Hongchen Wu | Computer Science | Best Researcher Award

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Prof. Hongchen Wu | Computer Science | Best Researcher Award

Associate Professor at Shandong Normal University, China.

Dr. Hongchen Wu 🌏💻 is an associate professor in the School of Information Science & Engineering at Shandong Normal University. After earning his Ph.D. in Computer Science & Technology in 2016—supplemented by a two‑year joint Ph.D. stay at the University of California, Irvine—he has built a vibrant career at the crossroads of next‑generation Internet, information security, and AI‑driven data science. Wu leads multiple national and provincial projects on cross‑domain recommendation, privacy management, and online‑payment fraud, publishing widely in Neurocomputing, Information Processing & Management, IEEE Access, and other high‑impact venues. A committee member of the China Computer Federation (CCF) and active reviewer for top IEEE Transactions titles, he blends rigorous theory with real‑world impact—pushing the envelope on fake‑news detection, multimodal content analysis, and privacy‑aware personalization. Outside the lab, Wu mentors students, collaborates globally, and champions ethical AI practices, making him a dynamic force in contemporary computer science. 🚀📈

Professional  Profile:

Scopus

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Suitability For Best Researcher Award – Prof. Hongchen Wu

Dr. Hongchen Wu exemplifies the qualities of an outstanding researcher whose contributions span both theoretical innovation and real-world application. His research seamlessly integrates AI, information security, and digital ethics to address urgent challenges in privacy, fraud detection, and misinformation. His active leadership in prestigious national and international projects, high-impact publications, and dedication to mentorship make him a highly suitable candidate for the Best Researcher Award.

🎓 Education:

Wu completed his B.Eng. and M.Eng. at Shandong University 🏫 before obtaining his Ph.D. in Computer Science & Technology there in 2016. Thanks to a prestigious exchange program, he spent 2013‑2015 at UC Irvine, USA 🌎, sharpening his expertise in networked systems and machine learning. This bicultural training equipped him with a global view of AI ethics, security, and large‑scale data processing. 🧑‍🎓🔗

🚀 Professional Development :

Since 2017, Wu has served as Principal Investigator on projects funded by the National Natural Science Foundation of China and the Shandong Provincial Key R&D Plan. These initiatives—covering cross‑platform privacy mining, emotional contagion modeling, and payment‑fraud risk analytics—have yielded deployable prototypes and policy recommendations for e‑commerce stakeholders. Within the CCF, he helps steer the Service Computing Technical Committee, organizing workshops that connect academia and industry. As a meticulous peer reviewer for IEEE TCYB, TNNLS, and Information Sciences, he advances scholarly quality while staying abreast of frontier research. Wu also champions open‑source culture, supervising student hackathons and offering guest lectures on reproducible AI. Together, these activities reflect a career trajectory marked by leadership, mentorship, and continuous upskilling. 🛠️📚✨

🔍 Research Focus:

 Wu’s lab explores privacy‑conscious AI and trustworthy media analytics. Key threads include (1) 🤖 Deep‑learning architectures for multimodal fake‑news detection—fusing text, imagery, and voice to flag disinformation early; (2) 🔒 Cross‑domain recommender systems that balance personalization with minimal privacy intrusion through adaptive default settings; (3) 💳 Behavior‑aware fraud prediction for online payments, leveraging temporal event graphs and sentiment drift; (4) 🧠 Behavioral analytics in educational platforms to support adaptive tutoring. By uniting computational linguistics, computer vision, and behavioral science, Wu delivers end‑to‑end frameworks that are both explainable and scalable. The overarching ambition: create a safer, more transparent digital ecosystem without sacrificing user experience. 🌐⚖️

🏆 Awards & Honors:

 Wu’s leadership has been recognized through consecutive NSFC Young Scientists Awards for outstanding PIs 🥇, a Shandong Provincial Science‑and‑Technology Progress Excellence Citation 🌟, and multiple “Outstanding Reviewer” certificates from IEEE and Elsevier journals 📜. His projects on privacy‑aware recommendation earned a Top‑Ten Innovation Achievement nod at the 2022 Shandong Digital Economy Expo 🏅, while his teaching excellence garnered a university‑level Mentor of the Year award 🎖️. Collectively, these accolades highlight his dual impact on scientific discovery and community service. 👏

Publication Top Notes

1. Multimodal Fake News Detection via Progressive Fusion Networks

  • Authors: J. Jing, H. Wu, J. Sun, X. Fang, H. Zhang

  • Journal: Information Processing & Management

  • Volume/Issue: 60 (1)

  • Article Number: 103120

  • Year: 2023

  • Citations: 155

  • Summary: This paper presents a progressive fusion network approach to detect fake news by integrating multimodal data sources (e.g., text, images). The proposed framework captures both fine-grained and high-level correlations across modalities to improve detection accuracy.

