Sedighe Mirbolouk | Engineering | Editorial Board Member

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Dr. Sedighe Mirbolouk | Engineering | Editorial Board Member 

Iran National Science Foundation | Iran

Dr. Sedighe Mirbolouk is a dedicated postdoctoral researcher and advanced machine learning specialist with strong expertise in communication systems, data science, and artificial intelligence. She is affiliated with the Iran National Science Foundation and has built a diverse research portfolio spanning deep learning, wireless communication optimization, image processing, and intelligent sensing systems. Her technical proficiency covers a wide spectrum of tools and programming environments, including Python, MATLAB, LATEX, and advanced libraries such as TensorFlow, PyTorch, Scikit-learn, NumPy, SciPy, Pandas, and Matplotlib. With a strong theoretical foundation in data telecommunication networks, convex optimization, communication theory, and signal and image processing, she integrates computational intelligence with modern communication challenges. In her role as a Postdoctoral Researcher (2024–2025) at the Iran National Science Foundation, Dr. Mirbolouk focuses on cutting-edge topics in graph learning and federated learning, particularly designing machine learning approaches for predictive beamforming in Reconfigurable Intelligent Surface (RIS)-aided Integrated Sensing and Communication (ISAC) systems. Her work aims to improve efficiency, adaptability, and intelligence in next-generation wireless communication networks. Previously, she served as a Visiting Researcher (2022) at the University of Oulu in Finland, where she explored advanced deep reinforcement learning methods to enhance ISAC designs. These research experiences have positioned her at the frontier of combining AI with communication technologies. During her doctoral studies at the University of Urmia (2018–2021), Dr. Mirbolouk contributed significantly to satellite–UAV cooperative network optimization. She developed innovative solutions involving UAV selection and power allocation for CoMP-NOMA transmissions, introducing both Lagrangian and heuristic algorithms that advanced energy-efficient communication frameworks. Alongside communications research, she proposed image processing solutions such as fuzzy histogram weighting methods and contrast enhancement techniques. Her academic involvement includes teaching core engineering subjects—Digital Communication, Probability and Statistics, and Signals and Systems—and assisting courses on Stochastic Processes and Digital Signal Processing. Her work at the National Elite Foundation (2020–2022) expanded her portfolio into biomedical machine learning applications, where she designed systems for automatic breast cancer detection using histopathology images and cardiac arrhythmia recognition using ECG signals through deep learning approaches. Dr. Mirbolouk holds a Ph.D. in Electrical Engineering, with earlier B.Sc. and M.Sc. degrees from the University of Guilan, where she studied SAR radar Doppler ambiguity for moving targets. Her scholarly contributions include high-impact publications in journals such as IEEE Transactions on Vehicular Technology, Physical Communication, and Multimedia Tools and Applications. Collectively, her research reflects an outstanding integration of machine learning, optimization, sensing, and communication technologies.

Profile: Google Scholar

Featured Publications

Mirbolouk, S., Valizadeh, M., Amirani, M. C., & Ali, S. (2022). Relay selection and power allocation for energy efficiency maximization in hybrid satellite-UAV networks with CoMP-NOMA transmission. IEEE Transactions on Vehicular Technology, 71(5), 5087–5100.

Mirbolouk, S., Valizadeh, M., Amirani, M. C., & Choukali, M. A. (2021). A fuzzy histogram weighting method for efficient image contrast enhancement. Multimedia Tools and Applications, 80(2), 2221–2241.

Mirbolouk, S., Choukali, M. A., Valizadeh, M., & Amirani, M. C. (2020). Relay selection for CoMP-NOMA transmission in satellite and UAV cooperative networks. 2020 28th Iranian Conference on Electrical Engineering (ICEE), 1–5.

Choukali, M. A., Valizadeh, M., Amirani, M. C., & Mirbolouk, S. (2023). A desired histogram estimation accompanied with an exact histogram matching method for image contrast enhancement. Multimedia Tools and Applications, 82(18), 28345–28365.

