Xiaopeng Han | Computer Science | Best Industrial Research Award

Dr. Xiaopeng Han | Computer Science | Best Industrial Research Award

Researcher at Purple Mountain Laboratories, China

Dr. Xiaopeng Han is a dedicated researcher currently serving as an Assistant Research Fellow at the Endogenous Security Research Center, Purple Mountain Laboratories. With a strong foundation in photogrammetry, remote sensing, and cyber-physical systems security, Dr. Han bridges geospatial technology and security innovation. His career has been marked by a blend of academic rigor and real-world application, particularly in the fields of high-resolution remote sensing image interpretation and network security. Over the past few years, he has contributed to numerous national and provincial research projects, including high-value initiatives like the National Key R&D Program and the Jiangsu Province Doctoral Innovation Program. Dr. Han has also played pivotal roles in multi-disciplinary collaborative research, publishing extensively in leading international journals. Notably, his work integrates machine learning, deep learning, and sensor network control with applications in smart cities and industrial cybersecurity. Through his academic endeavors and contributions to national strategy documents and patents, he has established himself as a well-rounded scientist pushing the boundaries of both remote sensing and cybersecurity. His robust profile and consistent academic engagement reflect a passion for scientific innovation, talent cultivation, and technological transformation.

Profile

ORCID

Education

Dr. Xiaopeng Han began his academic journey at Central South University, where he pursued a Bachelor of Engineering in Surveying and Mapping Engineering from September 2010 to June 2014. This program provided him with a solid grounding in geospatial science, data acquisition, and engineering applications. Motivated by a desire to further specialize, he continued his education at Wuhan University—one of China’s leading institutions in the field of photogrammetry and remote sensing—where he earned a Ph.D. between September 2014 and June 2019. His doctoral studies involved deep analytical work in remote sensing technologies, image classification, and environmental modeling. During this time, he developed a strong foundation in high-resolution image analysis and multi-source data fusion, skills that have been integral to his subsequent research. The academic rigor and innovative environment at Wuhan University equipped Dr. Han with the tools to thrive in cross-disciplinary research areas, paving the way for his transition into more security-focused technological research. Though he has not pursued postdoctoral studies, his educational background has enabled him to take on high-impact research roles in both academic and industry-aligned settings, bridging theory with practice.

Professional Experience

Dr. Xiaopeng Han’s professional journey reflects a well-rounded progression from industry roles to academic research positions. From July 2019 to July 2022, he worked as an Engineer in the System Research Department at the 14th Research Institute of China Electronics Technology Group Corporation (CETC). Here, he engaged in research and development activities focused on system integration, high-tech innovations, and security frameworks. This experience grounded his technical knowledge in practical, large-scale applications, particularly in cybersecurity systems and smart infrastructure. Since July 2022, Dr. Han has been serving as an Assistant Research Fellow at the Endogenous Security Research Center of Purple Mountain Laboratories. In this role, he has continued his work on network security, remote sensing, and data-driven system optimization. His professional portfolio includes collaborations on significant national projects, involving cutting-edge topics such as semi-supervised learning for remote sensing and cloud-edge industrial security technologies. He has also led and participated in provincial-level and talent development programs. These experiences have allowed him to blend the rigor of academic research with the urgency of real-world problem-solving. Dr. Han’s current position enables him to mentor junior researchers, drive innovative studies, and contribute to China’s evolving cybersecurity and geospatial technology landscapes.

Research Interest

Dr. Xiaopeng Han’s research interests span across multiple interdisciplinary domains, with a strong emphasis on high-resolution remote sensing, intelligent image interpretation, urban spatial analysis, and cybersecurity systems. His early academic work focused on photogrammetry and remote sensing, particularly in developing frameworks for image classification and environmental modeling using machine learning. Over time, his research evolved to address more complex challenges in smart city planning, environmental monitoring, and urban morphology analysis. Recently, Dr. Han has concentrated on cybersecurity, especially in relation to cloud-edge industrial systems and the development of endogenous security strategies. He is particularly interested in semi-supervised learning approaches for pixel-to-scene image interpretation, which allows for greater precision in automated data processing. Additionally, he investigates the application of artificial intelligence and deep learning in both remote sensing and network threat detection systems. His integrative research perspective allows him to develop solutions that link earth observation data with national defense and network security concerns. This convergence of disciplines places him at the forefront of innovation, where data science meets geospatial intelligence and cyber-physical security.

