Dr. Umadevi Kandalam | Biotechnology | Best Researcher Award

Published on by Computer Scientists Awards

Umadevi Kandalam | Biotechnology | Best Researcher Award

Associate Professor, Texas Tech University Health Science Center El Paso, United States

Dr. Umadevi Kandalam, Ph.D., is an accomplished academic and researcher currently serving as an Associate Professor of Physiology at the Woody L. Hunt School of Dental Medicine, Texas Tech University Health Sciences Center, El Paso, where she also holds a faculty role with the L. Frederick Francis Graduate School of Biomedical Sciences. With a strong foundation in zoology, endocrinology, and parasitology from Andhra and Annamalai Universities, complemented by advanced training in computer applications and environmental management, she brings interdisciplinary expertise to biomedical and craniofacial research. Her career spans significant roles at Nova Southeastern University, where she was Associate Professor and Director of the Craniofacial Research Fellowship, and at institutions in India, including Andhra University, where she began as a Young Scientist. Dr. Kandalam has actively engaged in faculty development, completing programs at Texas Tech and Cornell University, while also contributing to professional bodies such as AADOCR through session chairing and mentorship. Recognized with prestigious awards like the Faculty Scientific Research Award by the American Association of Oral and Maxillofacial Surgeons and Osteoscience Foundation, as well as multiple External Funding Recognition Awards at Nova Southeastern, she has established a strong research profile in craniofacial biology and biomaterials. Her scholarly impact is reflected in 25 research documents, a citation count of 1,283 by 1,149 documents, and an h-index of 13, underscoring her international recognition and influence. Through her commitment to teaching, research, and leadership, Dr. Kandalam continues to shape dental education and biomedical sciences with innovation and dedication.

Profile : Scopus

Featured Publications

  • Ishii, T., Ruiz-Torruella, M., Yamamoto, K., Yamaguchi, T., Heidari, A., Pierrelus, R., Leon, E., Shindo, S., Rawas-Qalaji, M., Pastore, M.R., Ikeda, A., Nakamura, S., Mawardi, H., Kandalam, U., Hardigan, P., Witek, L., Coelho, P.G., & Kawai, T. Locally Secreted Semaphorin 4D Is Engaged in Both Pathogenic Bone Resorption and Retarded Bone Regeneration in a Ligature-Induced Mouse Model of Periodontitis. International Journal of Molecular Sciences, 23(10), 5630 (2022).

  • Babanejad, N., Kandalam, U., & Omidian, H. Functional properties of thermally tampered poly (ethylene oxide). Bioimplants, 12(5), 471-476 (2022).

  • Shindo, S., Savitri, I.J., Ishii, T., Ikeda, A., Pierrelus, R., Heidari, A., Okubo, K., Nakamura, S., Kandalam, U., Kawai, T., et al. Dual-Function Semaphorin 4D Released by Platelets: Promotion of Suppression of Osteoblastogenesis and Osteoclastogenesis. International Journal of Molecular Sciences, 23(6), 2938 (2022).

  • Babanejada, N., Kandalam, U., Ahmad, R., Omidian, Y., & Omidian, H. Abuse-deterrent properties and cytotoxicity of poly (ethylene oxide) after thermal tampering. International Journal of Pharmaceutics, 600(1), 120481 (2021).

  • Kandalam, U., Kawai, T., Ravindran, G., Brockman, R., Romero, J., Munro, M., Ortiz, J., Heidari, A., Thomas, R., Kuriakose, S., Naglieri, C., Ejtemai, S., & Kaltman, S.I. Pre-differentiated Gingival Stem Cells Induced Bone Regeneration in Rat Alveolar Bone Defect Model. Tissue Engineering Part A, 5-6, 427-436 (2021).