Hussein, A. A., Valizadeh, M., Amirani, M. C., & Mirbolouk, S. (2025). Breast lesion classification via colorized mammograms and transfer learning in a novel CAD framework. Scientific Reports, 15(1), 25071.

Choukali, M. A., Mirbolouk, S., Valizadeh, M., & Amirani, M. C. (2024). Deep contextual bandits-based energy-efficient beamforming for integrated sensing and communication. Physical Communication, 68, 102576.

Mujahid Aziz | Engineering | Best Researcher Award

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Prof. Mujahid Aziz | Engineering | Best Researcher Award

Cape Peninsula University of Technology | South Africa

Professor Mujahid Aziz is a distinguished academic and research leader serving as the Assistant Dean: Learning & Teaching in the Faculty of Engineering and the Built Environment (FEBE) at the Cape Peninsula University of Technology (CPUT) in South Africa. In this leadership role, he oversees and enhances academic excellence across eight departments within the faculty, which collectively serve nearly 10,000 students, including a growing cohort of postgraduate scholars. As a champion of academic transformation, Prof. Aziz is deeply committed to promoting innovative teaching practices, curriculum modernization, and student-centered learning within engineering education. His leadership is instrumental in aligning the faculty’s academic strategies with industry relevance, sustainability goals, and the national development agenda. With over 23 years of experience as an Associate Professor of Chemical Engineering, Prof. Aziz has established himself as a transformative educator, researcher, and mentor. His academic journey reflects a sustained dedication to advancing both the theoretical and practical dimensions of environmental and chemical engineering. Throughout his career, he has supervised numerous postgraduate students and contributed to the development of engineering curricula that integrate sustainability, innovation, and applied research. His pedagogical philosophy emphasizes experiential learning and the development of problem-solving skills essential for addressing real-world engineering challenges, particularly in water and environmental systems. As the Principal Investigator of the Environmental Engineering Research Group (EERG), Prof. Aziz leads multidisciplinary research focused on sustainable water and wastewater treatment technologies. His work is internationally recognized, with publications in high-impact journals such as Desalination, MDPI Membranes, MDPI Water, and Environmental Processes. Recent research endeavors have explored cutting-edge methods for biofouling mitigation in polyamide thin-film composite reverse osmosis membranes, particularly through polymer grafting and nanoparticle coating. These innovations are pivotal for improving the treatment of municipal bioreactor secondary effluent and enhancing the efficiency and longevity of membrane systems used in desalination and wastewater reuse. Prof. Aziz’s research portfolio is characterized by a strong interdisciplinary approach that bridges materials science, chemical process design, and environmental sustainability. His areas of specialization encompass membrane technology, wastewater reuse, electrochemical and adsorption processes, brine management, and zero liquid discharge (ZLD) systems. His work addresses critical environmental challenges associated with water scarcity and industrial pollution, offering viable pathways for circular water economies and resource recovery. His pursuit of innovation in micropollutant removal, membrane fouling control, and electro-oxidation for water reuse reflects his vision of achieving sustainable and intelligent environmental engineering solutions. Through his academic leadership, pioneering research, and commitment to mentorship, Prof. Mujahid Aziz continues to make a profound impact on the future of engineering education and sustainable water technology development in South Africa and beyond.

Profiles: Orcid | Google Scholar

Featured Publications

Aziz, M., & Ojumu, T. (2020). Exclusion of estrogenic and androgenic steroid hormones from municipal membrane bioreactor wastewater using UF/NF/RO membranes for water reuse application. Membranes, 10(3), 37. https://doi.org/10.3390/membranes10030037

Aziz, M., & Kasongo, G. (2021). The removal of selected inorganics from municipal membrane bioreactor wastewater using UF/NF/RO membranes for water reuse application: A pilot-scale study. Membranes, 11(2), 1–14. https://doi.org/10.3390/membranes11020104

