Lili Zhan | Artificial Intelligence | Best Researcher Award

Published on by Global Scholar 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

Nida Saddaf Khan | Artificial intelligence | Best Researcher Award

Published on by Global Scholar Awards

🌟Dr. Nida Saddaf Khan, Artificial intelligence, Best Researcher Award🏆

  • Doctorate at Aga Khan University, Karachi Pakistan

Dr. Nida Saddaf Khan is a dedicated faculty member, seasoned researcher, and accomplished data scientist specializing in healthcare solutions. With over 15 years of teaching experience at esteemed institutions in Pakistan, she holds a Ph.D. in Computer Science with a focus on managing clinical treatment for anxiety and obsessive-compulsive disorder (OCD) using deep learning and smart devices. Currently serving as a Senior Instructor at the Clinical and Translational Research Incubator (CITRIC)-Health Data Science Centre at Medical College, Aga Khan University, Karachi, Pakistan, she is actively engaged in research collaborations and projects funded by organizations such as the Patrick J. McGovern Foundation and the Bill & Melinda Gates Foundation. Dr. Khan’s career ambitions center on becoming a well-trained and seasoned researcher in AI and machine learning for healthcare, with a focus on mental health, while also aspiring to pursue a career in academia to mentor the next generation of healthcare leaders.

Author Metrics

Dr. Khan’s research output is reflected in her author metrics, which include publications in high-impact journals such as Wireless Personal Communications and Sensors. She has also made significant contributions to datasets and open-access repositories, facilitating knowledge dissemination and collaboration within the research community.

Scopus Profile

Google Scholar Profile

  • Total Citations: 86
  • Total Documents: 5
  • h-index: 5

The provided information is about Dr. Nida Saddaf Khan, affiliated with the Institute of Business Administration in Karachi, Pakistan. She has a Scopus Author Identifier with the ID 56083863100 and has been cited 86 times across 85 documents. Dr. Khan has authored 5 documents, resulting in an h-index of 5.

Education

Dr. Khan holds a Ph.D. in Computer Science from the Institute of Business Administration (IBA), Karachi, Pakistan, with a thesis focused on human activity recognition for anxiety and OCD. She completed her M.S. and B.S. in Computer Science from the same institution, along with an MBA in Finance from Karachi University Business School (KUBS), University of Karachi, Pakistan.

Research Focus

Dr. Khan’s research primarily revolves around the application of artificial intelligence (AI) and machine learning techniques in healthcare, particularly in the domain of mental health. Her work spans projects such as developing AI-based systems for diagnosing and monitoring OCD and anxiety disorders, real-time analysis of sensor data for automated decision-making in smart homes, sentiment analysis on social media, and identification of opinion leaders in social networks. She is passionate about leveraging technology to improve health outcomes, with a specific interest in mental health interventions.

Professional Journey

Dr. Khan’s professional journey includes roles as a Senior Instructor at CITRIC-Health Data Science Centre, Visiting Faculty at IBA Karachi, Ph.D. Scholar at IBA Karachi, Consultant at Love For Data, Technical Consultant at Predictify.me, and Software Engineer at Software Island. Throughout her career, she has contributed to teaching, research, and project management in various capacities, focusing on health data science, machine learning, and software development.

Honors & Awards

Dr. Khan has received several honors and awards for her contributions to research and academia. Notably, she secured funding as a Co-Principal Investigator for an interdisciplinary project titled “Face Your Fear: Human Activity Recognition for Obsessive-Compulsive Disorder.” She has also been recognized for her publications in reputable journals and conferences, including awards such as the IBA RFPC Interdisciplinary Research Grant.

Publications Noted & Contributions

Dr. Khan has authored numerous research papers published in reputable journals and conferences, covering topics such as human activity recognition, sentiment analysis, IoT-based smart home systems, and anti-money laundering. She has also contributed to collaborative research projects and grant applications, demonstrating her commitment to advancing knowledge in her field.

Ontology based expert-system for suspicious transactions detection
Authors: Q Rajput, NS Khan, A Larik, S Haider
Published in: Computer and Information Science, 2014
Citations: 69

A Bayesian approach for suspicious financial activity reporting
Authors: NS Khan, AS Larik, Q Rajput, S Haider
Published in: International Journal of Computers and Applications, 2013
Citations: 39

A survey of deep learning based models for human activity recognition
Authors: NS Khan, MS Ghani
Published in: Wireless Personal Communications, 2021
Citations: 38

Real-time analysis of a sensor’s data for automated decision making in an IoT-based smart home
Authors: NS Khan, S Ghani, S Haider
Published in: Sensors, 2018
Citations: 35

Identification of opinion leaders in social network
Authors: NS Khan, M Ata, Q Rajput
Published in: 2015 International Conference on Information and Communication Technologies
Citations: 19

ADAM-sense: Anxiety-displaying activities recognition by motion sensors
Authors: NS Khan, MS Ghani, G Anjum
Published in: Pervasive and Mobile Computing, 2021
Citations: 9

Predicting collective synchronous state of sentiments for users in social media
Authors: NS Khan, MS Ghani
Published in: Mehran University Research Journal of Engineering & Technology, 2019
Citations: 2

Research Timeline

Dr. Khan’s research timeline spans over a decade, starting from her role as a Research Assistant at the AI Lab, IBA Karachi, in 2012. She has since progressed through various academic and professional roles, contributing to research projects, organizing international events, securing research funding, and publishing her findings in reputable journals and conferences. Her research trajectory reflects a continuous dedication to advancing knowledge and addressing critical challenges in healthcare, particularly in mental health, through innovative research and collaboration.