Xin Wang | Artificial Intelligence in Statistics | Best Paper Award

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Ms. Xin Wang | Artificial Intelligence in Statistics | Best Paper Award

Chang’an University | China

Ms. Xin Wang is a dedicated researcher in transportation engineering with a strong interdisciplinary background in engineering and economics. She is currently pursuing her PhD in Engineering at the College of Transportation Engineering, Chang’an University, where she specializes in travel behaviour research, traffic network modelling, optimal network toll problems, and econometric modelling of transport costs and efficiency. She previously earned a Master of Economics degree in Regional Economics and a Bachelor of Economics degree in Finance from Xi’an International Studies University, establishing a solid academic foundation that connects transportation systems with economic analysis. Her professional background includes serving as an Account Manager at the Bank of China, working as a Teaching Assistant at Xi’an International Studies University, and completing an internship as a Lobby Manager at the Bank of China, roles that strengthened her analytical capability, communication skills, and leadership experience. Throughout her academic journey, she has received multiple honors, including several College First-class and Second-class academic scholarships in recognition of her outstanding performance. Xin Wang has also participated in numerous key research projects and academic meetings, such as the World Transportation Convention, the Intelligent Operation and Management Evaluation of the Hong Kong-Zhuhai-Macao Bridge, the Higher Education Discipline Innovation Project 111 on sustainable transportation development in Western China, a research project on a MaaS-based public transportation integrated travel platform in Xi’an, and a study on financing and lending challenges faced by small and medium-sized enterprises. Her scholarly contributions include publications in respected journals such as IEEE Transactions on Intelligent Transportation Systems, Journal of Transport Geography, and Special Zone Economy. She is proficient in SPSS, ArcGIS, Endnote, Origin, EViews, Python, Photoshop, and Microsoft Office applications, supporting her research excellence. Fluent in English and Chinese with basic knowledge of French, Xin Wang is supervised by Professor Wei Zhou and is affiliated with the College of Transportation Engineering at Chang’an University in Xi’an, China.

Citation Metrics (Scopus)

40
30
20
10
0

Citations
31

Documents
3

h-index
3

Citations

Documents

h-index

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Jian Xia | Artificial Intelligence in Statistics | Research Excellence Award

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Dr. Jian Xia | Artificial Intelligence in Statistics | Research Excellence Award

Hubei University of Automotive Industry | China

Dr. Jian Xia is a dedicated materials scientist specializing in next-generation electronic and photonic devices, with a strong academic foundation and a growing record of impactful research. He obtained his Ph.D. degree from the School of Materials Science and Engineering at Huazhong University of Science and Technology, where he developed expertise in resistive switching devices, phase-change materials, and advanced optical memory technologies. After completing his doctoral studies, he joined the Hubei University of Automotive Technology as a lecturer, contributing actively to both teaching and research in the field of electronic materials and integrated circuit design. Dr. Xia’s research interests encompass memristors, phase-change memory, and photonic neuromorphic devices, all of which hold promising applications in high-performance computing, data storage, and artificial intelligence hardware. He has undertaken notable research projects, including the Open Fund of the Hubei Key Laboratory of Energy Storage and Power Battery and the Doctoral Scientific Research Foundation of Hubei University of Automotive Technology. With a citation index of 361 and a research portfolio of 20 SCI-indexed publications, Dr. Xia has contributed articles to leading international journals such as Nature Communications, Laser & Photonics Reviews, ACS Photonics, Applied Physics Letters, IEEE Electron Device Letters, and Science China Materials. His innovative contributions are further demonstrated by nine patents that are either published or under review, highlighting his commitment to advancing practical and technologically significant developments in electronic device engineering. Although he has yet to hold editorial appointments or professional memberships, his scholarly influence continues to grow through strong research visibility and future collaboration potential. Dr. Xia maintains an active academic presence on platforms such as ResearchGate and continues to advance pioneering research aimed at developing energy-efficient, high-density, and neuromorphic computing devices to meet the evolving demands of modern information technology.

Citation Metrics (Scopus)

400
300
200
100
0

Citations
361

Documents
7

h-index
5

Citations

Documents

h-index


View Scopus Profile

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Khurshid Hussain | Artificial Intelligence in Statistics | Research Excellence Award

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Mr. Khurshid Hussain | Artificial Intelligence in Statistics | Research Excellence Award