Research Skills

Dr. Xiaopeng Han possesses a diverse and advanced skill set, positioning him as a key contributor in both geospatial and cybersecurity research. His core competencies include high-resolution remote sensing image processing, data fusion techniques, and machine learning-based image classification methods. He is proficient in implementing multi-classifier learning frameworks that preserve edge features in complex remote sensing data. Beyond remote sensing, Dr. Han is also skilled in designing resilient control strategies for mobile sensor networks under adversarial conditions, including input delay and Sybil attacks. His work often involves semi-supervised and sparse representation learning, reflecting his deep understanding of AI model optimization for real-world scenarios. Furthermore, he has experience developing system-level threat detection and risk assessment methodologies, which are crucial for next-generation industrial and smart grid environments. His skills extend into software programming and system modeling, making him capable of conducting end-to-end experimentation and algorithm development. With the ability to cross traditional disciplinary boundaries, Dr. Han brings computational, analytical, and theoretical expertise to the table, supported by practical engagement in multi-million-yuan national and provincial projects. His research capabilities are complemented by his familiarity with cutting-edge platforms and security protocols in cloud-edge computing environments.

Awards and Honors

Dr. Xiaopeng Han has received several prestigious recognitions that underscore his academic excellence and innovative contributions. One of his most notable honors is the inclusion in the Jiangsu Province Dual-Innovation Doctoral Talent Program, administered by the Jiangsu Provincial Organization Department in 2020. This competitive award recognizes outstanding researchers with strong potential for innovation and industrial transformation. In addition to this award, Dr. Han has contributed to a wide range of patent filings, showcasing his applied research impact. These include patented methods for system security assessment, network threat detection, and 3D object reconstruction, among others. Many of these inventions are co-authored with leading experts in cybersecurity and have been registered both domestically in China and internationally through WIPO. He has also participated in high-profile conferences such as the IEEE ICTC 2024, interacting with global scholars and presenting breakthrough ideas. Dr. Han’s involvement in major strategy white papers, such as the “Cybersecurity Strategy and Technology Trends” released at the 2024 China Endogenous Security Conference, further cements his role as a thought leader. Collectively, these accolades reflect his dedication to blending theoretical research with practical solutions that address critical societal challenges.

Publications

Dr. Xiaopeng Han has a strong portfolio of publications in internationally renowned journals, reflecting his diverse research interests and collaborative capabilities. His most cited work includes “The edge-preservation multi-classifier relearning framework for the classification of high-resolution remotely sensed imagery” published in ISPRS Journal of Photogrammetry and Remote Sensing, which highlights novel classification methods for remote sensing images. He has also co-authored a pivotal study in Environmental Pollution analyzing the relationship between urban noise and city morphology, showcasing his engagement with real-world urban analytics. In the journal Land Degradation & Development, his contribution to monitoring ecosystem services in Shenzhen using deep learning and satellite imagery stands out as a key interdisciplinary application. More recently, Dr. Han has contributed to work on resilient control in sensor networks published in the International Journal of Applied Mathematics and Computer Science, reflecting his shift toward cybersecurity topics. Alongside journal articles, he has presented at major conferences like ICTC 2024 and authored multiple patents related to network threat detection and smart system security. His publication record demonstrates a continuous trajectory of innovation across different yet interlinked domains, with a focus on impactful research that bridges environmental science and cyber defense.

