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.

Soujanya Reddy Annapareddy | Engineering | Women Researcher Award

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Mrs. Soujanyareddy Annapareddy | Engineering | Women Researcher Award

TAE Power Solutions | United States

Mrs. Soujanya Reddy Annapareddy is a seasoned Firmware Automation and Software Test Engineer with over 7.5 years of professional experience in embedded systems testing, automation frameworks, and data-driven validation methodologies. Her research and professional interests lie at the intersection of firmware validation, automation engineering, and intelligent system testing, focusing on how advanced test automation techniques enhance the performance, reliability, and scalability of embedded and IoT systems. At TAE Power Solutions, she has contributed to the automation and validation of Battery Energy Storage System (BESS) control platforms, integrating hardware-in-the-loop (HIL) environments and open-source frameworks such as PyTest, pandas, and matplotlib to improve regression coverage and testing efficiency. Her work explores the application of data analytics, fault-injection methods, and CI/CD pipeline integration in firmware testing to ensure real-world performance and fault tolerance. Her prior experience at Google Inc. involved automation testing for Android devices, wearable technologies, and data center systems, where she developed automation scripts in Python, Go, and C++, applied object-oriented design principles, and leveraged tools such as Mobly, Blueberry, and Buganizer for large-scale system validation. Soujanya’s analytical research focuses on automated testing frameworks, system-level reliability modeling, and signal strength optimization in wireless and connectivity domains. Methodologically, she employs Python-based automation, statistical analysis, and cloud-integrated validation frameworks, with hands-on experience in Linux environments, GCP cloud infrastructure, and RF system automation. Her interdisciplinary expertise bridges firmware engineering, test analytics, and computer science, offering insights into how automation accelerates innovation in embedded systems. Soujanya holds a Master of Science in Computer Technology from Eastern Illinois University and a Bachelor of Technology in Electronics and Communication Engineering from Jawaharlal Nehru Technological University Hyderabad (JNTUH), where she graduated with distinction. Her academic projects and industrial research underscore her commitment to advancing intelligent automation, embedded testing, and data-driven system optimization in modern technology ecosystems.

Profile: Google Scholar

Featured Publications

Annapareddy, S. R. (2025). Edge AI for real-time fault detection in embedded systems. International Journal of Emerging Trends in Computer Science and Information Systems.

Annapareddy, S. R. (2024). Managing power flows and energy efficiency in embedded systems for BESS. IJAIDR – Journal of Advances in Developmental Research, 15(2), 1–5.

Annapareddy, S. R. (2024). Advanced fault detection and diagnostics in embedded control units for BESS. IJSAT – International Journal on Science and Technology, 15(4).

Annapareddy, S. R. (2024). Firmware architecture and safety standards in battery energy storage systems. International Journal of Innovative Research in Engineering.

Annapareddy, S. R. (2024). Optimizing Android device testing with automation frameworks. International Journal of Innovative Research and Creative Technology, 10(4), 1–7.

Annapareddy, S. R. (2024). Real-world applications of Python in firmware and software automation. International Journal of Innovative Research and Creative Technology, 10(2), 1–6.

Annapareddy, S. R. (2024). Advancements in firmware testing and validation techniques. ESP Journal of Engineering & Technology Advancements, 4(3).

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

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