 

Assoc. Prof. Dr. Fatih Ünal | Energy Simulation | Best Researcher Award

Published on by Computer Scientists Awards

Fatih Ünal | Energy Simulation | Best Researcher Award

Mechanical Engineering, Mersin University, Turkey

Fatih Ünal is an Associate Professor in the Department of Mechanical Engineering at Mersin University, specializing in energy systems, renewable energy applications, and thermal sciences. He earned his Bachelor’s degree in Mechanical Engineering from Dumlupinar University, followed by a Master’s degree in Heat and Process Engineering at Yildiz Technical University, where he conducted a thesis on the exergy analysis of thermal power plants. He later completed his Ph.D. in the same field at Yildiz Technical University, focusing on the applicability of solar-assisted vertical ground source heat pumps in Mardin. His academic career began at Mardin Artuklu University, where he served as Lecturer, Assistant Professor, and Head of Department, as well as Director of the Distance Teaching Application and Research Center. He later joined Mersin University, advancing to the rank of Associate Professor. His research contributions span photovoltaic performance analysis, solar-assisted Rankine cycles, hybrid energy systems, and geothermal heating applications, with numerous publications in international refereed journals. To date, he has authored 12 scientific documents that have been cited 86 times by 80 different sources, reflecting an h-index of 5, which highlights the growing recognition of his work. His academic journey reflects dedication to advancing renewable energy and sustainable engineering solutions.

Profile: Scopus | ORCID | Google Scholar

Featured Publications

Ünal, F., Şentürk Acar, M., & Demir, B. (2024). Evaluating photovoltaic panel efficiency during the cooling season in Mersin: Insights from alternative performance models. International Journal of Advanced Natural Sciences and Engineering Researches, 8(11), 636–640.

Ünal, F., Şentürk Acar, M., & Demir, B. (2024). Assessment of photovoltaic panel efficiency at various tilt angles in Mersin Province during the cooling season. International Journal of Advanced Natural Sciences and Engineering Researches, 8(11), 641–646.

Ünal, F., & Şentürk Acar, M. (2024). Exergoeconomic analysis of a solar assisted organic Rankine cycle: Case study of Mardin, Turkey. Thermal Science.

Boz, İ., Ayanoğlu, A., Ayas, G., & Ünal, F. (2022). Investigation of temperature effect on electrical efficiency for a photovoltaic–thermal hybrid system. International Journal of Science and Research, 11(8), 1158–1163.

Ünal, F., Akan, A. E., Demir, B., & Yaman, K. (2022). 4E analysis of an underfloor heating system integrated to the geothermal heat pump for greenhouse heating. Turkish Journal of Agriculture and Forestry, 46(5), 762–780.

Prof. Chun-pin Tseng | Catastrophe | Best Researcher Award

Published on by Computer Scientists Awards

Chun-pin Tseng | Catastrophe | Best Researcher Award

Associate Professor, Qilu Institute of Technology, China

Prof. Chun-pin Tseng is an accomplished scholar and professional in civil engineering, risk management, and disaster mitigation, currently serving as an Associate Professor at Qilu Institute of Technology in Shandong, China, while also leading Jenn-Don Engineering Consultants Inc. as CEO. He earned his Ph.D. in Civil Engineering and Risk Management from National Central University, where his dissertation focused on designing strategies for insurance and risk control that balanced economic effects with disaster mitigation. His academic journey also includes an MEng in Space and Remote Sensing, where his thesis on natural detection via GPS was recognized as excellent, and a BA in Civil Engineering. Throughout his career, he has held significant roles, including Duty Director at the National Chung-Shan Institute of Science and Technology, Senior Engineer at the Industrial Technology Research Institute, visiting scholar at Stanford University’s John A. Blume Earthquake Engineering Center, and consultant for STI Colleges and Education Centers. He has also co-founded Taiwan Risk Management Co., Inc., pioneering natural disaster risk analysis in Taiwan. His research contributions span earthquake insurance systems, natural disaster loss assessment, and dynamic financial analysis. With 24 published documents, 679 citations, and an h-index of 15, Prof. Tseng continues to advance scholarship in engineering and disaster risk management.

Profile: Scopus | ORCID

Featured Publications

Zhang, H. (2025). A closed-loop optimization system for evaluating the development effect and potential of producers with water alternating gas flooding. Processes.

Zhang, H. (2025). A dynamic characterization method for horizontal wells based on the gated recurrent unit: A case study of a carbonate reservoir in the Middle East. In Springer Series in Geomechanics and Geoengineering (Book chapter).