Conclusion

Dr. Xiaopeng Han is an accomplished researcher whose expertise lies at the intersection of geospatial science and cybersecurity. With an academic background rooted in photogrammetry and remote sensing, he has expanded his research to cover pressing issues in smart urban systems and industrial network security. His career trajectory—from an engineer in a national research institute to an Assistant Research Fellow at a premier lab—illustrates both his technical depth and upward professional mobility. Dr. Han has been entrusted with critical roles in high-value R&D projects, and his contributions are recognized through prestigious awards, patents, and scholarly publications. He actively contributes to scientific advancement not only through innovative research but also by participating in national policy formulation and knowledge dissemination. His ability to bridge disciplines and integrate theoretical and applied science makes him a unique asset in both academic and industrial settings. As he continues to explore new frontiers in semi-supervised learning, cyber-physical systems, and intelligent remote sensing, Dr. Han remains a driving force in shaping the future of integrated technology solutions. His work stands as a testament to rigorous scholarship aligned with real-world impact.

Mohitkumar Bhadla | Computer Science & Engineering | Best Researcher Award

Assoc. Prof. Dr. Mohitkumar Bhadla | Computer Science & Engineering | Best Researcher Award

Associate Professor & HOD at Gandhinagar University, Gujarat, India

Dr. Mohit Bhadla is a dedicated academician and researcher with over 16 years of experience in the field of Computer Engineering and Information Technology. He currently serves as the Head of the Department and Professor at Gandhinagar University, Gandhinagar. Throughout his career, Dr. Bhadla has contributed significantly to research and education, focusing on emerging technologies, software development, and network security. His expertise extends to mentoring students, developing innovative research methodologies, and enhancing academic curricula. Passionate about advancing technological education, he actively participates in conferences, workshops, and international collaborations to further his knowledge and contribute to the global research community.

Profile

Orcid

Education

Dr. Mohit Bhadla earned his Ph.D. in Computer Engineering from Rai University, Ahmedabad, in 2019. Prior to that, he completed his Master of Engineering (M.E.) in Computer Engineering from Noble Group of Institutions, Junagadh, affiliated with Gujarat Technological University in 2013. He holds a Bachelor of Engineering (B.E.) degree in Computer Science and Engineering from Anuradha Engineering College, Chikhali, Maharashtra, which he obtained in 2009. His strong academic foundation has equipped him with the necessary skills to excel in both research and teaching domains.

Professional Experience

Dr. Bhadla has held several prestigious academic positions throughout his career. Since July 2024, he has been serving as the Head of the Department and Professor at Gandhinagar University, where he oversees research initiatives and academic programs. Prior to this, he was the Associate Professor and Dean of Research Cell at Swarnim Startup & Innovation University from August 2023 to July 2024, where he played a crucial role in research-led teaching and curriculum development. From September 2019 to August 2023, he worked as an Associate Professor and Head of the IT Department at Ahmedabad Institute of Technology. His earlier academic roles include serving as an Assistant Professor at Gandhinagar Institute of Technology and Noble Group of Institutions. In addition to his academic career, he has industry experience as a Support Engineer at Mindarray Systems Ltd from 2016 to 2017 and as a Programme Assistant at RTO Junagadh from 2009 to 2012.

Research Interests

Dr. Bhadla’s research focuses on artificial intelligence, machine learning, Internet of Things (IoT), network security, and biomedical applications. His work involves developing efficient algorithms for intrusion detection, biomedical imaging, data security, and optimizing power consumption in wireless sensor networks. He has also explored applications of deep learning in healthcare and social network analysis. His contributions to research have been recognized through various publications in reputed journals and conference proceedings. He is an active member of professional organizations such as IEEE, ACM, and IFERP, contributing to research discussions and technological advancements.

Awards and Achievements

Dr. Mohit Bhadla has received numerous accolades for his outstanding contributions to research and academia. In 2022, he was honored with the Best Researcher Award by INSO Bangalore. He was also recognized with the Best Young Researcher Award in the International Research Awards on New Science Invention in Fiber Optics & Communication in 2022. His innovative work in IoT and networking has led to multiple patents, including a patent for “An IoT-Based Sensor Network for Smart City Implementations” granted by the Government of Australia. Additionally, he has received invitations as a featured speaker at international conferences, including the Peers Alley Conference in London. His contributions to software malware detection and wireless sensor networks have been widely acknowledged in the research community.

