Siyi Wang | Smart Manufacturing | Best Researcher Award

Ms. Siyi Wang | Smart Manufacturing
| Best Researcher Award

Graduate student at Xi’an Technological University, China.

Siyi Wang is a graduate student at Xi’an Technological University, majoring in Industrial Engineering and Management Science. Under the mentorship of Professor Gao Xiaobing, she has focused her research on optimizing body-in-white (BIW) measurement station planning for automotive manufacturing. Her work addresses complex real-world constraints—such as environmental limitations, feature characteristics, equipment capability, and on-site operability—leading to significantly improved measurement efficiency in a major automobile factory. With a recent publication in Applied Sciences, she demonstrates strong research potential and the ability to apply academic insights to industrial practice. Her innovative approach reflects a rare blend of theoretical rigor and practical relevance, making her a promising candidate for recognition through the Best Researcher Award.

🌍 Professional Profile:

Google Scholar

🏆 Suitability for the Best Researcher Award :

Siyi Wang is highly suitable for the Best Researcher Award due to her outstanding application of engineering principles to solve real-world industrial challenges. Her research on body-in-white measurement station planning is not only academically rigorous but also has direct implications for enhancing manufacturing efficiency in the automotive sector. Despite being at the graduate level, she has authored a peer-reviewed paper in a reputable SCI-indexed journal, demonstrating her capability to contribute valuable knowledge to the field. Her ability to work under constraints and deliver measurable improvements in industrial settings reflects her innovation, problem-solving acumen, and technical insight—qualities befitting a future research leader. She exemplifies emerging excellence in engineering science and deserves recognition for her impactful contributions.

🎓 Education :

Siyi Wang is currently pursuing her graduate studies in Industrial Engineering and Management Science at Xi’an Technological University, China. She is under the academic supervision of Professor Gao Xiaobing, a recognized expert in measurement system optimization and intelligent manufacturing. Her education has been deeply focused on the practical aspects of industrial systems, measurement technologies, and operations research. Her curriculum includes advanced coursework in production system optimization, statistical modeling, and quality control systems. Through her graduate program, Siyi has developed a strong foundation in both theoretical and applied aspects of industrial engineering, with a particular interest in automotive manufacturing and laser radar systems. Her academic training equips her well to continue impactful research in smart manufacturing and systems optimization.

🏢 Work Experience :

Siyi Wang has accumulated significant research experience through her graduate work at Xi’an Technological University. Her primary project involves the planning of body-in-white (BIW) measurement stations, where she integrates theoretical modeling with industrial constraints to enhance manufacturing accuracy and efficiency. She has worked closely with real automotive production data, analyzing environmental limitations, measurement feature characteristics, equipment restrictions, and actual operating conditions. Her findings have led to a practical breakthrough—notably improving measurement efficiency in a collaborating automobile factory. Though early in her career, her experience reflects high-impact, real-world application of academic research. She is also the co-author of a published article in Applied Sciences, highlighting her ability to produce peer-reviewed work with industrial significance.

🏅 Awards and Honors :

As an emerging researcher, Siyi Wang has begun gaining recognition for her contributions to applied engineering science. Her notable achievement includes co-authoring an SCI-indexed paper in Applied Sciences titled “Research on Laser Radar Inspection Station Planning of Vehicle Body-In-White (BIW) with Complex Constraints” (2025). While she has not yet received formal awards, her selection for publication in a respected international journal as a graduate student demonstrates early-career research excellence. Her work has been acknowledged internally within her department for its relevance and innovation in solving industry-specific problems. Given her demonstrated potential and the measurable impact of her research, she is a strong candidate for future academic and professional honors, including the Best Researcher Award.

🔬 Research Focus :

Siyi Wang’s research centers on measurement station planning for body-in-white (BIW) systems in automotive manufacturing. She focuses on improving the efficiency and accuracy of vehicle inspection processes by considering a wide range of constraints, such as environmental conditions, geometry of features, sensor capabilities, and operational dynamics. Her work applies advanced methods in industrial engineering and systems optimization to model and solve these complex, multi-variable challenges. She is particularly interested in integrating laser radar technologies with planning algorithms to enhance the flexibility and precision of inspection stations. Her research is both practical and forward-looking, contributing to smart manufacturing, digital twin environments, and intelligent quality control systems. It has already shown real industrial value in a major automotive factory.