2. Matrix Factorization for Personalized Recommendation with Implicit Feedback and Temporal Information in Social E-Commerce Networks

  • Authors: M. Li, H. Wu, H. Zhang

  • Journal: IEEE Access

  • Volume: 7

  • Pages: 141268–141276

  • Year: 2019

  • Citations: 31

  • Summary: This work enhances traditional matrix factorization techniques for recommendation systems by integrating users’ implicit feedback and temporal behaviors within social e-commerce platforms.

3. NSEP: Early Fake News Detection via News Semantic Environment Perception

  • Authors: X. Fang, H. Wu, J. Jing, Y. Meng, B. Yu, H. Yu, H. Zhang

  • Journal: Information Processing & Management

  • Volume/Issue: 61 (2)

  • Article Number: 103594

  • Year: 2024

  • Citations: 27

  • Summary: The paper introduces NSEP, a model designed for early fake news detection by perceiving the semantic environment surrounding the news content. The framework captures contextual cues from related articles to support early-stage detection.

4. Div-Clustering: Exploring Active Users for Social Collaborative Recommendation

  • Authors: H. Wu, X. Wang, Z. Peng, Q. Li

  • Journal: Journal of Network and Computer Applications

  • Volume/Issue: 36 (6)

  • Pages: 1642–1650

  • Year: 2013

  • Citations: 20

  • Summary: This study proposes Div-Clustering, a method that leverages active users’ social influence and clustering behavior to enhance collaborative filtering in recommendation systems.

5. Enabling Smart Anonymity Scheme for Security Collaborative Enhancement in Location-Based Services

  • Authors: H. Wu, M. Li, H. Zhang

  • Journal: IEEE Access

  • Volume: 7

  • Pages: 50031–50040

  • Year: 2019

  • Citations: 17

  • Summary: The paper presents a smart anonymity scheme to enhance security and privacy in location-based services, allowing secure collaboration among users without revealing sensitive information.

✅ Conclusion

Dr. Hongchen Wu is an exemplar of 21st-century research excellence. His interdisciplinary innovation, societal relevance, global collaboration, and academic integrity firmly position him as a deserving recipient of the Best Researcher Award. His work not only advances the frontiers of computer science but also addresses some of the most pressing technological challenges facing society today.

JUN WON HO | Computer Engineering | Best Researcher Award

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Dr. JUN WON HO | Computer Engineering | Best Researcher Award

Research Fellow at Incheon National University, South Korea.

Dr. Jun Won-Ho 🎓 is a dedicated Research Fellow at Incheon National University, South Korea 🇰🇷. He earned his Ph.D. in Computer Engineering in February 2023 🧠, focusing on sleep pattern analysis in an unconscious, non-intrusive state 🛏️. His innovations aim to revolutionize sleep health through biosensor-based technologies 💡. With peer-reviewed publications in SCI-indexed journals 📚 and a patent on body weight estimation while lying in bed 🧾, Dr. Jun is making sleep monitoring accessible and home-based. His work bridges healthcare and engineering, offering practical solutions for sleep apnea detection 🩺 using biosensors and ambient signals 🌐.

Professional Profile:

ORCID

Suitability for Best Researcher Award – Dr. Jun Won-Ho

Dr. Jun Won-Ho is highly suitable for the Best Researcher Award due to his pioneering research at the intersection of biomedical engineering and computer science. Despite being an early-career researcher, he has demonstrated remarkable innovation and scientific productivity, especially in the field of non-intrusive sleep health monitoring. His Ph.D. and postdoctoral work have resulted in SCI-indexed journal publications, a granted patent, and the development of AI-based, contact-free technologies to address global health concerns like sleep apnea—showing both originality and real-world impact.