Tseng, C. (2025). GIS-based automated waterlogging depth calculation and building loss assessment in urban communities. Water.

Tseng, C. (2013). A new viewpoint of hazard assessment and management for Taiwan’s insurance issues. Natural Hazards.

Tseng, C. (2013). Application of GIS for the determination of hazard hotspots after direct transportation linkages between Taiwan and China. Natural Hazards.

Mr. Zhenduo Meng | Machine Learning | Best Researcher Award

Published on by Computer Scientists Awards

Zhenduo Meng | Machine Learning | Best Researcher Award

Inner Mongolia University, China

Zhenduo Meng is a graduate student pursuing his M.Sc. in Electronic Information Engineering at the School of Electronic Information Engineering, Inner Mongolia University, with a strong academic foundation built during his B.Eng. studies in Automation at Guangxi University. His research primarily focuses on multi-agent reinforcement learning (MARL), deep reinforcement learning, cooperative control of multi-agent systems, and the broader applications of artificial intelligence in intelligent decision-making. He has actively participated in several research projects, where he contributed to the development of algorithms integrating attention mechanisms and value decomposition methods to improve collaboration efficiency in MARL environments. Recently, his research work, “DDWCN: A Dual-Stream Dynamic Strategy Modeling Network for Multi-Agent Elastic Collaboration,” was accepted for publication in Applied Sciences (2025), highlighting his innovative contributions in the field. Despite being at the early stage of his academic journey, his scholarly output includes 2 documents, and his current citation count stands at zero, reflecting the fresh and emerging nature of his research profile. His h-index is also recorded as zero, consistent with his recent entry into the publication landscape. Proficient in Python, MATLAB, PyTorch, and TensorFlow, along with strong command of both Chinese and English, Meng demonstrates promising potential for impactful contributions in intelligent systems research.

Profile: Scopus

Featured Publications

Meng, Z., Na, X., Wang, T., Liu, J., & Wang, W. (2025). DDWCN: A dual-stream dynamic strategy modeling network for multi-agent elastic collaboration.

Wang, T., Na, X., Nie, Y., Liu, J., Wang, W., & Meng, Z. (2025). Parallel task offloading and trajectory optimization for UAV-assisted mobile edge computing via hierarchical reinforcement learning. Drones, 9(2),

Dr. Anbo Wang | Photonics | Best Researcher Award

Published on by Computer Scientists Awards

Anbo Wang | Photonics | Best Researcher Award

Chief Executive Officer, Sentek Instrument, United States

Dr. Anbo Wang is a highly accomplished scientist, entrepreneur, and academic leader with over three decades of expertise in optical fiber sensor technology. He is the founder of Sentek Instrument LLC (Sentek), where he has led the successful development and commercialization of advanced fiber optic sensing systems for applications in structural health monitoring, traffic management, and industrial process optimization. In academia, he is the founding director of the Virginia Tech Center for Photonics Technology and currently holds the prestigious Clayton Arye Professorship. With a prolific research career, Dr. Wang has authored more than 350 journal articles and conference papers, and his work has garnered over 8,835 citations across 6,000 documents, reflecting his significant influence in the field. He maintains an impressive h-index of 51, showcasing both the depth and impact of his research contributions. Beyond his publications, Dr. Wang has mentored more than 100 graduate students and postdoctoral researchers, shaping the next generation of scientists and engineers. He has also played a leading role in the scientific community by chairing or co-chairing numerous international conferences and symposia on fiber optics and sensors. Recognized globally, he is a Fellow of the International Society for Optics and Photonics (SPIE).

Profile: Scopus | Google Scholar

Featured Publications

Dejneka, Z., Homa, D., Theis, L., Wang, A., & Pickrell, G. (2025). Acoustic sensing fiber coupled with highly magnetostrictive ribbon for small-scale magnetic-field detection. Sensors. MDPI.

Theis, L., Homa, D., Pickrell, G., & Wang, A. (2025). Acoustic frequency domain reflectometry in waveguides. IEEE Sensors Journal. IEEE.

Wang, R., Wang, R., Dou, C., Yang, S., Gnanasambandam, R., Wang, A., & Kong, Z. (2024). Sub-surface thermal measurement in additive manufacturing via machine learning-enabled high-resolution fiber optic sensing. Nature Communications.