Kiost | South Korea

Mr. Khurshid Hussain is a dynamic researcher whose work spans advanced automotive engineering, semiconductor design, integrated sensing and communications, and AI-driven signal processing, establishing him as a multidisciplinary contributor across next-generation wireless, cybersecurity, and intelligent vehicular systems. He holds a Master’s degree in Advanced Automotive Engineering from Sun Moon University, South Korea, where he specialized in high-performance millimeter-wave circuit design with emphasis on 60 GHz digital variable-gain amplifiers, beamforming architectures, low-power attenuators, and chip-level ISAC systems for secure and intelligent communication. His research extends into geomatics and remote sensing, focusing on multimodal mapping using optical, SAR, and LiDAR streams, change detection, 3D reconstruction, and uncertainty-aware geospatial pipelines, alongside self-supervised and weak-supervised learning approaches for large-scale spatial data modeling. He is the inventor of a patented transistor-array-based variable attenuator and has authored an expanding collection of peer-reviewed publications in leading journals such as Electronics, IEEE Access, Applied Sciences, and IEEE Transactions, addressing topics ranging from radar–communication co-design and ultrasonic 3D beamforming sensors to predictive maintenance of aerospace components, OTFS-based V2X ISAC architectures, and AI-enhanced signal intelligence. His scholarly profile includes 9 documents, 77 citations, and an h-index of 4, reflecting his growing influence in mmWave IC design, wireless sensing, and AI-integrated communication. Khurshid has delivered technical presentations at major international conferences covering maritime IT convergence, high-frequency amplifier design, battery analytics, advanced beamforming, and power-efficient RF front-end systems. His expertise spans Cadence, HFSS, Python, MATLAB, OrCAD, cybersecurity tools, and vector network analyzers, reinforced by experience in transceiver integration, AI-chip convergence, intrusion detection systems, battery research, and embedded engineering. Earlier, he completed his B.Sc. in Electrical Engineering with a focus on IoT-based renewable-energy automation, where he developed sensor-driven, cloud-connected, and energy-efficient systems. Fluent in English and active in multicultural environments, Khurshid is known for his creativity, leadership, communication skills, and passion for innovation, continually advancing secure, intelligent, and energy-efficient technologies for the automotive, wireless, and sensing industries.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Hussain, K., & Yoo, J. (2025). Low-latency marine-based OTFS echo parameter estimation enabled by AI. Sensors, 25(23), Article 7104. DOI: 10.3390/s25237104

Hussain, K., Ali, E. M., Hussain, W., Raza, A., & Elkamchouchi, D. H. (2025). Robust OTFS-ISAC for vehicular-to-base station end-to-end sensing and communication. Electronics, 14(21), Article 4340. DOI: 10.3390/electronics14214340

Hussain, K., Jeon, W., Lee, Y., Song, I., & Oh, I. (2025). CMOS-compatible ultrasonic 3D beamforming sensor system for automotive applications. Applied Sciences, 15(16), Article 9201. DOI: 10.3390/app15169201

Hussain, K., & Oh, I. (2024). Joint radar, communication, and integration of beamforming technology. Electronics, 13(8), Article 1531. DOI: 10.3390/electronics13081531

Hussain, K., & Oh, I. (2024). Review of joint radar, communication, and integration of beam-forming technology. Preprint. DOI: 10.20944/preprints202404.0208.v1

En Yu | Artificial Intelligence in Statistics | Excellence in Research Award

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Mr. En Yu | Artificial Intelligence in Statistics | Excellence in Research Award

Huazhong University of Science and Technology | China

Mr. En Yu is a PhD student in the Department of Intelligence Science and Technology at Huazhong University of Science and Technology (HUST), where he also completed his M.S. and B.Eng. degrees, building a strong foundation in automation, intelligent systems, and multimodal learning. His research focuses on visual perception, spatial intelligence, and multimodal large language models (MLLMs), with pioneering contributions in image and video understanding, multimodal reasoning, and reinforcement learning–based alignment for foundation models. He has produced influential work, including research on anti-scaling laws and temporal hacking in video MLLMs, the development of future-prediction multimodal reasoning models, perception policy learning with RL for visual tasks, and breakthroughs in fully end-to-end multi-object tracking. His earlier work established new directions in cross-domain tracking with natural-language representations, contrastive multi-object tracking, and decoupled representation learning for relation-aware MOT. Yu has further advanced spatial intelligence through contributions to 3D multi-object tracking and open-vocabulary tracking, bridging perception, reasoning, and robust scene understanding. He has interned at MEGVII Technology in the Foundation Model Group under Xiangyu Zhang, at StepFun AI in the Multimodal LLM Group under Zheng Ge, and at the UCSB NLP Group under William Wang as a visiting PhD researcher, contributing to cutting-edge multimodal systems and video-language modeling. his work is rapidly shaping next-generation MLLMs and visual reasoning systems. He actively serves as a reviewer for top AI conferences including NeurIPS, CVPR, ICCV, ECCV, ICML, ICLR, and leading journals such as TMM and TCSVT. His current interests span synthetic multimodal data generation, supervised and reinforcement post-training for MLLMs, real-world navigation agents, game agents, and spatial perception in visual and multimodal foundation models. Outside research, he enjoys movies, singing, reading, ball games, swimming, and skiing.