🎓 Education and Experience

  • 🎓 Ph.D. in Computer Engineering – Incheon National University (2023)

  • 🧪 Research Fellow – Incheon National University (Current)

  • 📄 Published in SCI-indexed journals – Including Sensors

  • 🛏️ Doctoral Research – Focused on unobtrusive sleep pattern analysis

  • 🔬 Ongoing Research – Development of self-screening technology for sleep apnea

  • 🧾 Patent Holder – System for estimating body weight while lying on a bed

🚀 Professional Development

Dr. Jun Won-Ho has significantly contributed to the field of sleep science and biomedical engineering 🧠. His journey began with a strong academic foundation in computer engineering 🎓, which he has transformed into impactful research focused on real-world health challenges 🩺. He has authored articles in SCI-indexed journals 📚 and currently works on a cutting-edge sleep apnea screening solution using biosensors and environmental data 🌙📊. His patented invention 🧾 and active engagement in non-contact health monitoring technologies reflect his innovative mindset and commitment to improving global health accessibility 🌍💡.

🧬 Research Focus Category

Dr. Jun Won-Ho’s research falls under the category of Biomedical Engineering and Sleep Science 🧠🛌. He is especially focused on unobtrusive health monitoring, developing systems that use biosensors, physiological signals, and environmental data to analyze sleep patterns and detect sleep disorders like apnea 😴🩺. His goal is to eliminate the need for intrusive clinical testing such as polysomnography 🧪 and instead offer home-based, AI-powered health solutions 🌐📲. His patented work on weight estimation during sleep complements his broader mission of advancing digital health technologies for continuous, contact-free care 🧾💡.

🏅 Awards and Honors

  • 🧾 Patent Granted – System for Estimating Body Weight While Lying on a Bed (KR 10-2556030)

  • 📄 SCI-Indexed Publications – Published 2 articles in renowned journals like Sensors

  • 📌 Ph.D. Achievement – Doctorate completed with impactful research in 2023

  • 🏆 Nominated for Best Researcher Award – For contributions to biomedical sleep technology

  • 🧠 Research Innovation Recognition – Development of non-contact sleep apnea screening system

Publication Top Notes

1. Detection of Sleep Posture via Humidity Fluctuation Analysis in a Sensor-Embedded Pillow

  • Published: April 30, 2025

  • Journal: Bioengineering

  • DOI: 10.3390/bioengineering12050480

  • Summary: This study introduces a novel method for detecting sleep posture by analyzing humidity fluctuations using sensors embedded in a pillow. The system monitors changes caused by respiration and perspiration, offering a non-invasive approach to sleep posture detection.

2. Sleep Pattern Analysis in Unconstrained and Unconscious State

  • Published: November 29, 2022

  • Journal: Sensors

  • DOI: 10.3390/s22239296

  • Citation Count: 6

  • Summary: This research analyzes sleep patterns in individuals without physical constraints or active awareness. Utilizing various sensors, the study collects physiological and environmental data to classify sleep stages, providing insights into natural sleep behaviors.MDPI

3. Multi-Sensor Data Fusion with a Reconfigurable Module and Its Application to Unmanned Storage Boxes

  • Published: July 19, 2022

  • Journal: Sensors

  • DOI: 10.3390/s22145388

  • Citation Count: 12

  • Summary: This paper presents a reconfigurable module for multi-sensor data fusion, applied to unmanned storage boxes. By integrating data from various sensors, the system enhances reliability and security in automated storage environments.

Conclusion

Dr. Jun Won-Ho exemplifies the qualities of a Best Researcher Award recipient through his innovative mindset, impactful biomedical applications, and commitment to global health technology advancement. His work is not only academically rigorous but also practically transformative, making essential health monitoring more accessible, affordable, and patient-friendly. He stands out as a rising star in biomedical engineering, well-deserving of this prestigious recognition.

Yumeng Su | Engineering | Best Researcher Award

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Mr. Yumeng Su | Engineering | Best Researcher Award

Mr. Yumeng Su at Shanghai Jian Qiao University, China.

