Zhijiao Chen | Cryptographic Hardware | Best Researcher Award

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Prof. Zhijiao Chen | Cryptographic Hardware | Best Researcher Award

Associate Professor at Beijing University of Post and Telecommunications, China

Prof. Zhijiao Chen is an Associate Professor at Beijing University of Posts and Telecommunications, specializing in millimeter-wave antenna design and wireless communication technologies. He holds a Ph.D. in Antennas from Queen Mary University of London and has a strong background in dielectric resonator antennas, 3D printed antennas, and shaped beam synthesis. Prof. Chen has collaborated with leading institutions worldwide, including the National Physical Laboratory and City University of Hong Kong. His research focuses on high-efficiency antenna arrays for 5G and beyond, as well as innovative materials for antenna design. He is an active member of IEEE and has received multiple awards for his contributions to research and teaching.

 

Profile

Scopus Profile

ORCID Profile

Education

Prof. Zhijiao Chen obtained his PhD from the Antennas Research Group at Queen Mary University of London (2010–2014), under the supervision of Prof. Clive G. Parini, a Fellow of the Royal Academy of Engineering. His doctoral research, awarded in November 2014, laid a strong foundation in advanced antenna design. Prior to his PhD, he completed a BSc in a joint program between Beijing University of Posts and Telecommunications and Queen Mary University of London, graduating with First Class Honors in 2010.

Experience

Currently, Prof. Chen serves as an Associate Professor at the Beijing University of Posts and Telecommunications (2020-present). He previously held a lecturer position there from 2014 to 2020. He has extensive international exposure, having been a Visiting Scholar at institutions like the National Physical Laboratory in the UK (2019), City University of Hong Kong (2018–2019), and Northeastern University in the USA (2013). His collaborations with leading researchers in the field, such as Professors Tian Hong Loh, Chi Hou Chan, and Nian-Xiang Sun, underscore his expertise and contribution to global antenna research.

Research Interests

Prof. Chen’s research interests span critical areas in antenna technology, including millimeter-wave and dielectric resonator antennas, base station antennas, 3D printed antennas, shaped beam synthesis, and bandpass filters. His innovative work in these areas has significant implications for advancing 5G, satellite communication, and vehicular connectivity.

Awards 

Prof. Chen has received multiple accolades throughout his career, reflecting his scholarly impact. Notable awards include the Young Scientists Award at the ACES-China 2021 symposium and the Best Oral Presentation Award at IEEE ICET 2021. His contributions to antenna technology have also earned him first place in the 2020 Ceyear Electronic Measurement Competition and Best Paper Award at IEEE iWAT2013, underscoring his role as a leader in antenna research.

Skills

Prof. Zhijiao Chen specializes in millimeter-wave antennas, dielectric resonator antennas, 3D printed antennas, and beam synthesis for advanced communication systems. His expertise includes high-efficiency antenna arrays, satellite communications, and IoT applications. He is skilled in materials science, particularly in the use of ceramics and dielectric structures for antenna design. Prof. Chen has extensive experience in collaborative research with leading institutions and plays an active role in the academic community as a reviewer, editor, and conference session chair. His work bridges theory and practice, contributing to advancements in wireless communication technologies like 5G and beyond.

