Mr. Hussm Rostum | Computer Science | Best Researcher Award

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Mr. Hussm Rostum | Computer Science | Best Researcher Award

Miskolc University, Institute of Automation and Info-communication, Hungary.

Hussam Rostum is a PhD candidate and researcher at the University of Miskolc in Hungary, specializing in computer vision for autonomous drone navigation. With a strong background in telecommunications and electronics, he blends academic excellence with hands-on experience as a part-time software engineer at FIEK. Hussam is known for developing cutting-edge solutions in industrial automation, biomedical imaging, and human–machine interfaces. Fluent in Arabic and English, he brings international insight into interdisciplinary research projects, merging software innovation with engineering systems.

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🎓 Education

Hussam holds a BSc and MSc in Telecommunication and Electronic Engineering, equipping him with deep theoretical and practical knowledge in signal processing, system design, and electronics. Currently, he is pursuing a PhD in Information Science at the University of Miskolc, focusing on AI-based vision systems for autonomous drone operations.

💼 Experience

Hussam serves as an Assistant Researcher and Part-time Software Engineer at FIEK, where he builds C# monitoring software, implements PLC-to-PC communications, and automates data workflows using Linux, Docker, and Excel. His professional journey includes work as a Full Stack Developer and Telecom Engineer, with experience in GUI development, DevOps collaboration, and .NET technologies.

🔬 Research Interests

📸 Computer Vision & Image Processing

🤖 Autonomous Systems & Drone Navigation

🩺 Biomedical Imaging & Oxygen Saturation Estimation

🔬 Optical System Design (Zemax)

⚙️ Industrial Automation & Data Visualization

🧠 Human–Machine Interfaces & Sensor Integration

📚 Selected Publications

Enhancing Machine Learning Techniques in VSLAM for Robust Autonomous Unmanned Aerial Vehicle Navigation
📅 2025-04-02 | 📰 Electronics
📌 Focus: Improving Visual SLAM with machine learning for UAVs in complex environments.
🔗 DOI: 10.3390/electronics14071440
👥 Co-author: József Vásárhelyi

Comparing the Effectiveness and Performance of Image Processing Algorithms in Face Recognition
📅 2024-05-22 | 📚 Conference Paper
📌 Focus: Evaluation of various image processing techniques for face recognition applications.
🔗 DOI: 10.1109/ICCC62069.2024.10569864
👥 Co-author: József Vásárhelyi

FPGA Implementation in Mobile Robot Applications: State of the Art Review
📅 2023-12-20 | 📰 Multidiszciplináris Tudományok
📌 Focus: Overview of FPGA-based systems in robotics.
🔗 DOI: 10.35925/j.multi.2023.2.21
👥 Co-authors: Omar M. Salih, Noha Hammami

An Overview of Energies Problems in Robotic Systems
📅 2023-12-14 | 📰 Energies
📌 Focus: Challenges in energy management for robotic systems.
🔗 DOI: 10.3390/en16248060
👥 Co-authors: József Vásárhelyi, Omar M. Salih, Rabab Benotsname

A Review of Using Visual Odometry Methods in Autonomous UAV Navigation in GPS-Denied Environments
📅 2023-12-01 | 📰 Acta Universitatis Sapientiae, Electrical and Mechanical Engineering
📌 Focus: Use of visual odometry for UAVs in GPS-denied settings.
🔗 DOI: 10.2478/auseme-2023-0002
👥 Co-author: József Vásárhelyi

 

 

 

 

Mr. Pawan Gaire | Applied Electromagnetics | Best Researcher Award

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Mr. Pawan Gaire | Applied Electromagnetics | Best Researcher Award

University of Nebraska Lincoln, United States.

Pawan K. Gaire is a Ph.D. candidate in Electrical Engineering at the University of Nebraska-Lincoln, specializing in electromagnetic (EM) simulation, numerical modeling, and RF/antenna design. With expertise in tools like HFSS, ADS, and COMSOL, he has a strong background in designing innovative wireless communication and power transfer systems. His research focuses on advanced computational techniques, including Physics Embedded Neural Networks (PENN) for solving complex electromagnetic problems.

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🎓 Education

Mr. Pawan Gaire is a dedicated scholar in the field of Electrical Engineering, currently pursuing his Ph.D. at the University of Nebraska-Lincoln (2022-2025) with a perfect GPA of 4.0. Prior to this, he earned his M.S. in Electrical Engineering from Florida International University (2019-2022), achieving an impressive GPA of 3.96. His academic journey began at Howard University, where he completed his B.S. in Electrical Engineering (2015-2019) with Summa Cum Laude honors and a GPA of 3.89. With a strong academic background and a commitment to excellence, Mr. Gaire continues to contribute to advancements in electrical engineering.

💼 Experience

Mr. Pawan Gaire has extensive research experience in electrical engineering, specializing in electromagnetics, antenna design, and wireless power transfer. Currently serving as a Research Assistant at the University of Nebraska-Lincoln (2022-Present), he has developed PENN, a novel neural network-based approach for solving Maxwell’s equations. His work also includes designing and fabricating sub-100 MHz multi-band antenna arrays using multiferroic heterostructures and simulating vector vortex wave generation for high-capacity tunnel communication.

