Dr. Mohamed Hegab | Scheduling Automation | Best Researcher Award

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Dr. Mohamed Hegab | Scheduling Automation | Best Researcher Award

Dr. Mohamed Hegab | Professor | California State University | United States

Academic Background

Dr. Mohamed Hegab holds a PhD in Civil Engineering and is a licensed Professional Engineer with certifications in Project Management and Construction Management. His academic journey encompasses extensive training and research in infrastructure systems, project controls, and construction technology. With over three decades of experience in both academia and industry, he has contributed to advancing knowledge in construction planning, public-private partnerships, and AI-enabled construction automation. His scholarly impact is demonstrated through a robust portfolio of publications, books, and peer-reviewed research Citation Index: Google Scholar Citations ≈ 480 | h-index = 11 | i10-index = 12 reflecting his influence in the field. All supporting documents and credentials are verifiable upon request.

Research Focus

Dr. Hegab’s research centers on integrating artificial intelligence with construction planning and management. His work focuses on ontology-based frameworks for automated scheduling, digital twin integration, and smart infrastructure monitoring. He explores innovative approaches to construction productivity modeling, risk assessment, and project controls that bridge academic theory with industry practice.

Work Experience

Dr. Hegab has served as a Professor and Department Chair, leading civil engineering and construction management programs. His professional experience spans consulting for large-scale infrastructure projects, including metropolitan water systems and state transportation authorities. He has overseen multi-disciplinary teams, managed project budgets, and provided expert advisory services to public and private organizations. Beyond academia, he has held leadership positions in businesses supporting construction operations, demonstrating a unique blend of academic rigor and practical expertise.

Key Contributions

Dr. Hegab has pioneered the use of AI-driven semantic frameworks in construction planning, enabling automated project scheduling and constraint validation. His work has improved decision-making processes, minimized data fragmentation in digital models, and enhanced the implementation of Construction 4.0 practices. He has significantly influenced industry standards, academic curricula, and international research collaborations, bridging the gap between emerging technologies and practical infrastructure delivery.

Awards & Recognition

Dr. Hegab has been widely recognized for his contributions to construction engineering and management. His research and industry leadership have garnered national and international attention, earning accolades for innovation in project delivery, risk assessment, and AI integration in construction processes. His work continues to inspire academic peers and industry professionals globally.

Professional Roles & Memberships

Dr. Hegab actively contributes to professional organizations, including the American Society of Civil Engineers, Construction Management Association of America, Project Management Institute, and the Dispute Resolution Board Foundation. He serves as a senior evaluator for accreditation bodies and participates in multidisciplinary research collaborations with universities and research institutions worldwide, supporting the advancement of construction engineering education and practice.

Publication Profile

Scopus | Google Scholar

Featured Publications

Hegab, M., Smith, G. R. (2007). Delay time analysis in microtunneling projects. Journal of Construction Engineering and Management, 133, 191-195.

Nassar, K., Gunnarsson, H. G., Hegab, M. (2005). Using Weibull analysis for evaluation of cost and schedule performance. Journal of Construction Engineering and Management, 131, 1257-1262.

Hegab, M., Salem, O. M. (2010). Ranking of the factors affecting productivity of microtunneling projects. Journal of Pipeline Systems Engineering and Practice, 1, 42-52.

Ali, S., Zayed, T., Hegab, M. (2007). Modeling the effect of subjective factors on productivity of trenchless technology. Journal of Construction Engineering and Management, 133, 743-748.
Elwakil, E., Hegab, M. (2018). Risk management for power purchase agreements. IEEE Conference on Technologies for Sustainability, 1-6.

Impact Statement / Vision

Dr. Hegab envisions a future where AI-driven methodologies and digital integration transform construction management, enabling smarter, safer, and more efficient infrastructure systems. His work continues to advance knowledge, inform policy, and inspire innovation across academia and industry globally.

