dr. Gokhan Basar’s research focuses primarily on advanced welding techniques, particularly Friction Stir Welding (FSW), and the machinability and mechanical properties of materials. His expertise extends to optimization methods, including the Taguchi Method, Response Surface Methodology, and Grey Relational Analysis, enabling him to develop effective strategies for improving material performance and process efficiency. He is particularly interested in the production of composite materials, investigating the use of SiC and B4C particles in aluminum matrices to enhance their mechanical properties. His research also includes the design of experiments and multi-response optimization, providing insights into surface quality and operational parameters in various manufacturing processes. Dr. Basar’s commitment to innovation in mechanical engineering drives his work to address contemporary challenges and contribute to the evolution of engineering practices.

Publications Top Notes:

  1. Optimization of machining parameters in face milling using multi-objective Taguchi technique 📄
  2. Modeling and optimization of face milling process parameters for AISI 4140 steel 📄
  3. Determination of the optimum welding parameters for ultimate tensile strength and hardness in friction stir welding of Cu/Al plates using Taguchi method 📄
  4. Optimization of cutting parameters in hole machining process by using multi-objective Taguchi approach 📄
  5. Modeling and optimization for fly ash reinforced bronze-based composite materials using multi-objective Taguchi technique and regression analysis 📄
  6. Multi-response optimization in drilling of MWCNTs reinforced GFRP using grey relational analysis 📄
  7. Delik İşleme Prosesinde Kesme Parametrelerin Taguchi Metodu ve Regresyon Analiz Kullanılarak Modellenmesi ve Optimizasyonu 📄
  8. Kolemanit ve Boraks Takviyeli Fren Balatalarının Sürtünme Performansı 📄
  9. Sıcak presleme yöntemi ile üretilmiş uçucu kül takviyeli bronz matrisli fren balata malzemelerinin sürtünme-aşınma özellikleri üzerine kolemanit miktarının etkisi 📄
  10. Mathematical Modeling and Optimization of Milling Parameters in AA 5083 Aluminum Alloy 📄
  11. 316L Paslanmaz Çeliklerin Frezeleme işlemindeki Yüzey Pürüzlülüğün ANFIS ile Modellenmesi 📄
  12. Bronz Esaslı Kompozit Sürtünme Malzemelerin Üç Nokta Eğme Mukavemetinin Taguchi Metodu ile Optimizasyonu 📄
  13. Statistical Investigation of the Effect of CO2 Laser Cutting Parameters on Kerf Width and Heat Affected Zone in Thermoplastic Materials 📄
  14. A new hybrid meta-heuristic optimization method for predicting UTS for FSW of Al/Cu dissimilar materials 📄
  15. Prediction of surface hardness in a burnishing process using Taguchi method, fuzzy logic model and regression analysis 📄
  16. Multi-objective optimization of cutting parameters for polyethylene thermoplastic material by integrating data envelopment analysis and SWARA-based CoCoSo approach 📄
  17. Kompozit Malzemelerin Delme İşleminde İtme Kuvvetinin Taguchi Metodu ile Optimizasyonu ve Regresyon Analizi ile Tahmini 📄
  18. Tepki yüzeyi metodolojisi kullanılarak nanokompozitin delinmesinde oluşan itme kuvvetinin modellenmesi ve analizi 📄
  19. Analysis and Optimization of Ball Burnishing Process Parameters of AA 7075 Aluminium Alloy with Taguchi Method 📄
  20. The Effect of Colemanite and Borax Reinforced to the Friction Performance of Automotive Brake Linings 📄

Conclusion:

Dr. Gokhan Basar exemplifies the qualities of a strong candidate for the Research for Best Researcher Award. His extensive research experience, educational background, and contributions to the field of engineering position him as a noteworthy researcher. By focusing on collaboration, increasing his publication impact, and engaging with the broader community, he could further enhance his profile as a leading researcher. His commitment to advancing knowledge in his areas of expertise makes him a deserving candidate for this prestigious award.