Wang, R., Qiu, T., Zhang, Y., Rein, M., Stolyarov, A., Zhang, J., Seidel, G. D., Johnson, B. N., & Wang, A. (2024). Fiber-based miniature strain sensor with fast response and low hysteresis. Advanced Functional Materials. Wiley.

Dejneka, Z., Homa, D., Buontempo, J., Crawford, G., & Wang, A. (2024). Magnetic field sensing via acoustic sensing fibers with submicron magnetostrictive cladding inclusions. Optical Fiber Technology. Elsevier.

 

 

Mr. Chenxi Peng | Development of Chemometrics | Best Researcher Award

Published on by Computer Scientists Awards

Chenxi Peng | Development of Chemometrics | Best Researcher Award

University of Barcelona, Spain

Chenxi Peng is a dedicated researcher currently pursuing his doctoral studies in Analytical Chemistry and the Environment at the University of Barcelona, where his work focuses on advancing chemometric methodologies and their applications to spectroscopy and imaging. He holds a master’s degree in Resource and Environmental Science from Wenzhou University, where he developed a strong foundation in analytical techniques and environmental research. His research expertise covers a broad range of spectroscopic approaches, including Raman, near-infrared, mid-infrared, and hyperspectral methods, with an emphasis on experimental design, spectral data acquisition, and advanced preprocessing techniques to improve data quality. He applies multivariate analysis tools such as multivariate curve resolution (MCR), partial least squares (PLS) and its extensions, Least Trimmed Squares (LTS), MacroPCA, and outlier detection algorithms, enabling precise quantitative analysis, feature identification, and band interpretation. His studies connect spectral features to chemical bonds and functional groups, particularly in biomedical and environmental diagnostics. Despite being in the early stages of his research career, Chenxi has already demonstrated measurable academic contributions, with 3 citations across 2 documents and an h-index of 1, reflecting both the relevance and growing recognition of his work. His commitment lies in integrating data-driven approaches with analytical sciences to address pressing biomedical and environmental challenges.

Profile: Scopus | ORCID | Google Scholar

Featured Publications

Peng, C., Huang, G., Chen, X., Xie, Z., Ali, S., Chen, X., Nie, H., Yang, Z., Zhu, L., … (2024). Identification of near‐infrared characteristic bands of small bowel necrosis based on cellwise detection algorithm. Journal of Biophotonics, 17(6), e202300438.

Li, J., Peng, C., Hou, Y., Huang, G., Zhang, L., Chen, X., Xie, Z., Ali, S., Zhu, L., … (2025). Identification of near‐infrared characteristic bands of small intestine necrosis based on least trimmed squares with regularization. Journal of Biophotonics, e70023.

Peng, C., Chen, X., Zhu, L., de Juan, A., & Tauler, R. (2025). Analysis of ischemic intestinal tissue composition based on visible and near-infrared reflectance hyperspectral imaging and multivariate curve resolution. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 126841.

Dr. Han Zhang | Computer Science | Best Researcher Award

Published on by Computer Scientists Awards

Han Zhang | Computer Science | Best Researcher Award

Research Institute of Petroleum Exploration and Development, China

Dr. Han Zhang is a young and dedicated researcher at the China National Petroleum Corporation Research Institute of Petroleum Exploration and Production, where he focuses on advancing intelligent reservoir development and optimization for the future of the energy industry. With a strong educational foundation, he earned his bachelor’s degree in Marine Oil and Gas Engineering from a prestigious petroleum university in China, majoring in reservoir and oil production engineering, before continuing his master’s and doctoral studies in Oil and Gas Field Development Engineering at the same institute. His research centers on the development of advanced mathematical and numerical models that address key challenges in petroleum engineering, particularly intelligent reservoir management. Dr. Zhang has contributed to one national-level and one provincial-level research project and has also taken part in an industry consultancy project, demonstrating his ability to bridge academic research with practical applications. He has published peer-reviewed articles, including a notable study on gated recurrent unit-based dynamic characterization methods for horizontal wells in carbonate reservoirs, as well as a paper on closed-loop optimization systems for evaluating development potential with water-alternating gas flooding. With three patents under process and active membership in the Society of Petroleum Engineers, Dr. Zhang has positioned himself as a rising scholar committed to innovation. His contributions include refining the analytic hierarchy process through coupling with entropy weight methods for more objective production evaluation, as well as pioneering predictive models that enhance reservoir characterization. He aspires to continue developing transformative technologies that promote efficiency, sustainability, and innovation in petroleum exploration and production.