Previously, as a Research Assistant at Florida International University (2019-2022), Mr. Gaire contributed to the development of an ad-hoc wireless power transfer system for smartphone charging and pioneered clothing-integrated rectifiers for efficient RF-to-DC conversion. Additionally, he conducted market validation for wearable charging devices under the NSF I-Corps program, showcasing his ability to bridge engineering innovation with commercial applications.

🛠️ Internships

SLAC National Accelerator Laboratory (2018) – Designed testbench for Hard X-ray systems.

DiCarlo Lab, MIT (2017) – Benchmarked AI models against primate vision.

Center for Integrated Quantum Materials (2016) – Fabricated and characterized diamond field-effect transistors.

🏆 Research Interests

Electromagnetic (EM) Simulation & RF Design: Expertise in Ansys HFSS, COMSOL, and ADS for antenna and circuit design.

Physics Embedded Neural Networks (PENN): Development of AI-driven solutions for scientific computing.

Wireless Power Transfer (WPT): Innovative antenna designs for efficient energy transfer.

Numerical Modeling & Computational Electromagnetics: Application of Finite Element Method (FEM) in RF systems.

🏅 Awards & Recognitions

NSF I-Corps Grant Recipient – Validated market demand for wireless charging solutions.

IEEE Conference Presenter – Multiple research presentations at premier EM and RF conferences.

Summa Cum Laude – Graduated with highest honors from Howard University.

📚 Publications

Physics Embedded Neural Network: Novel Data-Free Approach Towards Scientific Computing and Applications in Transfer Learning
Neurocomputing, 2025-02 | Journal Article
DOI: 10.1016/j.neucom.2024.128936
Contributors: Pawan Gaire, Shubhendu Bhardwaj

Data-Free Solution of Electromagnetic PDEs Using Neural Networks and Extension to Transfer Learning
IEEE Transactions on Antennas and Propagation, 2022-07 | Journal Article
DOI: 10.1109/TAP.2022.3186710
Contributors: Shubhendu Bhardwaj, Pawan Gaire

An Ergonomic Wireless Charging System for Integration With Daily Life Activities
IEEE Transactions on Microwave Theory and Techniques, 2021-01 | Journal Article
DOI: 10.1109/TMTT.2020.3029530
Contributors: Dieff Vital, Pawan Gaire, Shubhendu Bhardwaj, John L. Volakis

 

 

Prof. Dr. Chih-Hsien Hsia | Image Processing | Best Researcher Award

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Prof. Dr. Chih-Hsien Hsia | Image Processing | Best Researcher Award

National Ilan University, Taiwan.

Chih-Hsien Hsia is a distinguished professor and researcher in computer science, specializing in DSP IC Design, Computer Vision, Image Processing, and Cognitive Engineering. He holds dual Ph.D. degrees in Engineering Science from National Cheng Kung University and Electrical & Computer Engineering from Tamkang University, Taiwan. Currently, he serves as a Distinguished Professor at National Ilan University and holds key positions in AI research, industry collaborations, and professional organizations. His contributions to AI, image processing, and intelligent systems have earned him prestigious awards and widespread recognition.

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🎓 Education

Prof. Dr. Chih-Hsien Hsia holds dual Ph.D. degrees in Engineering Science from National Cheng Kung University, Taiwan, and Electrical & Computer Engineering from Tamkang University, Taiwan. His expertise spans multiple engineering disciplines, with a strong focus on cutting-edge technological advancements and interdisciplinary research.

💼 Experience

Prof. Dr. Chih-Hsien Hsia is a Distinguished Professor at National Ilan University (2024 – Present) and serves as the Executive Director of the AI Promotion Office at the same institution. He is also the Director of the AIoX Research Center at National Ilan University (2024 – Present).

Beyond his role at NIU, he has been an Honorary Distinguished Professor at Chaoyang University of Technology since 2022 and a Board Member of the Chinese Society of Consumer Electronics since 2018. Additionally, he holds the position of Vice Chair of the IEEE Taipei Chapter Signal Processing Society (2024 – Present).

Previously, he served as a Professor at National Ilan University (2020 – 2024) and was the Chairperson of the Department of Computer Science at NIU from 2021 to 2024. His leadership and research contributions have significantly advanced AI, signal processing, and computer science education.