Publication Top Noted

  • Great Adventures and Experiences: The IEEE Antennas and Propagation Society Young Professional Ambassador Program [Young Professionals]
    • Author(s): Chen, Z.
    • Journal: IEEE Antennas and Propagation Magazine
    • Year: 2024
    • Volume: 66
    • Issue: 2
    • Pages: 80–83
    • Type: Article, Open Access
    • Abstract & Related Documents: Not available
  • Compact Multibeam Antenna Using Miniaturized Slow-Wave Substrate-Integrated Waveguide Rotman Lens for Satellite-Assisted Internet of Vehicles
    • Author(s): Deng, J.-Y., Liu, Y.-B., Chen, Z., Lin, W.
    • Journal: IEEE Internet of Things Journal
    • Year: 2024
    • Volume: 11
    • Issue: 4
    • Pages: 6848–6856
    • Type: Article
    • Citations: 3
  • FDM 3D-Printed DRA Array for 5G Millimeter Wave and 6G Applications
    • Author(s): Li, S., Izquierdo, B.S., Gao, S., Chen, Z.
    • Conference: IEEE Antennas and Propagation Society, AP-S International Symposium (Digest)
    • Year: 2024
    • Pages: 417–418
    • Type: Conference Paper
    • Citations: 0
  • A Dental Dielectric Resonator Antenna
    • Author(s): Chen, Z., Zhang, J., Jing, Y., Jiang, X., Sanz-Izquierdo, B.
    • Conference: IEEE Antennas and Propagation Society, AP-S International Symposium (Digest)
    • Year: 2024
    • Pages: 1391–1392
    • Type: Conference Paper
    • Citations: 0
  • IWS 2024 Women in Microwaves: Challenge Yourself and Be Proud [Women in Microwaves]
    • Author(s): Li, Z., Chen, Z., Han, Y., Yang, W., Che, W.
    • Journal: IEEE Microwave Magazine
    • Year: 2024
    • Volume: 25
    • Issue: 10
    • Pages: 87–90
    • Type: Conference Paper
    • Citations: 0
  • A W-Band High-Gain Low-Sidelobe Circular-Shaped Monopulse Antenna Array Based on Dielectric Loaded Waveguide
    • Author(s): Zhang, X., Chen, Z., Ye, X.
    • Journal: IEEE Access
    • Year: 2024
    • Volume: 12
    • Pages: 64997–65006
    • Type: Article, Open Access
    • Citations: 2
  • A Wearable Open-Ring Dielectric Resonator Antenna with Frequency Reconfiguration
    • Author(s): Jiang, X., Chen, Z., Sanz-Izquierdo, B.
    • Conference: 18th European Conference on Antennas and Propagation, EuCAP 2024
    • Year: 2024
    • Type: Conference Paper
    • Citations: 0
  • Dielectric Resonator Antennas: Materials, Designs and Applications
    • Author(s): Chen, Z., Deng, J., Liu, H.
    • Book Title: Dielectric Resonator Antennas: Materials, Designs and Applications
    • Year: 2024
    • Pages: 1–301
    • Type: Book
    • Citations: 1
  • Wideband Millimeter-Wave MIMO Antenna with a Loaded Dielectric Cover for High-Gain Broadside Radiation
    • Author(s): Chen, Z., Song, W., Wang, W.
    • Journal: Electronics (Switzerland)
    • Year: 2023
    • Volume: 12
    • Issue: 21
    • Article ID: 4384
    • Type: Article, Open Access
    • Citations: 2
  • Novel B-site Scheelite Structure Ceramic Bi(Ge0.5Mo0.5)O4 and its Dielectric Properties
    • Author(s): Xu, D., Zhang, H., Pang, L., Chen, Z., Zhou, D.
    • Journal: Journal of the American Ceramic Society
    • Year: 2023
    • Volume: 106
    • Issue: 11
    • Pages: 6675–6683
    • Type: Article
    • Citations: 7

Conclusion

Prof. Zhijiao Chen’s extensive academic and research experience, along with his significant contributions to the field of antenna technology and communication systems, make him an outstanding candidate for the Research for Best Researcher Award. His expertise, leadership in research projects, collaboration with international institutions, and recognition within the scientific community underscore his qualifications for this honor.

Omer Tariq | Cryptographic Accelerators | Best Researcher Award

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Mr. Omer Tariq | Cryptographic Accelerators | Best Researcher Award

Ph.D. Candidate at Korea Advanced Institute of Science and Technology, South Korea

Mr. Omer Tariq is a Ph.D. candidate at the Korea Advanced Institute of Science and Technology (KAIST), specializing in efficient and privacy-preserving deep learning for AIoT and Autonomous Systems. With over seven years of experience in Digital ASIC Design, Embedded Systems, and Hardware Design, Mr. Tariq has demonstrated a strong capability in developing and deploying innovative machine learning solutions using tools like TensorFlow, TensorRT, and PyTorch. His professional journey includes significant roles at the National Electronics Complex and the National Space Agency of Pakistan, where he led projects in SoC/RTL design, satellite imaging payload systems, and autonomous robotics. He is an accomplished researcher with several publications in prestigious journals, and his work is recognized for its impact on AI and robotics. Mr. Tariq holds a Bachelor of Science in Electrical Engineering from the University of Engineering and Technology, Taxila, and is actively seeking roles that will allow him to further contribute to the fields of AI and machine learning.

Profile:

Education:

Mr. Omer Tariq is currently pursuing a Doctor of Philosophy (Ph.D.) in Computer Science at the Korea Advanced Institute of Science and Technology (KAIST), School of Computing, specializing in Machine Learning and AI, with a CGPA of 3.74/4.3. His doctoral coursework includes advanced topics such as Programming for AI, Intelligent Robotics, Human-Computer Interaction, and Advanced Machine Learning. He previously earned a Bachelor of Science (BSc.) in Electrical Engineering from the University of Engineering and Technology (UET), Taxila, with a CGPA of 3.25/4.0. His undergraduate thesis focused on developing a “Computer Vision-Assisted Object Detection and Control Framework for a 3-DoF Robotic Arm,” showcasing his early interest in robotics and advanced computer architecture.