Su Yumeng 🎓, a top-ranking computer science undergraduate at Shanghai Jian Qiao University 🇨🇳, excels in AI 🤖, robotics 🚁, and embedded systems 🧠. With hands-on experience in drone development, ROS, and deep learning 💡, he has published impactful research and led award-winning teams 🏆. His technical expertise spans Python, MATLAB, LaTeX, and advanced hardware platforms like Jetson Nano and STM32 💻. Beyond academics, he’s a dynamic leader and athlete 🏀🚴‍♂️, known for his resilience and innovation in intelligent systems and smart hardware applications 🔍. Su’s work bridges theoretical AI with real-world applications 🌐.

Publication Top Notes

ORCID

Suitability for Best Researcher Award – Su Yumeng

Su Yumeng is a highly promising and exceptionally driven early-career researcher whose blend of technical excellence, innovation, and leadership places him as a top contender for the Best Researcher Award. As an undergraduate, his hands-on contributions to AI, robotics, and embedded systems are not only commendable but groundbreaking, particularly for his academic level. He demonstrates a rare ability to translate theory into impactful real-world applications, bridging research with innovation in autonomous systems, drone technology, and intelligent hardware solutions.

🔹 Education & Experience

  • 🎓 B.Sc. in Computer Science & Technology, Shanghai Jian Qiao University (2021–Present)

  • 📍 Focus: AI, Robotics, Embedded Systems, and Smart Hardware

  • 📚 Completed key courses with top grades (AI, Python, Robotics, Microcontroller Principles, etc.)

  • 🚀 ROS training at East China Normal University (Basic & Advanced UAV/Vehicle Tracking)

  • 🛠 Internship at Superdimension Technology Space: Autonomous drone development

  • 🧪 Project collaboration with FAST-Lab at Zhejiang University on UAVs

🔹 Professional Development

Su Yumeng continually advances his professional skills through academic projects 🧪, interdisciplinary competitions 🏆, and real-world UAV applications 🚁. He has mastered the integration of AI models like YOLO with edge computing platforms such as Jetson Nano and Raspberry Pi 💻. His leadership in innovation competitions reflects his capacity to guide teams and deliver impactful solutions 🎯. Su’s deep involvement in research and drone design demonstrates his ability to convert academic concepts into cutting-edge technology 💡. With practical ROS experience and sensor fusion expertise, he remains at the forefront of smart automation and robotics 🌐.

🔹 Research Focus Category

Su Yumeng’s research focuses on Artificial Intelligence in Embedded and Autonomous Systems 🤖, especially in smart robotics and deep learning applications for environmental perception and control 🌍. His work bridges physics-informed neural networks (PINNs) with real-time sensor fusion for drones and robotics 🤝. He explores practical challenges like crack detection in infrastructure using UAVs 🛠️, baby posture recognition on embedded platforms 🍼, and SLAM-based navigation for wheeled robots 🚗. His interdisciplinary approach merges hardware innovation with AI, yielding scalable, intelligent, and responsive systems suitable for civil engineering, healthcare, and autonomous mobility fields 🚀.

🔹 Awards & Honors

  • 🥇 National Second Prize, 17th National College Student Computer Design Competition (2024)

  • 🥉 National Bronze & Shanghai Gold, China Innovation Competition (2024)

  • 🥇 Shanghai Gold Award, Career Planning Competition (2024)

  • 🏅 First Prize, Shanghai College Student Computer Application Competition (2024)

  • 🥈 Shanghai Second Prize, Ti Cup Electronic Design Contest (2023)

  • 🥉 Bronze Award, “Challenge Cup” Entrepreneurship Plan Competition

  • 🥉 Shanghai Third Prize, China Robot & AI Competition (2024)

  • 🎖 National Motivational Scholarship ×3

  • 🎓 President “Qing Yun” Scholarship

  • 🎗 School Special Scholarship

Publication Top Notes

  • “The Feasibility Assessment Study of Bridge Crack Width Recognition in Images Based on Special Inspection UAV”
    Cited by: 13 | Year: 2020 ​

  • “Intelligent Crack Detection and Quantification in the Concrete Bridge: A Deep Learning-Assisted Image Processing Approach”
    Cited by: 20 | Year: 2022

Conclusion

Su Yumeng’s combination of academic excellence, deep technical knowledge, hands-on innovation, and research impact clearly distinguishes him as an ideal recipient of the Best Researcher Award. His contributions as an undergraduate are extraordinary and reflect the potential of a future global leader in AI and robotics research.