Sanyogita Manu | Engineering and Technology | Best Researcher Award

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Ms. Sanyogita Manu | Engineering and Technology | Best Researcher Award

PhD Candidate, The University of British Columbia, Canada

Publication Profile

Google scholar

Strengths for the Award

  1. Innovative Research Focus: Sanyogita’s work addresses a significant issue—indoor environmental quality during a time when many transitioned to remote work due to the pandemic. Her systematic study has the potential to inform guidelines and policies related to home office setups, highlighting its relevance in current public health discussions.
  2. Methodological Rigor: The research employs a robust methodology, utilizing continuous monitoring of various IEQ parameters alongside subjective assessments from participants. This comprehensive approach enhances the reliability of her findings.
  3. Professional Affiliations and Contributions: Sanyogita is actively engaged in professional organizations related to her field, serving on committees and reviewing journals. Her involvement in international conferences signifies her commitment to advancing research in IEQ and energy-efficient design.
  4. Publication Record: With multiple peer-reviewed publications and conference proceedings, Sanyogita demonstrates a solid track record in disseminating her research findings, contributing to the academic community’s understanding of indoor environments.
  5. Awards and Recognition: Her prior achievements and recognitions, including scholarships and awards, underscore her dedication and excellence in research.

Areas for Improvement

  1. Broader Impact Assessment: While her research is focused on WFH settings, there may be an opportunity to expand her study to include diverse populations and different geographical locations to enhance the generalizability of her findings.
  2. Interdisciplinary Collaboration: Collaborating with professionals from related fields such as psychology, sociology, or occupational health could enrich her research and offer a more holistic understanding of the WFH experience.
  3. Public Engagement: Engaging in public outreach or workshops to share her findings with broader audiences, including policymakers and the general public, could enhance the impact of her work and foster practical applications of her research.

Education

Sanyogita holds a Master’s degree in Interior Architecture and Design, specializing in Energy and Sustainability from CEPT University, India, where her dissertation focused on optimizing window performance in commercial buildings. She also earned her Bachelor’s degree in Interior Design from the same institution, with a dissertation exploring the thermal effects of furniture in interior environments. 🎓

Experience

With extensive experience in academia and research, Sanyogita has contributed to various projects assessing indoor environmental conditions and energy efficiency in buildings. She has served on several scientific committees and has been actively involved in peer review for reputable journals, reflecting her expertise in the field. 🏢

Research Focus

Her research primarily focuses on indoor environmental quality (IEQ) and its impact on occupant well-being and productivity, particularly in work-from-home settings. Sanyogita employs a systematic approach to evaluate both perceived and observed IEQ, utilizing a variety of environmental monitoring tools. 🔍

Awards and Honours

Sanyogita is a member of multiple prestigious organizations, including the International Society of Indoor Air Quality and Climate (ISIAQ) and the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE). She has been recognized for her contributions to building performance simulation and energy conservation, reflecting her commitment to sustainable practices. 🏆

Publication Top Notes

Manu, S., & Rysanek, A. (under review). A novel dataset of indoor environmental conditions in work-from-home settings. Building and Environment.

Manu, S., & Rysanek, A. (2024). A Co-Location Study of 87 Low-Cost Environmental Monitors: Assessing Outliers, Variability, and Uncertainty. Buildings, 14(9), Article 9. Link

Manu, S., et al. (2024). A state-of-the-art, systematic review of indoor environmental quality studies in work-from-home settings. Building and Environment, 111652. Link

Doctor-Pingel, M., et al. (2019). A study of indoor thermal parameters for naturally ventilated occupied buildings in the warm-humid climate of southern India. Building and Environment, 151, 1-14. Link

Manu, S., et al. (2019). Performance evaluation of climate responsive buildings in India – Case studies from cooling dominated climate zones. Building and Environment, 148, 136-156. Link

Gupta, R., et al. (2019). Customized performance evaluation approach for Indian green buildings. Building Research & Information, 47(1), 56–74. Link

Conclusion

Sanyogita Manu’s research on indoor environmental quality in work-from-home settings is both timely and significant. Her methodological rigor, publication record, and active participation in professional communities demonstrate her dedication to advancing knowledge in her field. While there are areas for improvement, her strengths strongly position her as a worthy candidate for the Best Researcher Award. Her work has the potential to influence policy and improve well-being in residential work environments, making her contributions invaluable in today’s context.

Qi Liang | Pattern Recognition | Excellence in Research

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Mr Qi Liang | Pattern Recognition | Excellence in Research

Master in Tongji University at China

Qi Liang is a dedicated researcher and master’s student at Tongji University, PR China, specializing in mechanical engineering. With a strong foundation in industrial engineering from Jiangsu University of Science and Technology, Qi has a keen interest in advancing technology through innovative research. Recognized for introducing self-supervised learning methods in semiconductor applications, Qi’s work aims to solve complex challenges in pattern recognition. Their publication in Engineering Applications of Artificial Intelligence reflects a commitment to high-impact research. With multiple ongoing projects and a focus on practical applications, Qi is paving the way for efficient solutions in the semiconductor industry.