Professional Experience:

Mr. Omer Tariq has accumulated extensive experience across various high-tech sectors. From April 2019 to September 2022, he served as an Engineering Manager and Team Lead at the National Electronics Complex, Pakistan, where he led the verification and validation of high-performance SoC/RTL designs. He oversaw RTL development and optimization for integrated circuits, utilizing tools such as SystemVerilog and UVM. Prior to this, from October 2014 to April 2019, Mr. Tariq worked as an Assistant Manager at the National Space Agency (SUPARCO), Pakistan. In this role, he was instrumental in designing and developing satellite imaging payload systems and high-speed PCB designs, contributing to successful national satellite missions. Currently, Mr. Tariq is a Research Assistant in the Department of Industrial & Systems Engineering at KAIST, where he has been involved in designing and developing the electronics and power management module for the DAIM-Autonomous Mobile Robot. His work includes engineering advanced robotics software systems and implementing cutting-edge SLAM algorithms to enhance real-time navigation accuracy.

Research Interests:

Mr. Omer Tariq’s research interests are centered on advancing deep learning techniques for AIoT (Artificial Intelligence of Things) and autonomous systems, with a particular focus on efficiency and privacy preservation. His work explores the application of state-of-the-art machine learning frameworks such as TensorFlow, TensorRT, and PyTorch to develop innovative solutions that address complex challenges in these fields. Mr. Tariq is particularly engaged in improving robot motion planning, mapping, and localization (SLAM) algorithms to enhance autonomous systems’ navigation accuracy. His research also extends to federated learning approaches for secure AIoT-enabled applications, context-aware indoor-outdoor detection frameworks using smartphone sensors, and privacy-preserving methods in smart card authentication for Non-Fungible Tokens. His extensive work in these areas contributes to both theoretical advancements and practical implementations in machine learning and AI.

Skills:

Mr. Omer Tariq possesses a robust skill set in both software and hardware domains, crucial for his work in advanced machine learning and AI systems. He is proficient in programming languages such as C/C++, Python, SQL, SystemVerilog, and Verilog, enabling him to develop and optimize complex algorithms and systems. His expertise extends to a range of technologies and tools including TensorFlow, PyTorch, CUDA, and various AWS services like EC2, PostgreSQL, SQS, and Lambda. Additionally, he is adept in containerization and orchestration technologies such as Docker and Kubernetes. Mr. Tariq’s skills also encompass digital ASIC design and hardware tools, with experience using Cadence IC Design, Synopsys, Vivado/Vitis, and Altium Designer. This diverse technical knowledge underpins his ability to tackle intricate challenges in machine learning, embedded systems, and digital design.

Conclution:

Mr. Omer Tariq’s combination of academic excellence, professional experience, technical skills, and impactful research makes him a strong candidate for the Best Researcher Award. His contributions to AIoT, Autonomous Systems, and privacy-preserving technologies are not only innovative but also address critical challenges in today’s technological landscape. His achievements reflect a commitment to advancing knowledge and technology, making him deserving of recognition as a leading researcher in his field.

Publication Tob Noted:

  • A Smart Card Based Approach for Privacy Preservation Authentication of Non-Fungible Token Using Non-Interactive Zero Knowledge Proof
    • Authors: MBA Dastagir, O. Tariq, D. Han
    • Published in: 2022 IEEE Smartworld, Ubiquitous Intelligence & Computing, Scalable
    • Citations: 1
    • Year: 2022
  • Compact Walsh–Hadamard Transform-Driven S-Box Design for ASIC Implementations
    • Authors: O. Tariq, MBA Dastagir, D. Han
    • Published in: Electronics 13 (16), 3148
    • Citations: Not yet cited
    • Year: 2024
  • TabCLR: Contrastive Learning Representation of Tabular Data Classification for Indoor-Outdoor Detection
    • Authors: MBA Dastagir, O. Tariq, D. Han
    • Published in: IEEE Access
    • Citations: Not yet cited
    • Year: 2024
  • 2D Particle Filter Accelerator for Mobile Robot Indoor Localization and Pose Estimation
    • Authors: O. Tariq, D. Han
    • Published in: IEEE Access
    • Citations: Not yet cited
    • Year: 2024
  • DeepIOD: Towards A Context-Aware Indoor–Outdoor Detection Framework Using Smartphone Sensors
    • Authors: MBA Dastagir, O. Tariq, D. Han
    • Published in: Sensors 24 (16), 5125
    • Citations: Not yet cited
    • Year: 2024
  • HILO: High-level and Low-level Co-design, Evaluation and Acceleration of Feature Extraction for Visual-SLAM using PYNQ Z1 Board
    • Authors: MB Akram Dastagir, O. Tariq, D. Han
    • Published in: 12th International Conference on Indoor Positioning and Indoor Navigation
    • Citations: Not yet cited
    • Year: 2022