Profile: ORCID 

Featured Publications

Zhang, H. (2025). A closed-loop optimization system for evaluating the development effect and potential of producers with water alternating gas flooding. Processes.

Zhang, H. (2025). A dynamic characterization method for horizontal wells based on the gated recurrent unit: A case study of a carbonate reservoir in the Middle East. In Springer Series in Geomechanics and Geoengineering. Springer.

Dr. Zeyi Shang | Parallel Computing | High Performance Computing Award

Published on by Computer Scientists Awards

Zeyi Shang | Parallel Computing | High Performance Computing Award

Vice Dean of Department of Computer Science, Civil Aviation Flight University of China, China

Zeyi Shang is a lecturer at the School of Computer Science, Civil Aviation Flight University of China (CAFUC), Guanghan, where he has been serving since 2021. He earned his B.E. degree in Mechanical Design & Manufacture and Their Automation from Southwest Jiaotong University in 2010, followed by an M.E. degree in Theory and Technology of Civil Aircraft Maintenance from CAFUC in 2016. Pursuing advanced studies, he received a Ph.D. in Computer Science from Université Paris-Est Créteil (UPEC), France, in 2020 and a Ph.D. in Control Science and Engineering from Southwest Jiaotong University in 2021, reflecting his multidisciplinary expertise bridging mechanical systems, computer science, and control engineering. His research interests are diverse and interdisciplinary, encompassing membrane computing, reaction systems, FPGA development, robotics, and artificial intelligence, with a strong emphasis on advancing unconventional computing models and their hardware implementations. Dr. Shang has contributed significantly to the international research community through publications in reputable journals such as Electronics, Molecules, ACM Computing Surveys, and the International Journal of Unconventional Computing, addressing topics from FPGA architectures for numerical P systems to hardware implementations of reaction systems. In addition to his academic achievements, he has actively engaged with the scientific publishing community, serving as a reviewer for the Journal of Membrane Computing since 2019 and for Simulation: Transactions of the Society for Modeling and Simulation International since 2024. His contributions have been recognized internationally, as evidenced by receiving the prestigious International Membrane Computing Society (IMCS) Prize for the best Ph.D. thesis of the year 2020, a testament to the impact and innovation of his doctoral research. Combining rigorous academic training, cross-disciplinary research, and service to the scholarly community, Dr. Shang continues to advance the frontiers of unconventional computing and intelligent systems.

Profile: ORCID 

Featured Publications

Shang, Z., Verlan, S., Lu, J., Wei, Z., & Zhou, M. (2024). FPGA implementation of reaction systems. Electronics, 13(24), 4929.

Shang, Z., Wei, Z., Verlan, S., Li, J., & He, Z. (2023). An FPGA architecture for the RRT algorithm based on membrane computing. Electronics, 12(12), 2741.

Shang, Z., Verlan, S., Zhang, G., & Rong, H. (2021). FPGA implementations of numerical P systems. International Journal of Unconventional Computing, 16(2–3), 279–302.

Zhang, G., Shang, Z., Verlan, S., Martínez-del-Amor, M. Á., Yuan, C., Valencia-Cabrera, L., & Pérez-Jiménez, M. J. (2020). An overview of hardware implementation of membrane computing models. ACM Computing Surveys, 53(4), Article 90, 1–38.

Shang, Z., Verlan, S., Petre, I., & Zhang, G. (2019). Reaction systems and synchronous digital circuits. Molecules, 24(10), 1961.