Selected Publications

An Intelligent IoT Intrusion Detection System using HeInit-WGAN and SSO-BNM CNN-Based Multivariate Feature Analysis (2023) – Published in Elsevier: Engineering Application of Artificial Intelligence.

Enhanced Ubiquitous System Architecture for Securing Healthcare IoT using Efficient Authentication and Encryption (2023) – Published in International Journal of Data Science and Analytics.

Multi-Stage Biomedical Feature Selection Extraction Algorithm for Cancer Detection (2023) – Published in Springer Nature: Applied Science.

Semantic Analysis for Image Distribution of Various Edge Detection Techniques (2022) – Published in IJRAR (UGC Approved).

Deep Learning-Based Dynamic User Alignment in Social Networks (2023) – Published in ACM JDIQ (Scopus Indexed).

Execution of Hard C-Means Clustering Algorithm for Medical Image Separation (2022) – Published in IJRAR (UGC Approved).

A Survey of Intrusion and Detection Models on Network and Communication Topologies (2023) – Published in UGC Approved Journal.

Conclusion

Dr. Mohit Bhadla is a distinguished academician, researcher, and mentor in the field of Computer Engineering. His extensive contributions to research, innovative curriculum development, and passion for teaching have significantly impacted students and fellow researchers. With multiple patents, high-impact publications, and international recognition, he continues to drive advancements in artificial intelligence, IoT, and network security. His commitment to excellence and knowledge dissemination makes him a valuable asset to the academic and research community, inspiring future generations of scholars and professionals.

Guangbo Yu | Computer Science | Best Researcher Award

Mr. Guangbo Yu | Computer Science | Best Researcher Award

Mr. Guangbo Yu, University of California, United States.

Guangbo Yu is a dedicated Ph.D. candidate at the University of California, Irvine, specializing in Biomedical Engineering. His research integrates artificial intelligence with radiological science, particularly focusing on innovative approaches to cancer immunotherapy. Yu combines his technical expertise in AI and medical imaging to advance predictive models for improved cancer treatment outcomes.

Profile

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Strengths for the Award

Advanced Education and Specialization: Guangbo Yu has an extensive academic background, working toward a PhD in Biomedical Engineering with a focus on Radiological Science. This, combined with a master’s degree in Computer Science, showcases a strong multidisciplinary foundation, especially in applying computational techniques to complex medical challenges.

Cutting-Edge Research Focus: Yu’s work emphasizes the integration of artificial intelligence in cancer immunotherapy, particularly through MRI biomarkers, an area with significant potential for impact. This kind of innovation is both timely and crucial, given the growing importance of personalized medicine in oncology.

Practical AI Implementation Experience: Yu’s professional experience as an AI Engineer at Tencent Qtrade demonstrates practical skills in building scalable AI-driven systems, including the ability to handle real-world unstructured data. This expertise in AI, especially in Named Entity Recognition (NER) and model enhancement, reflects his ability to bring sophisticated AI models into actionable, large-scale applications—a valuable asset for advancing medical technology.

Robust Publication Record: With multiple peer-reviewed publications and conference presentations in leading venues, Yu has a proven track record of research dissemination. His publications cover impactful topics, from immunotherapy strategies to specific applications in hepatocellular carcinoma and pancreatic cancer, positioning him as a researcher contributing novel insights to the field.

Recognized Expertise in Radiomics: Yu’s presentations and publications underline his skill in MRI radiomics, a crucial technique for monitoring therapeutic outcomes. His work has been showcased at reputable conferences like the Society of Interventional Radiology Annual Meeting, suggesting that his research has been well-received by the scientific community.

Areas for Improvement

Broader Clinical Impact: While Yu’s work is highly specialized, a broader clinical focus, potentially expanding beyond MRI biomarkers and AI-driven imaging in immunotherapy, might make his research more universally applicable. Collaborations across more diverse medical imaging modalities or therapeutic fields could strengthen his versatility.

