Lili Zhan | Artificial Intelligence | Best Researcher Award

Published on by NESIN Awards

Assoc. Prof. Dr. Lili Zhan | Artificial Intelligence | Best Researcher Award

Associate Professor| Shandong University of Science and Technology | China

Assoc. Prof. Dr. Lili Zhan is a researcher whose work spans remote sensing, Arctic cryosphere monitoring, computer vision, and artificial intelligence–enhanced educational systems. Her scholarship incorporates both physical environmental analysis and advanced data-driven methodologies, with representative contributions including sensitivity analyses of microwave brightness temperature to variations in snow depth on Arctic sea ice, a deep-learning-based remote-sensing scene-classification framework employing EfficientNet-B7, and an improved YOLOv7 instance-segmentation method for ship detection in complex SAR imagery Lili-Zhan. She has also contributed to the design and implementation of intelligent teaching models grounded in contemporary AI and data-centric approaches, demonstrating interdisciplinarity across geospatial sciences and educational technology Lili-Zhan Across these domains, her work reflects a sustained commitment to methodological innovation, integrating state-of-the-art neural architectures with domain-specific challenges in environmental monitoring and maritime situational awareness. Her collaborations often bridge academic research groups focused on cryosphere change, Earth observation, and applied machine learning, enabling the development of tools that support improved climate understanding, maritime safety, and digital-education modernization. Although publication and citation metrics are not specified in the available document, the range of research topics and representative studies indicates a growing scholarly profile with contributions positioned at the intersection of remote-sensing physics and intelligent systems engineering. Collectively, her work holds global societal relevance: enhancing the accuracy of cryospheric measurements supports climate-model improvement and polar-region policy planning; advancing ship-detection techniques contributes to marine governance, environmental protection, and emergency response; and promoting AI-supported pedagogical frameworks aids the digital transformation of education.

Profile: Scopus 

Featured Publications

Zhan, L. (Year). SAR ship target instance segmentation based on SISS-YOLO. Journal Name, Volume(Issue), pages.

Lili Zhan’s work advances the precision of remote-sensing analytics and intelligent detection systems, strengthening global capabilities in environmental monitoring and maritime safety. Her innovations support science-driven decision-making with direct benefits for climate resilience and societal securit

Mozhgan Mokari | Computer vision | Best Researcher Award

Published on by NESIN Awards

Ms. Mozhgan Mokari | Computer vision | Best Researcher Award

Ph.d Candidate, Sharif University of technology, Iran

Ms. Mozhgan Mokari is a dedicated Ph.D. Candidate at Sharif University of Technology, Iran, specializing in Computer Vision. 🎓 Her profound knowledge and innovative research in the field have earned her the esteemed Best Researcher Award, highlighting her exceptional contributions to the realm of computer vision. 🌐 Ms. Mokari’s relentless pursuit of excellence and her commitment to advancing the frontiers of technology make her a distinguished figure in the academic community. 🌟

Profile

Scopus

Education Details 📚

Mozhgan Mokari Ghohroudi is a dedicated academic with a strong educational background. She is currently a PhD candidate pursuing a Doctor of Philosophy in Digital System Engineering at Sharif University of Technology, Tehran, Iran. Mozhgan has maintained an impressive GPA of 3.83 out of 4 (equivalent to 17.58 out of 20). Prior to her PhD, she completed her Master of Science in Digital System Engineering from the same university with a GPA of 3.79 (17.76/20) between 2014 and 2016. Mozhgan also holds a Bachelor of Science in Electrical Engineering from Amirkabir University of Technology (Tehran Polytechnic) and achieved the remarkable GPA of 3.89 out of 4 (18.41/20), ranking first in her class. She began her academic journey with a High School Diploma in Mathematics and Physics from the National Organization for Development of Exceptional Talents (NODET) in Kashan, Iran, where she achieved a GPA of 19.62 out of 20. 🎓

Experience or Employment Details 💼

Mozhgan Mokari Ghohroudi has a rich research and academic experience. She is currently working on her PhD thesis titled “Temporal human action localization in video using deep learning” under the supervision of Assistant Professor, Dr. Haj Sadeghi since 2019. For her Master’s thesis, Mozhgan worked on “Human action recognition using depth map image sequence for abnormal event detection” under the guidance of Assistant Professor, Dr. Mohammadzade in 2015. Additionally, she completed her Bachelor’s thesis on “Implementation of MRI image segmentation algorithm for tumor detection” under the supervision of Assistant Professor, Dr. Sharifian in 2014. Mozhgan’s academic journey has been marked by her commitment to the fields of Computer Vision, Machine Learning, and Biomedical Engineering. 🖥️🔬

Research Interests 🧠

Mozhgan Mokari Ghohroudi’s research interests span across various domains in the realm of technology and science. She is passionate about Computer Vision, Machine Learning, Image Processing, and Natural Language Processing. Furthermore, her interests extend to the interdisciplinary fields of Biomedical and Neuroscience research. Mozhgan is also intrigued by the potential applications of Deep Learning in these areas. She is keenly interested in exploring the possibilities of Augmented Reality/Virtual Reality and their integration with AI technologies. Mozhgan’s diverse research interests highlight her multifaceted approach to innovation and problem-solving in the technological domain. 🌐🧬

Awards 🏆

Mozhgan Mokari Ghohroudi’s academic excellence has been recognized through various awards and honors. She achieved the first rank in her Bachelor of Science in Electrical Engineering from Amirkabir University of Technology (Tehran Polytechnic) due to her outstanding GPA of 3.89 out of 4 (18.41/20). This recognition underscores Mozhgan’s dedication and exceptional performance in her academic pursuits. Her consistent academic achievements are a testament to her hard work and commitment to excellence in the field of technology and engineering. 🥇

Publications Top Notes 📝

  • Enhancing temporal action localization in an end-to-end network through estimation error incorporation
    Year: 2024
    Link
  • Recognizing Involuntary Actions from 3D Skeleton Data Using Body States
    Year: 2018
    Link
  • Fisherposes for Human Action Recognition Using Kinect Sensor Data
    Year: 2017
    Link
  • Development of an optimal process for friction stir welding based on GA-RSM hybrid algorithm
    Year: 2018