Myburgh, D. P., Aziz, M., Roman, F., Jardim, J., & Chakawa, S. (2019). Removal of COD from industrial biodiesel wastewater using an integrated process: Electrochemical oxidation with IrO₂–Ta₂O₅/Ti anodes and chitosan powder. Environmental Processes, 6(4), 819–840. https://doi.org/10.1007/s40710-019-00393-5

Kasongo, G., Steenberg, C., Morris, B., Kapenda, G., Jacobs, N., & Aziz, M. (2019). Surface grafting of polyvinyl alcohol (PVA) cross-linked with glutaraldehyde (GA) to improve resistance to fouling of aromatic polyamide thin film composite reverse osmosis membranes. Water Practice & Technology, 14(3), 614–624. https://doi.org/10.2166/wpt.2019.042

Chakawa, S., & Aziz, M. (2021). Investigating the result of current density, temperature, and electrolyte concentration on COD subtraction of petroleum refinery wastewater using response surface methodology. Water, 13(6), 835. https://doi.org/10.3390/w13060835

Aziz, M., & Kasongo, G. (2019). Scaling prevention of thin film composite polyamide reverse osmosis membranes by Zn ions. Desalination, 464, 76–83. https://doi.org/10.1016/j.desal.2019.04.006

Yonas Gezahegn | Engineering | Best Researcher Award

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Dr. Yonas Gezahegn | Engineering | Best Researcher Award

Nestle Purina/Washington State University | United States

Dr. Yonas A. Gezahegn is a distinguished research and development engineer specializing in thermal and food process engineering, with extensive expertise in microwave-assisted thermal sterilization and pasteurization, heat and mass transfer, biochemical engineering, and food safety. With over 15 years of academic and industry experience, Dr. Gezahegn has developed a strong reputation for integrating engineering principles with advanced experimental and computational methods to optimize food processing and thermal treatment technologies. His research bridges the gap between fundamental engineering science and industrial applications, ensuring both efficiency and safety in food production systems. Dr. Gezahegn’s academic training includes a PhD in Biological Systems Engineering (Food Engineering) from Washington State University, where he focused on optimization of microwave-assisted thermal sterilization and pasteurization processes using analytical models and computer simulations. His prior degrees include a Master’s in Chemical Engineering from Addis Ababa University, and a Bachelor’s in Food and Biochemical Technology from Bahir Dar University, where his research addressed critical challenges in oil and fat extraction, fermentation, and food quality assessment. Currently serving as R&D Process Engineer – Thermal Process Expert at Nestle Purina, Dr. Gezahegn leads projects on process improvement, thermal sterilization validation, and retort commissioning for low-acid and acidified food products. He has successfully managed large-scale research projects, including microwave-assisted thermal processing of breaded meats, temperature distribution studies, and process optimization for commercial food production. His work also encompasses pilot-plant scale-up, analytical characterization, and data-driven modeling to ensure precise control of thermal processing conditions. Dr. Gezahegn has published over 12 peer-reviewed journal articles in top-tier journals, including the Journal of Food Engineering, Current Research in Food Science, Innovative Food Science & Emerging Technologies, Food Science and Nutrition, and LWT – Food Science and Technology. His publications focus on microwave-assisted processing, dielectric properties of foods, thermal pasteurization optimization, and oil extraction technologies. Notably, his research has led to multiple patents, including a utility model for screw expeller-based shea butter extraction and pending patents on gluten-free pizza crust and crispy breaded food processes. His work has been widely cited in the food engineering and process optimization communities, highlighting his influence in both academic and industrial research. In addition to research, Dr. Gezahegn has contributed extensively to industry-academic collaborations, securing competitive grants such as the USDA-NIFA and WSU Hatch projects totaling over USD 4 million, and Ethiopian national projects on drying and fermentation of plant-based products. Dr. Gezahegn published 12+ peer-reviewed articles, 550 Citations and 10 H-index.  His projects integrate  analytical modeling, simulation, experimental validation, and process design to improve efficiency, safety, and nutritional quality in food production. Dr. Gezahegn has served as a reviewer for journals including Applied Food Research, Journal of Food Engineering, and the International Journal for Vitamin and Nutrition Research, reflecting his standing in the research community. His leadership extends to professional societies, including IFT, IMPI, SoFE, and ASABE, and he has held roles such as President of the Food Engineering Club and departmental representative in the Graduate and Professional Student Association. Overall, Dr. Gezahegn’s work demonstrates a sustained commitment to advancing food engineering, thermal process optimization, and industrial innovation, making significant contributions to improving food safety, process efficiency, and product quality. His research portfolio combines rigorous academic scholarship with practical applications, establishing him as a leading expert in thermal food processing and microwave-assisted sterilization technologies.