Wenwei Luo | Automation | Best Researcher Award

Published on by Computer Scientists Awards

Mr. Wenwei Luo | Automation | Best Researcher Award

Mr. Wenwei Luo at Institute of Logistics Science and Engineering, Shanghai Maritime University, China

Wenwei Luo is a passionate robotics researcher pursuing his Master’s degree at Shanghai Maritime University, specializing in control science and engineering. With a strong foundation in robotics engineering from Zhejiang Normal University, he has demonstrated academic excellence, technical proficiency, and innovative thinking in reinforcement learning and evolutionary robotics. Wenwei has published impactful research, led interdisciplinary projects, and earned recognition in national competitions. He possesses a unique combination of embedded systems expertise and AI-based control strategies, positioning him as a rising talent in intelligent robotics. His vision is to bridge adaptive learning and real-world robotics for autonomous systems. 🤖📚🔍

Publication Profile

Orcid

Academic Background

Wenwei Luo is currently pursuing a Master’s degree in Control Science and Engineering at Shanghai Maritime University under Associate Professor Bo Li, with a GPA of 3.84/4.0 and double First Academic Scholarships. His research interests span reinforcement learning, adaptive control, and evolutionary robotics. Previously, he earned his Bachelor’s degree in Robotics Engineering from Zhejiang Normal University under Associate Professor Hu Lan, graduating with a GPA of 3.40/4.0 and receiving a Third Academic Scholarship. Wenwei’s academic background blends strong theoretical knowledge with hands-on experience in intelligent systems and control engineering. 🧠🎓📈

Professional Experience

Wenwei has led and contributed to various high-impact robotics projects. As Principal Investigator, he developed a novel inner-outer loop framework for modular robots using reinforcement learning and evolutionary optimization. As Co-Investigator, he worked on intelligent drone navigation and pursuit-evasion for port defense. He also led a RoboMaster project, designing embedded software for a wheeled robot with Mecanum wheels and a shooting mechanism. His work integrates control algorithms, real-time systems, and AI-based decision-making, validated through both simulations and real-world experiments. His diverse project roles highlight both leadership and deep technical acumen. 🤖🧪🧑‍🔬

Awards and Honors

Wenwei has received several prestigious awards and honors throughout his academic career. At Shanghai Maritime University, he won the Third Prize in the 2022 “Huawei Cup” China Post-Graduate Mathematical Contest in Modeling. During his undergraduate years, he received the National Third Prize in the 2021 National College Students Robotics Competition (RoboMaster Event). He has also been awarded the First Academic Scholarship twice during his master’s program and the Third Academic Scholarship during his bachelor’s. These recognitions reflect his commitment to excellence and contributions to engineering and robotics research. 🥇🎖️📜

Research Focus

Wenwei’s research centers on intelligent control and adaptive robotics, specifically focusing on reinforcement learning-based control, evolutionary robotics, and adaptive dynamic programming. He has pioneered a hierarchical framework integrating genetic algorithms and deep RL (PPO) for optimizing morphology and control of modular robots. His work extends to autonomous UAV path planning and pursuit-evasion strategies using fuzzy logic, neural networks, and Lyapunov-based verification. His research leverages advanced tools such as JAX and GPU parallelism for real-time learning and optimization. Wenwei aims to develop scalable, autonomous systems capable of intelligent behavior in complex environments. 🧠📡🚀

Publication Top Notes

📄  Inner–Outer Loop Intelligent Morphology Optimization and Pursuit–Evasion Control for Space Modular Robot

 📅Year: 2025 | 📚 Journal: Actuators, Volume 14

Conclusion

Wenwei Luo is a highly promising early-career researcher whose academic excellence, innovative research, and practical contributions make him a strong contender for a Best Researcher Award. With a Master’s GPA of 3.84/4.0 and a strong undergraduate foundation, he has demonstrated consistent academic achievement. His research focuses on cutting-edge areas such as modular robotics, reinforcement learning, and evolutionary optimization, exemplified by his novel inner–outer loop architecture combining genetic algorithms and PPO for pursuit–evasion tasks. He has authored peer-reviewed publications, including a journal article in Actuators, and holds a patent alongside software copyrights, reflecting both theoretical and applied innovation. His technical skill set spans AI frameworks, embedded systems, and robotics platforms, and his leadership roles in multiple projects showcase his capability for independent and collaborative research. Combined with national competition awards and scholarships, Luo’s profile embodies the qualities celebrated by the Best Researcher Award.