Profile: Google Scholar 

Featured Publications

Yu, E., Zhao, L., Wei, Y., Yang, J., Wu, D., Kong, L., Wei, H., Wang, T., Ge, Z., et al. (2024). Merlin: Empowering multimodal LLMs with foresight minds. ECCV, 425–443.

Wei, H., Kong, L., Chen, J., Zhao, L., Ge, Z., Yu, E., Sun, J., Han, C., & Zhang, X. (2024). Small language model meets with reinforced vision vocabulary. arXiv Preprint, arXiv:2401.12503.

Yu, E., Lin, K., Zhao, L., Yin, J., Wei, Y., Peng, Y., Wei, H., Sun, J., Han, C., Ge, Z., et al. (2025). Perception-R1: Pioneering perception policy with reinforcement learning. NeurIPS.

Chen, S., Yu, E., Li, J., & Tao, W. (2024). Delving into the trajectory long-tail distribution for multi-object tracking. CVPR, 19341–19351.

Li, Z., Han, C., Ge, Z., Yang, J., Yu, E., Wang, H., Zhang, X., & Zhao, H. (2024). GroupLane: End-to-end 3D lane detection with channel-wise grouping. IEEE Robotics and Automation Letters, 24.

Ki Ryong Kwon | Artificial Intelligence in Statistics | Best Faculty Award

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Prof. Ki Ryong Kwon | Artificial Intelligence in Statistics | Best Faculty Award

Pukyong National University | South Korea

Professor Ki-Ryong Kwon is an eminent and highly respected scholar in electronics engineering, artificial intelligence, and computer science, serving as a leading Professor in the Division of Computer Engineering and AI at Pukyong National University, South Korea. he pursued his academic journey at Kyungpook National University, where he completed his bachelor’s, master’s, and doctoral degrees in Electronics Engineering, later advancing his research expertise through a prestigious postdoctoral fellowship at the University of Minnesota under the mentorship of Prof. Ahmed H. Tewfik, followed by a visiting scholar appointment at Colorado State University that further broadened his international academic exposure. Throughout his long-standing academic career, Professor Kwon has demonstrated exceptional leadership by serving as Dean of the College of Engineering, Vice-Dean of Engineering, Director of the Artificial Intelligence Lab, Director of the Center for Start-up Foundation, Director of the Center of IP Transfer, and Vice-Director of Industry-University Foundation Cooperation, contributing extensively to academic development, research infrastructure advancement, and student innovation ecosystems. Beyond the university environment, he has played influential strategic roles as Chairman of the Global Fintech Industry Promotion Center, Vice-Chairman of the Korea Cloud Association, Vice-Chairman of the Busan Federation of Service Industry, and Chair of the 4th Industrial Revolution Leadership Promotion Team for Busan City, where he has been instrumental in guiding regional and national initiatives in AI-driven transformation, digital economy growth, and emerging technology integration. His contributions to the global research community include major leadership roles in IEEE, the Korea Multimedia Society, the Korea Information Processing Society, and multiple international conferences where he has served as General Chair, Industrial Chair, Program Chair, and Organizing Chair. His research encompasses deep learning, digital watermarking, image forensics, signal processing, marine AI applications, smart digital-twin systems, cybersecurity, and intelligent multi-agent architectures. With approximately 118 published research documents, around 1,309 citations, and an estimated h-index in the mid-20s, he maintains a strong and influential academic footprint. Over his career, he has been honored with numerous Best Paper Awards, national recognitions, institutional leadership awards, and international distinctions that reflect his outstanding dedication to research excellence, innovation leadership, and the advancement of technology-driven societal development.

Profile: Scopus

Bao Chen | Artificial Intelligence in Statistics | Best Researcher Award

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Dr. Bao Chen | Artificial Intelligence in Statistics | Best Researcher Award

Dr. Bao Chen | Nanchang Hangkong University | China

Dr. Bao Chen is a dedicated researcher whose academic path reflects both perseverance and intellectual rigor. He completed his doctoral studies at the prestigious Harbin Institute of Technology, where he built a strong foundation in applied mathematics and computational modeling. Following his graduation, he continued to expand his research career with a focus on modern challenges in sparse optimization and image processing. His work has gained recognition at both national and international levels, supported by competitive funding agencies, including the National Natural Science Foundation of China and the Jiangxi Provincial Natural Science Foundation. Dr. Chen’s research is marked by innovation, with a distinctive ability to connect theoretical frameworks with practical applications. His contributions span across multiple disciplines, bridging functional analysis with applied imaging techniques. His collaborative spirit and scholarly excellence position him as an outstanding academic leader, committed to pushing the boundaries of knowledge and nurturing advancements in mathematical and computational sciences.