Increased Independent Research: Most of Yu’s listed publications involve collaboration with the same group of researchers, suggesting potential reliance on collaborative efforts with his advisor and other colleagues. Publishing independent research or leading a project might help demonstrate his capability to drive research innovations autonomously.

Focus on Clinical Outcomes: While AI advancements and radiomics techniques are valuable, furthering efforts to connect these techniques directly to patient outcomes and clinical protocols could enhance the practical relevance of his work. Translational research that bridges the gap between experimental AI models and routine clinical use would amplify his impact.

Education 🎓

Guangbo Yu holds a Master’s degree in Computer Science from the University of Southern California (2017) and a Bachelor’s degree in Software Engineering from the University of Electronic Science and Technology of China (2015). Currently, he is working towards a Ph.D. in Biomedical Engineering at the University of California, Irvine, under the guidance of Professor Zhuoli Zhang. This extensive academic foundation allows Yu to bridge computational techniques with radiology to address complex medical challenges.

Experience 💼

Yu has applied his AI expertise both in academia and industry. As a Graduate Assistant Researcher at UC Irvine since 2022, he develops AI-driven predictive models for cancer immunotherapy evaluation. Previously, he worked as an Artificial Intelligence Engineer at Tencent Qtrade in China (2020–2022), where he implemented advanced Named Entity Recognition (NER) techniques to transform financial data communications, improving data accuracy by 11% and increasing the user base fivefold.

Research Interests 🔬

Yu’s primary research interest lies in leveraging artificial intelligence to advance cancer immunotherapy treatments. His work seeks to enhance MRI-based predictive models for assessing immunotherapy responses, aiming to address significant challenges in treatment evaluation.

Awards 🏆

While details on specific awards are not provided in this CV, Yu’s ongoing contributions to both AI and medical imaging establish him as a notable figure in the field. His achievements in machine learning for healthcare and his impact at Tencent illustrate his potential to receive recognition for innovation and excellence in biomedical research.

Publications 📚

  1. Gan, W., Lin, Y., Yu, G., Chen, G., & Ye, Q. (2022). Qtrade AI at SemEval-2022 Task 11: A Unified Framework for Multilingual NER Task. 16th International Workshop on Semantic Evaluation (SemEval-2022). Cited by other papers for its advancements in multilingual NER applications.
  2. Yu, G., Zhang, Z., Eresen, A., Hou, Q., Garcia, E. E., Yu, Z., Abi-Jaoudeh, N., Yaghmai, V., & Zhang, Z. (2024). MRI Radiomics to Monitor Therapeutic Outcome of Sorafenib Plus IHA Transcatheter NK Cell Combination Therapy in Hepatocellular Carcinoma. Journal of Translational Medicine.
  3. Zhang, Z., Yu, G., Eresen, A., Chen, Z., Yu, Z., Yaghmai, V., & Zhang, Z. (2024). Dendritic Cell Vaccination Combined with Irreversible Electroporation for Treating Pancreatic Cancer – A Narrative Review. Annals of Translational Medicine (under review).
  4. Eresen, A., Zhang, Z., Yu, G., Hou, Q., Chen, Z., Yu, Z., Yaghmai, V., & Zhang, Z. (2024). Sorafenib Plus Intrahepatic Arterial Catheter Delivery of Memory-Like Natural Killer Cell Combination Therapy Boosts Therapeutic Response in Hepatocellular Carcinoma. Journal of Translational Medicine (under review).

Conclusion

Guangbo Yu’s qualifications make him a strong candidate for the “Best Researcher Award” due to his substantial contributions to biomedical imaging and AI applications in cancer therapy. His research holds promise for enhancing cancer treatment strategies, and his professional and academic accomplishments underscore his commitment to advancing his field. By broadening his focus to more independently led projects and directly linking his work to clinical outcomes, Yu could further elevate his profile and impact.