Xinxiang Zhang, Ph.D.

Xinxiang Zhang, Ph.D. is a Patent Agent in Sterne Kessler’s Electronics Practice Group where he assists in the preparation and prosecution of patent applications before the United States Patent & Trademark Office. His technical expertise and research experience includes artificial intelligence (AI), computer vision, machine learning, deep learning, sensor fusion, Internet of Things, digital signal processing, wireless communications, and optics.

Dr. Zhang has assisted clients to prepare and draft patent applications that leverage large language models (LLMs) to discover scientific knowledge and perform in silico immunogenicity assessment. Dr. Zhang has also prosecuted patent applications in AI-related technologies, including healthcare data quality enhancement, augmented reality (AR) and virtual reality (VR) for video conferencing, quantitative analysis of the art market, and the financial industry.

Dr. Zhang’s doctoral research relates to integrating computer vision, machine learning, and sensor fusion to develop intelligent monitoring solutions for civil infrastructures and traffic surveillance systems. During his Ph.D. studies, he also worked on several cutting-edge research projects that leverage AI and computer vision techniques to address challenges in the fields comprising generative AI, natural language processing, image and video processing, machine sensing and perception, 3D sensing technologies, autonomous vehicles, and drone communications.

Prior to joining Sterne Kessler, Dr. Zhang worked as a Postdoctoral Fellow at Southern Methodist University applying AI, computer vision, machine learning, and sensor fusion techniques to develop next-generation multi-modal seismo-acoustic monitoring systems for interpreting ground motion signals.

Dr. Zhang’s research is well-regarded in the field and he has garnered national and international acclaim for his work. He has authored or co-authored 16 technical publications with hundreds of citations around the world, including one Global ESI top 1% highly cited paper. He has reviewed more than 100 papers in several prestigious journals and has been serving as editor and editorial board member for at least three reputable journals in the field.

Technical Publications

• Xinxiang Zhang, Dinesh Rajan, Brett Story*, “Concrete Crack Detection Using Context-Aware Deep Semantic Segmentation Network,” Computer-Aided Civil and Infrastructure Engineering, 34(11), 951-971, 2019 (Global ESI top 1% Highly Cited Paper).
• Xinxiang Zhang*, Brett Story, Dinesh Rajan, “Night Time Vehicle Detection and Tracking by Fusing Vehicle Parts from Multiple Cameras,” IEEE Transactions on Intelligent Transportation Systems, 23(7), 8136-8156, 2021.
• Xinxiang Zhang, Yasha Zeinali, Brett Story*, Dinesh Rajan, “Measurement of Three-Dimensional Structural Displacement Using a Hybrid Inertial Vision-Based System,” Sensors, 19(19), 4083, 2019.
• Xinxiang Zhang, Stephen Arrowsmith*, Sotirios Tsongas, Chris Hayward, Haoran Meng, Yehuda Ben-Zion, “A Data-Driven Framework for Automated Detection of Aircraft-Generated Signals in Seismic Array Data Using Machine Learning,” Seismological Research Letters, 93(1), 226-240, 2022.
• Xinxiang Zhang, Chris Hayward, Sarah McComas, Stephen Arrowsmith*, “Exploring Acoustic Characteristics of Different Aircraft Types by Fusing with Aircraft Tracking Data,” The Journal of the Acoustical Society of America, 153(5), 3138-3138, 2023.
• Hao Wu, Xinxiang Zhang, Brett Story, Dinesh Rajan, “Accurate Vehicle Detection Using Multi-Camera Data Fusion and Machine Learning,” In 2019 IEEE 44th International Conference on Acoustics, Speech, and Signal Processing, pp. 3767-3771, May, 2019.
• Ye Wang*, Xinxiang Zhang, Mi Lu, Han Wang, Yoonsuck Choe, “Attention Augmentation with Multi-Residual in Bidirectional LSTM,” Neurocomputing, 385, 340-347, 2020.
• Bryan Rodriguez*, Xinxiang Zhang, Dinesh Rajan, “Probabilistic Modeling of Multicamera Interference for Time-of-Flight Sensors,” Sensors, 23(19), 8047, 2023.
• Bryan Rodriguez, Xinxiang Zhang*, Dinesh Rajan, “Probabilistic Modeling of Motion Blur for Time-of-Flight Sensors,” Sensors, 22(3), 1182, 2022.
• Yue Zhang, Xinxiang Zhang, “Effective Real-Scenario Video Copy Detection,” In 2016 23rd International Conference on Pattern Recognition, pp. 3951-3956, December, 2016.

*Corresponding author

Technical Reviews

Selected Journals

IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Instrumentation and Measurement, IEEE Transactions on Consumer Electronics, Neural Computing and Applications, Construction and Building Materials, Engineering Applications of Artificial Intelligence, Remote Sensing, Sensors, Biosensors, Applied Sciences, Electronics, Robotics, Micromachines, Photonics

Selected Conference Proceedings

IEEE Vehicular Technology Conference, Asia-Pacific Signal and Information Processing Association