Ms. Ivett-Greta Zsak | Data-Driven | Best Researcher Award

Published on by Computer Scientists Awards

Ivett-Greta Zsak | Data-Driven | Best Researcher Award

PhD Candidate, Technical University of Cluj-Napoca, Romania

Ms. Ivett-Greta Zsak, a Romanian architect, lecturer, and PhD candidate at the Technical University of Cluj-Napoca, is an influential figure in sustainable architecture and heritage preservation. She earned her Diploma in Architecture from the University of Oradea under the board of UAUIM Bucharest and has since established herself as a practicing architect and administrator of Zero Positive Architecture SRL. Currently serving as an expert at Living Lab 10 within the EU GREEN European University Alliance for Sustainability and as an associate lecturer at the University of Oradea, she combines academic engagement with professional innovation. Her doctoral research focuses on civil engineering and installation, contributing to frameworks such as the Building Identity Passport (BIP) for prefabricated housing rehabilitation, published in Sustainability in 2025. She is actively engaged in heritage protection as the coordinator of the Ambulance for Monuments – Bihor branch and has co-authored the national Architecture Guidelines for Rural Areas. Recognized with multiple awards, including two first prizes at the 2023 Transylvania Architecture Biennale, she continues to impact both theory and practice in architecture. With 11 citations across 2 documents and an h-index of 2, her scholarly work, though emerging, reflects her growing influence at the intersection of sustainable design, cultural heritage, and participatory architecture.

Profile: Scopus | ORCID

Featured Publications

Zsak, I.-G., Pescaru, A. H., & Manea, L.-D. (2025). Beyond energy efficiency: Integrating health, building pathology, and community through the building identity passport for prefabricated housing. Sustainability, 17(17), 8176.

Zsak, G. I., Pescaru, A. H., & Manea, L.-D. (2024). Analysis on using 3D scanning and BIM to reduce the physical and non-physical construction waste for sustainable fireproofing of steel trusses. Sustainability, 16(5), 1832.

Zsak, G. I. (2020). Ghiduri de arhitectură pentru încadrarea în specificul local din mediul rural. The Order of Architects of Romania.

Zsak, G. I. (2019, September 18). Regeneration of the industrial heritage in the central area of Oradea. In Materials Science and Engineering Conference Series (Vol. 603). IOP Publishing.

Mr. Xing Li | GPU-Acceleration | Best Researcher Award

Published on by Computer Scientists Awards

Xing Li | GPU-Acceleration | Best Researcher Award

HSBC Bank, China

Leon  Li is a seasoned business and technology leader with over two decades of global experience spanning finance, insurance, high-tech, healthcare, and manufacturing sectors. An MBA graduate of Peking University NSD & Vlerick Business School and holder of a Master in Global Finance from Fordham Gabelli School of Business, he also earned advanced degrees in software engineering and applied mathematics from leading Chinese universities. Leon is a certified Project Management Professional (PMP) and a pioneer in artificial intelligence applications, particularly in machine learning, deep learning, and generative AI. Currently serving as Senior Vice President at HSBC Bank (China), he leads applied AI research, AI safety governance, and innovation strategies in corporate and investment banking. His previous leadership roles include steering digital transformation at HSBC Wealth & Personal Banking, managing SPAC IPOs and M&A projects at SPACGlobal, and advising high-value technology acquisitions, such as Apple’s landmark purchase of Yi+ AI. As CEO and founder of IntelLink, he mentored startups and facilitated equity fundraising, while earlier roles at MetLife, MedImpact, Softtek, and Sun Microsystems strengthened his cross-industry expertise. A bilingual professional in Mandarin and English, Leon has published research on GPU-accelerated option valuation, financial data science, and stock prediction, advancing AI-driven finance.

Profile: ORCID | Google Scholar

Featured Publications

Li, L. X. (2025). GPU-accelerated PSO for high-performance American option valuation. Applied Sciences, 15(18), 9961.

Li, L. X. (2024). GPU-accelerated American option pricing: The case of the Longstaff–Schwartz Monte Carlo model. The Journal of Derivatives, 32(2), 216.

Li, L. X. (2023). Using the graphics processing unit to evaluate American-style derivatives. The Journal of Financial Data Science, 5(3), 127.

Li, L. X. (2023). Predicting stock moves: An example from China. SSRN Electronic Journal.