Profile

Scopus

Education

Dr. Bao Chen obtained his doctoral degree in mathematics from the Harbin Institute of Technology, one of the most respected institutions in China for science and engineering research. During his doctoral studies, he developed deep expertise in inverse problems, variational models, and functional analysis, equipping him with the necessary background to address challenging problems in computational mathematics. His education combined rigorous mathematical theory with an emphasis on practical problem-solving, preparing him for interdisciplinary research. This academic training laid the foundation for his future contributions to the fields of optimization, algorithms, and image restoration. The comprehensive academic environment at Harbin Institute of Technology also allowed him to cultivate collaborations with scholars from diverse fields, fostering a holistic view of applied mathematics. Dr. Chen’s education has not only shaped his research trajectory but also enabled him to contribute to teaching, mentoring, and scientific community-building in his later career.

Experience

Dr. Bao Chen has accumulated valuable experience in both research and applied problem-solving. His career has been supported by leading research foundations, which provided him with opportunities to pursue innovative projects. Through these experiences, he has developed expertise in handling complex optimization tasks, creating new algorithms, and applying mathematical models to real-world imaging challenges. His professional path demonstrates a consistent record of advancing computational techniques, with a focus on practical applications such as image deblurring, noise reduction, and low-light enhancement. Beyond his individual contributions, Dr. Chen has also collaborated with fellow researchers across multiple institutions, demonstrating a commitment to collective scientific progress. His experience extends to publishing in highly regarded journals, where his research has gained visibility among peers worldwide. This breadth of academic engagement highlights his role not only as a researcher but also as a contributor to the global scientific community.

Research Interests

Dr. Bao Chen’s research interests are centered on sparse optimization, variational algorithms, and image restoration. His work integrates rigorous mathematical theory with computational techniques, resulting in practical solutions for challenging inverse problems. He has a particular focus on low-light image enhancement, non-convex optimization models, and fractional-order approaches, where he has proposed innovative methodologies with strong theoretical underpinnings. Another important area of his research is functional analysis and its role in advancing algorithmic performance. By combining these directions, he addresses both the theoretical development and applied effectiveness of new models. His interdisciplinary approach reflects a vision to advance mathematical methods that can impact computer vision, imaging technologies, and engineering applications. With continuous exploration of emerging directions in plug-and-play frameworks and adaptive models, his research contributes to both the academic understanding of optimization and the practical improvement of imaging systems used across scientific and industrial fields.

Awards & Recognitions

Dr. Bao Chen has earned recognition from national and provincial research foundations, which entrusted him with funding to lead innovative projects. His successful acquisition of competitive research grants demonstrates both his academic credibility and the trust placed in his ability to advance significant scientific outcomes. These awards not only highlight his capability as a researcher but also underline his leadership in guiding impactful studies that address important challenges in image processing and computational mathematics. Beyond research funding, his publications in internationally recognized journals have received strong acknowledgment from the scientific community, where his models and algorithms have been cited and applied in further research. These achievements reflect his standing as a respected scholar whose work continues to inspire and influence peers. His awards and recognitions collectively affirm the impact of his contributions and the promise of his continued success in advancing mathematical research and applications.

Publication Top Notes

A Novel Retinex Model for Low-Light Image Enhancement Based on Non-local and Plug-and-Play

Journal: Information Sciences
Authors: Bao Chen, Kan Yu, Yuchao Tang, Xiaohua Ding

A Noise Estimation Method for Multiplicative Noise Removal

Journal: Computational and Applied Mathematics
Authors: Bao Chen, Yuchao Tang, Xiaohua Ding

A Novel Adaptive Non-convex TVp,q^{p,q} Model in Image Restoration

Journal: Inverse Problems & Imaging
Authors: Bao Chen, Yuchao Tang, Xiaohua Ding

A Novel Fractional-Order Non-Convex TVα,p Model in Image Deblurring

Journal: Fractal and Fractional
Authors: Bao Chen, Xiaohua Ding, Yuchao Tang

 A novel variable exponent non-convex model in image restoration

Journal: Applied Mathematics Letters
Authors: Bao Chen, Wenjuan Yao, Boying Wu, Xiaohua Ding

Conclusion

Dr. Bao Chen exemplifies the qualities of an outstanding researcher and award nominee. His academic journey from doctoral training to established research leadership reflects continuous growth, innovation, and dedication. With a focus on sparse optimization, functional analysis, and image processing, his work has addressed critical challenges while opening new avenues for exploration. His publications in internationally respected journals and his recognition through national research foundations underscore both the quality and influence of his research. Dr. Chen’s interdisciplinary approach ensures his contributions remain relevant across mathematics, engineering, and applied sciences. Moreover, his collaborative work highlights a commitment to advancing collective knowledge, inspiring peers and supporting future scholars. As an academic who consistently demonstrates originality, rigor, and impact, Dr. Chen stands as a highly deserving candidate for recognition, and his nomination strongly reflects his significant contributions to the global research community.