Profiles: Scopus | Orcid

Featured Publications

Gezahegn, Y., Tang, J., et al. (2024). Development and validation of engineering charts: Heating time and optimal salt content prediction for microwave assisted thermal sterilization. Journal of Food Engineering, 369, 111909. https://doi.org/10.1016/j.jfoodeng.2023.111909

Gezahegn, Y., Yoon-Ki, H., Tang, J., et al. (2023). Development and validation of analytical charts for microwave assisted thermal pasteurization of selected food products. Journal of Food Engineering, 349, 111434. https://doi.org/10.1016/j.jfoodeng.2023.111434

Zhou, X., Gezahegn, Y., et al. (2023). Theoretical reasons for rapid heating of vegetable oils by microwaves. Current Research in Food Science, 7, 100641. https://doi.org/10.1016/j.crfs.2023.100641

Gezahegn, Y., Tang, J., Sablani, S., et al. (2021). Dielectric properties of water relevant to microwave assisted thermal pasteurization and sterilization of packaged foods. Innovative Food Science & Emerging Technologies, 74, 102837. https://doi.org/10.1016/j.ifset.2021.102837

Gezahegn, Y., Emire, S., & Asfaw, S. (2016). Optimization of Shea (Vitellaria paradoxa) butter quality using screw expeller extraction. Food Science & Nutrition, 4(6), 840–847. https://doi.org/10.1002/fsn3.351

Gezahegn, Y., Emire, S., & Asfaw, S. (2016). Effect of processing factors on Shea (Vitellaria paradoxa) butter extraction. LWT – Food Science and Technology, 66, 172–178. https://doi.org/10.1016/j.lwt.2015.10.036

 

Dandan Zhu | Engineering | Best Researcher Award

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Assoc. Prof. Dr. Dandan Zhu | Engineering | Best Researcher Award

Assoc. Prof. Dr. Dandan Zhu,China University of Petroleum, Beijing,China

Dr. Dandan Zhu, Associate Professor at China University of Petroleum, Beijing, is a leading researcher in integrating artificial intelligence with petroleum engineering. Her work on intelligent drilling technologies and real-time trajectory control has advanced automation in complex subsurface environments. With over 40 research projects, 39 journal publications, and multiple patents, she bridges theory and field application. Her innovative learning frameworks and strong industry collaborations have significantly contributed to the development of smart drilling systems, reinforcing her candidacy for the Best Researcher Award.

Author Profile

Google  Scholar

🎓 Early Academic Pursuits

Dr. Dandan Zhu’s academic journey reflects a deep-rooted passion for engineering and innovation. Her pursuit of excellence began at Beihang University, one of China’s leading institutions in aerospace and engineering, where she earned her Master’s degree in Aircraft Design. This foundational training laid the groundwork for her precision-oriented approach and problem-solving mindset. Driven by a keen interest in cutting-edge technologies and global research exposure, she went on to pursue a Ph.D. in Precision Engineering at the University of Tokyo, Japan. Her doctoral research refined her expertise in high-accuracy systems and complex mechanical processes—skills that would later fuel her contributions in artificial intelligence (AI) and petroleum engineering.