Profile

Google Scholar

Strengths for the Award

  1. Innovative Research: Qi Liang has introduced a self-supervised learning method for few-shot learning in semiconductor applications, demonstrating originality and a significant contribution to the field.
  2. Publication Record: The recent publication in Engineering Applications of Artificial Intelligence showcases a commitment to high-quality research, adding to the credibility of the work.
  3. Diverse Research Interests: With a focus on computer vision, multi-modal learning, and fault diagnosis, Qi’s work spans multiple cutting-edge areas, which increases the potential impact of the research.
  4. Practical Applications: The research addresses real-world challenges in the semiconductor industry, offering low-cost, efficient methods that have immediate applicability.
  5. Academic Engagement: Qi’s active involvement in ongoing projects and industry collaborations indicates a robust engagement with both academic and practical aspects of research.

Areas for Improvement

  1. Broader Collaboration: Expanding collaborations with international researchers could enhance the research’s visibility and applicability on a global scale.
  2. Increased Publication Volume: While the current publication is commendable, a more extensive publication record could further establish Qi’s expertise and leadership in the field.
  3. Outreach and Communication: Engaging in more outreach activities, such as conferences and seminars, could help disseminate findings and foster connections within the research community.

Education 

Qi Liang graduated with a Bachelor’s degree in Industrial Engineering from Jiangsu University of Science and Technology, where foundational principles of engineering and technology were mastered. Currently, Qi is pursuing a Master’s degree in Mechanical Engineering at Tongji University, one of China’s prestigious institutions, now in their third year of the program. This advanced education has allowed Qi to engage deeply with cutting-edge topics, particularly in computer vision and machine learning. Through rigorous coursework and research, Qi has developed expertise in areas such as pattern recognition, self-supervised learning, and fault diagnosis, equipping them with the skills necessary to tackle complex engineering problems and contribute significantly to both academic and industrial advancements.

Experience

Qi Liang has gained substantial experience through multiple research projects, totaling five completed or ongoing initiatives that emphasize practical applications of machine learning in semiconductor manufacturing. In addition to academic research, Qi has participated in three consultancy and industry-sponsored projects, bridging the gap between theoretical knowledge and real-world applications. Their collaborative efforts in research have led to valuable partnerships and a broader understanding of the industry’s challenges and needs. As the first to implement self-supervised learning techniques in few-shot learning tasks related to wafer map pattern recognition, Qi has showcased exceptional innovation. This unique approach has opened new avenues for cost-effective and efficient solutions within the semiconductor sector, positioning Qi as an emerging leader in their field.

Research Focus 

Qi Liang’s research focuses on the intersection of computer vision and machine learning, with a strong emphasis on pattern recognition, keypoint detection, and image retrieval. Specializing in self-supervised and multi-modal learning, Qi aims to develop innovative methodologies that minimize the reliance on labeled data while maximizing efficiency and applicability in industrial contexts. Current research projects explore dynamic adaptation mechanisms for few-shot learning, specifically tailored for wafer map pattern recognition in the semiconductor industry. Qi is also interested in signal processing and fault diagnosis, seeking to improve reliability and performance in manufacturing processes. This research direction not only contributes to the academic community but also addresses pressing industry challenges, promoting advancements in automation and smart manufacturing.

Publication Top Notes

  • Masked Autoencoder with Dynamic Multi-Loss Adaptation Mechanism for Few Shot Wafer Map Pattern Recognition 📄

Conclusion

Qi Liang’s innovative contributions to the field of mechanical engineering and computer vision make a strong case for the Excellence in Research award. The unique approach to self-supervised learning in few-shot learning for wafer map pattern recognition signifies both a breakthrough in methodology and practical application in the semiconductor industry. With a few strategic improvements, Qi has the potential to further amplify the impact of their research and cement their status as a leading researcher in their field.

Dalia El- Gazzar | Vibration and Dynamics | Best Researcher Award

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Dr Dalia El- Gazzar | Vibration and Dynamics | Best Researcher Award

Dr Dalia El- Gazzar, National water research center, Egypt

Dr. Dalia Mohamed Sadek El-Gazzar is an accomplished expert in mechanical and electrical engineering with over 24 years of experience at the Mechanical & Electrical Research Institute (MERI). Specializing in optimizing hydro-electro-mechanical systems, her work has significantly advanced predictive maintenance and dynamic analysis of pumping stations. She holds a Ph.D. in Mechanical Engineering from Menoufia University and has contributed extensively to technical research and education, including teaching advanced courses on vibration analysis and predictive maintenance. Her dedication to improving the performance and reliability of drainage and irrigation systems underscores her commitment to engineering excellence.