🔬 Research Interests

🖥 DSP IC Design

📷 Computer Vision & Image Processing

🧠 Cognitive Engineering

🏆 Awards & Honors

🥇 Taiwan International Science Fair (2025) – First Prize in Computer Science & Engineering

🏅 Best Paper Awards at IEEE Eurasia Conference on IoT, IET International Conference, National Defense Technology Academic Conference (2024)

🌟 World's Top 2% Scientists (2022)

🎖 Outstanding Young Scholar Award – Computer Society of the Republic of China (2018, 2020)

📚 Notable Publications

Finger Vein Recognition Based on Vision Transformer with Feature Decoupling for Online Payment Applications
IEEE Access, 2025 | DOI: 10.1109/ACCESS.2025.3552075
Contributors: Liang-Ying Ke, Yi-Chen Lin, Chih-Hsien Hsia

Artificial Intelligence and Machine Learning in Sensing and Image Processing
Sensors, 2025-03-18 | DOI: 10.3390/s25061870
Contributors: Jing Chen, Miaohui Wang, Chih-Hsien Hsia

An Edge-Cloud Collaborative Scalp Inspection System Based on Robust Representation Learning
IEEE Transactions on Consumer Electronics, 2024 | DOI: 10.1109/TCE.2024.3474911
Contributors: Sin-Ye Jhong, Guan-Ting Li, Chih-Hsien Hsia

Tucker Decomposition and Log-Gabor Feature-Based Quality Assessment for the Screen Content Videos
IEEE Transactions on Instrumentation and Measurement, 2024 | DOI: 10.1109/TIM.2024.3381267
Contributors: Hailiang Huang, Huanqiang Zeng, Jing Chen, Junhui Hou, Chih-Hsien Hsia, Kai-Kuang Ma

Width-Adaptive CNN: Fast CU Partition Prediction for VVC Screen Content Coding
IEEE Transactions on Multimedia, 2024 | DOI: 10.1109/TMM.2024.3410116
Contributors: Chao Jiao, Huanqiang Zeng, Jing Chen, Chih-Hsien Hsia, Tianlei Wang, Kai-Kuang Ma

 

 

 

Prof. Wen Jiang | Artificial Intelligence | Best Researcher Award

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Prof. Wen Jiang | Artificial Intelligence | Best Researcher Award

Northwestern Polytechnical University, China.

Prof. Wen Jiang is a distinguished researcher and academic with a Ph.D. from Northwestern Polytechnical University, Xi’an, China (2009). She currently serves as a professor in the School of Electronics and Information at Northwestern Polytechnical University. Her work focuses on cutting-edge areas like information fusion, artificial intelligence, remote sensing image processing, and intelligent algorithm security, making her a leader in her field.

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Education 🎓

Prof. Wen Jiang has an impressive academic background in information systems and engineering. She earned her Ph.D. in Information Systems from Northwestern Polytechnical University, Xi’an, China, in 2009, where her research focused on innovative data systems and intelligent technologies. Prior to that, she completed her Master’s degree in Information Engineering at Information Engineering University, Zhengzhou, China, in 1997, gaining in-depth knowledge of advanced engineering concepts. She began her academic journey with a Bachelor’s degree in Information Engineering from the same university in 1994, building a strong foundation for her pioneering contributions to the field.

Experience 🏫

Prof. Wen Jiang is a Professor at the School of Electronics and Information, Northwestern Polytechnical University, where she has made a significant impact in academia. She is highly regarded for mentoring aspiring researchers and leading innovative projects in advanced technologies. Her leadership and expertise have been instrumental in driving forward research in areas like artificial intelligence, information fusion, and algorithm security..

Research Interests 🔍

Information Fusion:
Integrating data from diverse sources to enable smarter and more efficient decision-making processes, crucial for applications in defense, healthcare, and industry.

Artificial Intelligence:
Advancing machine learning and intelligent systems to solve complex problems and enhance automation across various domains.

Remote Sensing Image Processing:
Developing cutting-edge tools for environmental monitoring, urban planning, disaster management, and mapping applications.

Intelligent Algorithm Security:
Ensuring the robustness, reliability, and safety of AI-driven solutions to address vulnerabilities in critical systems.

Publications Top Notes 📚

A New Data Augmentation Method Based on Mixup and Dempster-Shafer Theory IEEE Transactions on Multimedia, 2024
Contributors: Zhuo Zhang, Hongfei Wang, Jie Geng, Xinyang Deng, Wen Jiang. Link

A Novel Air Target Intention Recognition Method Based on Sample Reweighting and Attention-Bi-GRU IEEE Systems Journal, 2024
Contributors: Yu Zhang, Weichen Ma, Fanghui Huang, Xinyang Deng, Wen Jiang. Link

Causal Intervention and Parameter-Free Reasoning for Few-Shot SAR Target Recognition IEEE Transactions on Circuits and Systems for Video Technology, 2024, Contributors: Jie Geng, Weichen Ma, Wen Jiang. Link

CMSE: Cross-Modal Semantic Enhancement Network for Classification of Hyperspectral and LiDAR Data IEEE Transactions on Geoscience and Remote Sensing, 2024, Contributors: Wenqi Han, Wang Miao, Jie Geng, Wen Jiang. Link

Dual-Path Feature Aware Network for Remote Sensing Image Semantic Segmentation IEEE Transactions on Circuits and Systems for Video Technology, 2024, Contributors: Jie Geng, Shuai Song, Wen Jiang. Link