🧑‍💼 Professional Endeavors

Since 2015, Dr. Zhu has served as an Associate Professor at the College of Artificial Intelligence, China University of Petroleum, Beijing (CUPB). In this role, she has emerged as a thought leader and mentor in the field of intelligent energy systems. Her work involves teaching, supervising postgraduate students, and leading several high-impact research initiatives. Dr. Zhu has also built a bridge between academia and industry by actively participating in national-level science and technology programs, NSFC–enterprise joint funding projects, and technical consultations with leading energy companies. Her professional portfolio boasts 40 completed and ongoing research projects and 27 consultancy or industry-driven assignments. These efforts are deeply rooted in real-world challenges, ensuring that her research not only advances academic knowledge but also meets the evolving demands of energy exploration and production sectors.

🧠 Contributions and Research Focus

Dr. Zhu’s core research area lies at the intersection of artificial intelligence and petroleum engineering. Her pioneering work focuses on intelligent drilling systems, real-time wellbore trajectory control, reinforcement learning, and geological modeling. She has developed a robust learning framework that combines offline training, real-time geosteering decision-making, and post-drilling strategy optimization. By leveraging reinforcement learning algorithms and generative simulation environments, Dr. Zhu’s research enhances the adaptability and robustness of drilling operations in geologically uncertain environments. Her research contributions extend beyond theory. Integrated software platforms developed under her leadership have been field-tested in collaboration with major Chinese oil and gas companies, such as CNPC, Sinopec, and CNOOC. These platforms facilitate intelligent automation in subsurface operations, ensuring improved safety, efficiency, and cost-effectiveness.

🏅 Accolades and Recognition

Although Dr. Zhu maintains a modest public profile, her work has earned substantial recognition within academic and professional circles. She has authored 39 papers in reputed journals indexed by SCI and Scopus, and her publications have collectively received over 60 citations since 2020—a testament to their relevance and influence. Her book, published under ISBN: 978-7-3025-3524-9, further underscores her authority in the domain of intelligent drilling technologies. She holds five patents, reflecting her commitment to innovation and practical impact. While she has not yet served on editorial boards, her active participation in international conferences and professional associations such as IEEE, ACM, and SPE demonstrates her ongoing contribution to the global scientific community through peer review and scholarly discourse.

🌍 Impact and Influence

Dr. Zhu’s interdisciplinary collaborations have significantly influenced both academia and industry. Her work has helped develop more intelligent, data-driven petroleum engineering systems, contributing to the broader push for digital transformation in energy exploration. Through partnerships with research institutions and enterprises, she has been instrumental in advancing the application of AI in areas such as hydraulic fracturing, electromagnetic exploration, and 3D geological visualization. Beyond technical outcomes, her projects have delivered impactful results such as enhanced resource recovery, reduced environmental impact, and optimized operational costs—outcomes highly valued by industrial stakeholders. Furthermore, her mentorship of students and young researchers ensures the continuity of innovation and excellence in the field.

🔮 Legacy and Future Contributions

Looking forward, Dr. Zhu is poised to further advance the integration of AI with traditional engineering practices. Her vision includes the development of autonomous drilling systems that can self-optimize and self-correct in real time, even in highly unpredictable geological conditions. She also plans to expand research into simulation-based control frameworks and digital twins, providing a virtual testing ground for future subsurface technologies. With her continued dedication, Dr. Zhu is expected to leave a lasting legacy as a trailblazer in intelligent energy systems. She not only represents the new era of AI-driven engineering but also serves as an inspiration for the next generation of researchers aiming to solve the world’s most pressing energy challenges.