📊 Publication Top Notes:

📘 Solvent‐Annealed Crystalline Squaraine: PC70BM (1:6) Solar Cells
📅 Year: 2011 | 🔁 Cited by: 293 | 🧪 Topic: Organic Solar Cells

📘 Solution-Processed Squaraine Bulk Heterojunction Photovoltaic Cells
📅 Year: 2010 | 🔁 Cited by: 215 | ☀️ Topic: Photovoltaics, Squaraine

📘 Efficient, Ordered Bulk Heterojunction Nanocrystalline Solar Cells by Annealing of Ultrathin Squaraine Thin Films
📅 Year: 2010 | 🔁 Cited by: 189 | 🔬 Topic: Nanocrystalline Solar Cells

📘 High Efficiency Organic Photovoltaic Cells Based on a Vapor Deposited Squaraine Donor
📅 Year: 2009 | 🔁 Cited by: 153 | ⚡ Topic: Organic Photovoltaics

📘 Independent Control of Bulk and Interfacial Morphologies of Small Molecular Weight Organic Heterojunction Solar Cells
📅 Year: 2012 | 🔁 Cited by: 146 | 🧫 Topic: Morphology Control, OPV

📘 N,N-Diarylanilinosquaraines and Their Application to Organic Photovoltaics
📅 Year: 2011 | 🔁 Cited by: 144 | 🧪 Topic: Squaraine Chemistry

📘 Functionalized Squaraine Donors for Nanocrystalline Organic Photovoltaics
📅 Year: 2012 | 🔁 Cited by: 133 | ⚙️ Topic: Donor Design, Solar Cells

Hazrat Bilal | Robotics Engineering | Young Scientist Award

Dr. Hazrat Bilal |Robotics Engineering
| Young Scientist Award

Postdoctoral Research Fellow at Shenzhen University, China .

Dr. Hazrat Bilal is a highly accomplished researcher and Postdoctoral Fellow at Shenzhen University, China. With a Ph.D. in Control Science & Engineering from the University of Science & Technology of China, he brings exceptional expertise in intelligent robotics, deep learning, and fault diagnosis. Dr. Bilal has authored over 30 high-impact publications and has earned 1200+ citations (h-index: 12). His outstanding academic record is complemented by rich industry experience and several prestigious fellowships and awards. A dedicated IEEE member and registered engineer with PEC, he is passionate about pushing the boundaries of intelligent automation. His remarkable early-career accomplishments and leadership in research make him a strong candidate for the Young Scientist Award.

🌍 Professional Profile:

Scopus 

Orcid

Google scholar

🏆 Suitability for the Best Researcher Award


Dr. Hazrat Bilal is a highly deserving candidate for the Young Scientist Award, with an exceptional academic record (Ph.D., USTC, GPA 3.88/4.00; M.S., NUST, GPA 3.85/4.00). As a Postdoctoral Fellow at Shenzhen University, he has made significant contributions to intelligent robotics, fault diagnosis, and AI-driven control systems. With over 15 high-impact Q1/Q2 journal publications—including in the IEEE IoT Journal, Soft Computing, Bioengineering, and Human-centric Computing—his research demonstrates innovation and practical value. His interdisciplinary work in blockchain-enabled IoRT, fuzzy-ADRC control, and AI for medical and UAV systems reflects his leadership in emerging technologies. With over 1200 citations and global collaborations, Dr. Bilal stands out as a promising young researcher committed to advancing intelligent and sustainable technologies.

🎓 Education 

Dr. Hazrat Bilal’s academic journey reflects a commitment to excellence in engineering and research. He earned his Ph.D. in Control Science & Engineering from the University of Science & Technology of China (2018–2024), maintaining an exceptional GPA of 3.88/4.00. Prior to that, he completed his Master’s degree in the same field at Nanjing University of Science & Technology (2015–2018) with a GPA of 3.85/4.00 and received an Outstanding Graduate Certificate. His undergraduate studies in Electrical (Electronics) Engineering were completed at FUUAST Islamabad, Pakistan (2010–2014), earning a GPA of 3.18/4.00. This strong academic foundation underpins his work in robotics, automation, and advanced control systems.

🏢 Work Experience 

Dr. Bilal brings interdisciplinary and global experience from academia and industry. He worked as a Performance Software Engineer at ZF Friedrichshafen, Shanghai, where he developed vision algorithms and optimized embedded system performance. Prior to that, he served as a Telecom Engineer at Real Solution Pvt. Ltd., Pakistan, contributing to 3G system installations and RF optimization. He also worked at Dargai Hydropower Plant as a Control Engineer, where he led power generation and preventive maintenance operations. Additionally, he completed internships and technical training at the National Telecommunication Corporation, University of Tennessee (USA), and CAE Pakistan. These roles have refined his expertise in automation, control systems, robotics, and smart grid technologies.