Publication Profile

Scopus

Strengths for the Award

  1. Extensive Experience: Dalia Mohamed Sadek El-Gazzar has over 24 years of experience at the Mechanical & Electrical Research Institute (MERI), focusing on optimizing the operation and performance of hydro-electro-mechanical components in drainage and irrigation systems. This long-standing experience is a strong point for the award.
  2. Leadership Roles: She has held significant leadership roles, such as Director Deputy and Head of the Mechanical Department at MERI. Additionally, she has led multiple research projects related to dynamic analysis and quality control in irrigation and drainage systems.
  3. Research Contributions: Dalia has published numerous papers in reputable journals, highlighting her contributions to improving the dynamic performance and reliability of pumping systems. Her work in vibration analysis and preventive maintenance is particularly noteworthy.
  4. Educational Background: With a Ph.D. in Mechanical Engineering focused on vibration analysis of pumping systems, coupled with an M.Sc. and B.Sc. in related fields, her strong academic background supports her candidacy.
  5. Technical Expertise: Dalia has technical expertise in areas such as structural and mechanical vibration, fault detection, dynamic and hydraulic assessment, and preventive maintenance of rotating machinery.
  6. Conferences and Workshops: Her participation in a wide range of international conferences and workshops demonstrates her active involvement in the research community and her commitment to continuous learning and dissemination of knowledge.

Areas for Improvement

  1. Broader Impact: While her work is highly specialized in the field of mechanical and electrical systems for water resources, expanding her research to broader applications or interdisciplinary studies might enhance her impact and visibility within the research community.
  2. International Collaboration: Although she has participated in international conferences, increasing collaboration with international researchers or institutions could strengthen her research portfolio and provide diverse perspectives.
  3. Innovation and Patents: Emphasizing innovation through the development of new technologies or securing patents could further distinguish her work and contribute to practical advancements in her field.

Education

Dr. Dalia Mohamed Sadek El-Gazzar earned her Ph.D. in Mechanical Engineering from Menoufia University in February 2012, with a focus on vibration analysis of pumping systems with variable speed drives. She completed her M.Sc. in April 2004, studying the impact of bearing faults on dynamic behavior and power consumption in water pumps. Her B.Sc., obtained in May 1999, was in Production Engineering and Mechanical Design from the same institution. Her academic background has laid a strong foundation for her expertise in vibration analysis and predictive maintenance.

Experience

Dr. El-Gazzar’s professional journey spans over two decades, with roles including Director Deputy and Head of the Mechanical Department at MERI. She has led critical research projects on dynamic analysis and quality control in irrigation and drainage systems. Her experience includes hands-on inspection, calibration, and dynamic assessment of pumping stations. She has also contributed to numerous technical investigations and reports, enhancing system performance and reliability. Her role as an educator has involved teaching advanced engineering courses and training international engineers.

Research Focus

Dr. El-Gazzar’s research focuses on the dynamic performance and reliability of hydro-electro-mechanical systems in irrigation and drainage. Her work extensively covers vibration analysis, predictive maintenance, and fault diagnosis of pumping stations. She has explored the effects of variable speed drives, bearing faults, and structural vibrations on system efficiency. Her studies aim to optimize system performance, enhance reliability, and contribute to sustainable water resource management. Her research has significantly advanced the understanding and application of dynamic analysis in improving engineering practices.

Publication Top Notes

“Enhancing Efficiency and Dynamic Performance of Bearings in Pumping Stations” 📈

“Dynamic Performance Application of A Variable Speed Centrifugal Pump” 🚀

“Effect of Critical Speed on the Dynamic and Hydraulic Performance of a Variable Speed Pump” 🔧

“Vibration Analysis of Centrifugal Pump with Variable Speed Drives” ⚙️

“Evaluating Efficiency and Safety of Aerators in a Sanitary Drainage Station Using Vibration Analysis” 🔍

“Investigate the Effect of Fan Configuration on the Performance of Aeration Units for Waste Water Treatment” 💧

“Effect of Motor Vibration Problem on the Power Quality of Water Pumping Stations” ⚡

Conclusion

Dalia Mohamed Sadek El-Gazzar is a highly qualified candidate for the Best Researcher Award, given her extensive experience, leadership roles, and significant contributions to research in the field of mechanical and electrical systems for water resources. Her work has made valuable improvements in the performance and reliability of irrigation and drainage systems. While there is room for expanding her research’s impact and international collaboration, her current achievements make her a strong contender for the award.