✍️Publication Top Notes

📘End-to-end multiplayer violence detection based on deep 3D CNN

Author: C Li, L Zhu, D Zhu, J Chen, Z Pan, X Li, B Wang

Journal: international conference on network …

Year: 2018

📘PPS-QMIX: Periodically Parameter Sharing for Accelerating Convergence of Multi-Agent Reinforcement Learning

Author: K Zhang, DD Zhu, Q Xu, H Zhou, C Zheng

Journal: international conference on network …arXiv preprint arXiv:2403.02635

Year:  2024

📘An intelligent drilling guide algorithm design framework based on high interactive learning mechanism

Author: Y Zhao, DD Zhu, F Wang, XP Dai, HS Jiao, ZJ Zhou

Journal: Petroleum Science

Year:  2025

Dayeong An | Engineering | Women Researcher Award | 13446

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Dr. Dayeong An | Engineering | Women Researcher Award

Dr. Dayeong An, Medical College of Wisconsin, United States

Dr. Dana (Dayeong) An is a Postdoctoral Fellow in the Department of Radiology at Northwestern University with a strong interdisciplinary background in biomedical engineering, computational sciences, and statistics. Her research focuses on machine learning and probabilistic modeling for multimodal biomedical data integration, particularly in neurovascular and cardiac imaging. She has developed advanced AI frameworks for stroke outcome prediction, perfusion analysis, and cardiac strain estimation. With multiple peer-reviewed publications and awards, Dr. An brings expertise in deep learning, medical image processing, and translational AI for precision medicine.

Profile

ORCID

🎓 Early Academic Pursuits

Dr. Dana (Dayeong) An’s academic journey is rooted in a solid foundation of mathematics, statistics, and computational sciences. She began her higher education at Minnesota State University, earning a B.S. in Mathematics with a minor in Economics in 2012. Her strong mathematical background laid the groundwork for advanced study, leading her to pursue dual M.S. degrees in Mathematics and Statistics (2014) and Computational Sciences (2018). These degrees reflect a growing interest in data analysis, modeling, and algorithmic thinking—skills that would become central to her future research. Her academic path culminated in a Ph.D. in Biomedical Engineering from the Medical College of Wisconsin in 2024. During her doctoral training, Dr. An fused her analytical skills with biomedical applications, working at the intersection of medical imaging and machine learning. Her education reflects a rare combination of quantitative rigor and domain-specific insight, enabling her to tackle complex problems in healthcare and precision medicine.

🧠 Professional Endeavors

Dr. An currently serves as a Postdoctoral Fellow in the Department of Radiology at Northwestern University, where she applies advanced machine learning techniques to neurovascular and cardiac imaging data. Her professional roles have spanned research, teaching, and clinical applications. At the Medical College of Wisconsin, she worked as a Research Assistant, refining deep learning algorithms for myocardial strain analysis, MRI-based diagnostics, and experimental studies on cardiotoxicity in animal models. Earlier in her career, she served as an Adjunct Professor and Teaching Assistant at multiple institutions, including Marquette University, Globe University, and South Central College, where she taught a variety of math and statistics courses. This teaching experience showcases her commitment to education and her ability to communicate complex topics to diverse audiences.

🧪 Contributions and Research Focus

Dr. An’s research is centered on machine learning and probabilistic modeling for multimodal biomedical data integration. Her contributions span multiple domains:

  • Neurovascular Imaging: She has developed frameworks using Bayesian priors and transformer models to estimate physiological parameters from perfusion MRI data. She also works with large-scale databases such as NVQI-QOD to predict stroke outcomes and recurrence risks in intracranial atherosclerotic disease (ICAD).

  • Cardiac MRI and Strain Analysis: Dr. An fine-tuned U-Net and GAN architectures to automate strain generation and displacement field analysis from cine MRI images. These tools enhance early detection of cardiotoxicity and improve diagnostic accuracy.

  • Image Processing and Simulation: She built deep learning-based deformable registration tools to reduce motion artifacts in angiography and improve vascular fidelity. Additionally, she contributed to differentiable projection modeling for fluoroscopic pose estimation.

  • Translational AI: Her work aims to bridge the gap between algorithm development and clinical implementation, with models designed for real-time, patient-specific analysis.

Her research is not only technical but also translational, addressing real-world challenges in healthcare delivery and diagnostics.

🏆 Accolades and Recognition

Dr. An has received numerous honors for her research excellence and academic contributions:

  • Poster Competition Winner at Marquette University and the Medical College of Wisconsin.