🏅 Awards and Honors 

Dr. Hazrat Bilal has received numerous awards recognizing his academic excellence and innovation. He is a recipient of the CAS-TWAS Fellowship Award at USTC and the NMG-NUST Joint Scholarship for his master’s studies. His exceptional performance earned him the Outstanding Graduate Certificate from Nanjing University of Science & Technology. As an undergraduate, he was awarded scholarships from Akhuwat Foundation and Pakistan Bait-ul-Mal, along with a Prime Minister’s Laptop under the national scheme. He secured funding for his final-year project through the National Grassroots ICT R&D Program. Dr. Bilal also received a Letter of Appreciation from IEEE FUUAST and continues to excel as an IEEE member and professional contributor to engineering societies.

🔬 Research Focus 

Dr. Hazrat Bilal’s research lies at the intersection of robotic control systems, artificial intelligence, and fault diagnosis. His recent works emphasize hybrid deep learning algorithms for the Internet of Robotic Things (IoRT), adaptive control of flexible manipulators, and trajectory tracking. He has proposed advanced techniques integrating fuzzy logic, ADRC, CNNs, LSTMs, and blockchain for secure, intelligent, and resilient systems. His current research includes generative AI for traffic simulation, nanorobot control, and intelligent medical diagnosis using AI. Dr. Bilal’s work contributes significantly to the future of smart manufacturing, healthcare, and autonomous vehicles. His focus on interdisciplinary, experimental, and data-driven approaches positions him as a leader in intelligent control systems.

📊 Publication Top Notes:

  • Title: A data-driven approach for intrusion and anomaly detection using automated machine learning for the Internet of Things
    Authors: H. Xu, Z. Sun, Y. Cao, H. Bilal
    Journal: Soft Computing, 27(19), 14469–14481
    Citations: 172
    Year: 2023

  • Title: Pruning filters with L1-norm and capped L1-norm for CNN compression
    Authors: A. Kumar, A. M. Shaikh, Y. Li, H. Bilal, B. Yin
    Journal: Applied Intelligence, 51(2), 1152–1160
    Citations: 147
    Year: 2021

  • Title: A practical study of active disturbance rejection control for rotary flexible joint robot manipulator
    Authors: H. Bilal, B. Yin, M. S. Aslam, Z. Anjum, A. Rohra, Y. Wang
    Journal: Soft Computing, 27(8), 4987–5001
    Citations: 128
    Year: 2023

  • Title: Jerk-bounded trajectory planning for rotary flexible joint manipulator: an experimental approach
    Authors: H. Bilal, B. Yin, A. Kumar, M. Ali, J. Zhang, J. Yao
    Journal: Soft Computing, 27(7), 4029–4039
    Citations: 118
    Year: 2023

  • Title: Experimental validation of fuzzy PID control of flexible joint system in presence of uncertainties
    Authors: H. Bilal, W. Yao, Y. Guo, Y. Wu, J. Guo
    Conference: 2017 36th Chinese Control Conference (CCC), 4192–4197
    Citations: 115
    Year: 2017

  • Title: Real-time lane detection and tracking for advanced driver assistance systems
    Authors: H. Bilal, B. Yin, J. Khan, L. Wang, J. Zhang, A. Kumar
    Conference: 2019 Chinese Control Conference (CCC), 6772–6777
    Citations: 101
    Year: 2019

  • Title: Regional feature fusion for on-road detection of objects using camera and 3D-LiDAR in high-speed autonomous vehicles
    Authors: Q. Wu, X. Li, K. Wang, H. Bilal
    Journal: Soft Computing, 27(23), 18195–18213
    Citations: 90
    Year: 2023

  • Title: Reduction of multiplications in convolutional neural networks
    Authors: M. Ali, B. Yin, A. Kunar, A. M. Sheikh, H. Bilal
    Conference: 2020 39th Chinese Control Conference (CCC), 7406–7411
    Citations: 85
    Year: 2020

  • Title: Second-order convolutional network for crowd counting
    Authors: L. Wang, Q. Zhai, B. Yin, H. Bilal
    Conference: Fourth International Workshop on Pattern Recognition, 11198, 158–163
    Citations: 83
    Year: 2019

  • Title: A hybrid CEEMD-GMM scheme for enhancing the detection of traffic flow on highways
    Authors: H. Dou, Y. Liu, S. Chen, H. Zhao, H. Bilal
    Journal: Soft Computing, 27(21), 16373–16388
    Citations: 82
    Year: 2023

  • Title: Advanced efficient strategy for detection of dark objects based on spiking network with multi-box detection
    Authors: M. Ali, B. Yin, H. Bilal, A. Kumar, A. M. Shaikh, A. Rohra
    Journal: Multimedia Tools and Applications, 83(12), 36307–36327
    Citations: 50
    Year: 2024