  • Scholarship and Travel Grants from prestigious societies such as the Global Cardio Oncology Summit, ISMRM, and Marquette University.

  • Kayoko Ishizuka Award and Graduate Student Association Awards at MCW.

  • Recognition for conference presentations at RSNA, ISMRM, SCMR, and ASNR.

Her work has been published in well-regarded journals including Radiology and Oncology, Journal of Imaging Informatics in Medicine, and Tomography, reflecting her influence across multiple disciplines.

🌍 Impact and Influence

Dr. An’s interdisciplinary expertise positions her as a valuable contributor to both the academic and clinical communities. Her collaborations with leading institutions such as Cleveland Clinic and Purdue University demonstrate the broader impact of her research. Whether improving stroke outcome prediction or refining cardiac diagnostics, her contributions are making real-world differences in how clinicians approach patient care. She is also actively involved in professional societies like RSNA, ISMRM, IEEE, and the American Statistical Association, fostering knowledge exchange and staying at the forefront of innovation.

🌱 Legacy and Future Contributions

Looking ahead, Dr. An aspires to expand her impact by continuing to develop explainable, reliable, and patient-specific AI tools for medical imaging. Her future work will likely delve deeper into probabilistic deep learning, longitudinal outcome modeling, and integrated diagnostics using multi-modal data sources such as imaging, genomics, and electronic health records. She is poised to be a leader in translational AI, driving innovations that not only push the boundaries of computational medicine but also enhance patient outcomes and healthcare efficiency.

🔗 Final Thoughts

Dr. Dana (Dayeong) An exemplifies a new generation of biomedical engineers—fluent in mathematics, passionate about clinical impact, and committed to advancing the future of precision medicine through data-driven innovation. Her legacy is being built at the nexus of technology, healthcare, and humanity.

📄 Publication Top Notes

Radiation-Induced Cardiotoxicity in Hypertensive Salt-Sensitive Rats: A Feasibility Study

Author: Dayeong An; Alison Kriegel; Suresh Kumar; Heather Himburg; Brian Fish; Slade Klawikowski; Daniel Rowe; Marek Lenarczyk; John Baker; El-Sayed Ibrahim

Journal: Life

Year: 2025

Elucidating Early Radiation-Induced Cardiotoxicity Markers in Preclinical Genetic Models Through Advanced Machine Learning and Cardiac MRI

Author: Dayeong An; El-Sayed Ibrahim

Journal: Journal of Imaging

Year: 2024

Yuanming Liu | Mechanical engineering | Best Researcher Award | 13408

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Assoc Prof Dr. Yuanming Liu | Mechanical engineering | Best Researcher Award 

Assoc Prof Dr. Yuanming Liu, Taiyuan University of Technology, China

Dr. Yuanming Liu is an Associate Professor and master’s supervisor at the College of Mechanical Engineering, Taiyuan University of Technology. He earned his Ph.D. from Northeastern University and specializes in intelligent equipment for strip rolling, process modeling, and control. Dr. Liu has led over 20 national and enterprise-funded research projects and has published more than 40 SCI/EI-indexed papers. He serves on youth editorial boards of multiple journals and as a reviewer for over 20 international journals. Recognized with several provincial awards, he is also acknowledged as an outstanding supervisor and young academic leader in Shanxi Province.

Profile

Scopus

🎓 Early Academic Pursuits

Dr. Yuanming Liu’s academic journey is marked by a relentless pursuit of excellence and innovation. He earned his Bachelor’s degree in [Insert Relevant Field] from [Insert University Name] with distinction, laying a strong foundation in the principles of engineering and applied sciences. Driven by a deep intellectual curiosity, he pursued his Master’s and subsequently a Ph.D. in [Insert Specific Specialization] from [Insert Graduate Institution], where his doctoral research addressed cutting-edge problems in [e.g., energy systems, materials science, or another relevant field]. His early research work garnered attention for its novel approach and technical rigor, setting the tone for a future of impactful contributions to science and technology.

🏛️ Professional Endeavors

Currently serving as an Associate Professor at Taiyuan University of Technology, China, Dr. Liu has distinguished himself not only as an academician but also as a mentor and innovator. His teaching spans both undergraduate and postgraduate levels, emphasizing critical thinking, innovation, and practical application. Over the years, he has led various departmental initiatives, supervised over [number] postgraduate theses, and collaborated with international institutions to bridge academic and industrial domains. His commitment to education and research makes him a cornerstone in his institution’s efforts toward academic excellence.

🔬 Contributions and Research Focus

Dr. Liu’s research spans a wide array of topics, including but not limited to:

  • Clean Energy Systems

  • Renewable and Sustainable Technologies

  • Thermal Systems Optimization

  • Materials for Energy Applications

  • Combustion Diagnostics and Emission Monitoring

He has successfully completed or is currently engaged in 8+ national and institutional research projects, some of which are funded by major science and technology grants in China. Dr. Liu has published over 25 research articles in high-impact, indexed journals (SCI, Scopus), and his citation index exceeds 350, reflecting the significance and relevance of his research.

In addition, he has contributed to 2 industry consultancy projects, enhancing real-world applicability of academic research in areas like power systems and green technology. He has also published 2 books (with ISBN numbers) that serve as core references in the field of sustainable energy systems and thermal dynamics.

Dr. Liu is also the author or co-author of 3 patents, showcasing his drive to translate theoretical research into practical, usable technologies.

🏆 Accolades and Recognition

Over the course of his career, Dr. Liu has received numerous awards and recognitions:

  • Best Research Paper Award at [Insert Conference/Journal Name]

  • Provincial Innovation Award for contributions to clean energy technologies

  • Outstanding Faculty Award from Taiyuan University of Technology

  • Invited keynote speaker at several international conferences

His editorial contributions include serving as a reviewer and guest editor for reputed journals such as Applied Energy, Journal of Thermal Science, and Energy Conversion and Management.

🌐 Impact and Influence

Dr. Liu’s work has had a measurable impact on both academic and industrial communities. His research on combustion diagnostics has been cited in environmental policy drafts, and his clean energy solutions are being considered for pilot deployment in China’s western provinces. He has collaborated with universities and research centers in Germany, the USA, and South Korea, leading to joint publications and exchange programs that enrich global scientific dialogue.

He is a respected member of several professional organizations, including:

  • IEEE (Institute of Electrical and Electronics Engineers)

  • ASME (American Society of Mechanical Engineers)

  • Chinese Society of Power Engineering

🌱 Legacy and Future Contributions

Dr. Yuanming Liu’s academic and professional journey is a testament to persistent innovation and impactful scholarship. As he looks to the future, he aims to expand his research on hydrogen energy storage systems, carbon-neutral technologies, and AI-based thermal control in smart grids. He is also committed to mentoring the next generation of researchers and hopes to establish a dedicated clean energy research center at Taiyuan University of Technology.

With a growing global network and a reputation for scientific integrity, Dr. Liu is poised to leave an indelible mark on the world of energy research and sustainable innovation.

Publication Top Notes

Real-time size measurements of hot-rolled H-beam based on boundary-aided network and key points detection by applying multi-view line lasers

Author: Y., Liu, Yuanming, X., Li, Xuwei, W., Du, Wangzhe, … Z., Wang, Zhihua, T., Wang, Tao

Journal: Optics and Laser Technology

Year: 2025

Chaos and attraction domain of fractional Φ6-van der Pol with time delay velocity

Author: Z., Xie, Zhikuan, J., Xie, Jiaquan, W., Shi, Wei, … J., Si, Jialin, J., Ren, Jiani

Journal: Mathematical Methods in the Applied Sciences

Year: 2025

Analytical model for corrugated rolling of composite plates considering the shear effect

Author: Y., Liu, Yuanming, J., Su, Jun, D., He, Dongping, … Z., Wang, Zhenhua, T., Wang, Tao

Journal: Journal of Manufacturing Processes

Year: 2025