Anees Alhasi | Electronics Engineering | Best Researcher Award

Mr. Anees Alhasi | Electronics Engineering | Best Researcher Award

PhD Student | Cranfield University | United Kingdom

Mr. Anees S. Mohamed Alhasi, a Libyan national, is a dedicated electrical engineer and researcher with a strong academic and professional background. He obtained his BSc in Electrical Engineering with distinction from Omar Al Mukhtar University, Libya, in 2011, followed by an MSc in Electrical and Electronic Engineering with distinction from Coventry University, United Kingdom, in 2019. His professional experience spans several years in the energy sector, serving as an Electrical Engineer at Ras Lanuf Oil and Gas Processing Company (RASCO) from 2012 to 2015 and later at the General Electricity Company of Libya (GECOL) from 2015 to 2017, where he was responsible for maintenance, supervision, safety compliance, and training of new engineers. His diverse research interests include smart grids, renewable and alternative energy, robotics, power systems, digital signal and image processing, and microprocessor applications, reflecting a broad focus on advancing intelligent and sustainable technologies. He possesses strong technical skills in MATLAB, C++, Python, VHDL, Proteus, and robotics programming, coupled with expertise in sensors, measurement technologies, and control systems. In addition to academic and professional achievements, Mr. Alhasi has attended international training programs in the UK to enhance his English language and academic communication skills. His contributions to engineering practice, research projects, and mentorship highlight his commitment to bridging academia and industry. Recognized for his leadership and teamwork, he has often acted as a shift supervisor and mentor, contributing to safety and innovation in high-pressure environments. With professional memberships in IEEE and ACM and a track record of excellence, he is well-positioned to expand his impact through global collaborations and high-impact research outputs. In conclusion, Mr. Anees Alhasi is a promising researcher and professional whose academic strength, industrial expertise, and leadership potential make him a strong candidate for recognition and future contributions to sustainable electrical and electronic engineering advancements.

Profiles: Google Scholar | ORCID

Featured Publication

Alhasi, A., Luk, P. C.-K., Ibrahim, K. A., & Luo, Z. (2025). Advanced Single-Phase Non-Isolated Microinverter with Time-Sharing Maximum Power Point Tracking Control Strategy. Energies, 18(18), 4925.

 

Mohsin Hasan | Management science and engineering | Best Researcher Award

Mr . Mohsin Hasan | Management science and engineering | Best Researcher Award

Student at Nanjing University of Aeronautics and Astronautics , China

Mohsin Hasan is a dedicated and impactful researcher currently pursuing a PhD in Management Science and Engineering at Nanjing University of Aeronautics and Astronautics, China. His research focuses on epileptic seizure prediction using advanced machine learning techniques, including LSTM, SHAP, and deep neural networks, addressing a critical healthcare challenge. With publications in top-tier SCIE-indexed journals such as Engineering Applications of Artificial Intelligence and Annals of Operations Research, he demonstrates strong academic rigor and innovation. Mohsin possesses expertise in Python programming, big data analysis, and research writing, supported by a multi-disciplinary academic background in sociology. He has also actively contributed to community health initiatives in Pakistan, reflecting a blend of technical and social impact. While improved English proficiency and expanded international collaboration could enhance his profile, his current achievements make him a strong candidate for the Best Researcher Award, showcasing both research excellence and real-world relevance.

Professional Profile

EducationšŸŽ“

Mohsin Hasan has a diverse and interdisciplinary educational background that bridges social sciences and engineering. He is currently pursuing a PhD in Management Science and Engineering at Nanjing University of Aeronautics and Astronautics in China, with a research focus on epileptic seizure prediction using machine learning and deep learning techniques. Prior to his doctoral studies, he completed an M.S. in Rural Sociology from the University of Agriculture Faisalabad and a Master’s degree in Sociology from the University of Sargodha, Pakistan. His academic journey began with a Bachelor of Arts from Government College University Faisalabad, followed by intermediate studies at Government Islamia College Chiniot and matriculation at Government High School Chak No. 152 JB Chiniot. Throughout his education, Mohsin has developed strong skills in Python programming, big data analysis, and research writing, positioning him to apply advanced technological solutions to both social and engineering problems, particularly in healthcare and community development.

Professional ExperiencešŸ“

Mohsin Hasan has a well-rounded professional background that spans academic research and community development. Currently, he is engaged in cutting-edge research as a PhD scholar, working on epileptic seizure prediction using machine learning, with multiple SCIE-indexed publications to his name. His earlier professional experience includes various social outreach and coordination roles across Pakistan. As a Social Outreach Worker with UNODC, he led awareness campaigns and community mobilization for drug addiction treatment. He also served as Supervisor for the Sehat Sahulat Insaaf Card project with RCDP, managing field staff and overseeing healthcare card distribution. As a Dosti Coordinator with Muslim Hands International, he trained teachers and encouraged school enrollment and student participation in extracurricular activities. Additionally, he worked as an Assistant Constituency Coordinator for the FAFEN Election Project, monitoring electoral processes and data collection. His experience demonstrates a strong blend of technical expertise, leadership, and community-oriented service.

Research InterestšŸ”Ž

Mohsin Hasan’s research interests lie at the intersection of artificial intelligence, healthcare, and data science, with a strong focus on real-world applications that enhance human well-being. His primary area of interest is the prediction and classification of epileptic seizures using advanced machine learning and deep learning techniques, including Long Short-Term Memory (LSTM), Kolmogorov Arnold Network Theorem, SHAP-driven feature analysis, and attention-based neural networks. He is particularly passionate about leveraging electroencephalography (EEG) data to develop interpretable and accurate models for early seizure detection. His research also extends to reliability engineering, operational research, and the integration of AI in medical diagnostics. With a background in sociology and rural development, Mohsin brings a unique, human-centered approach to technological innovation, aiming to bridge the gap between data-driven solutions and community health challenges. His interdisciplinary perspective fuels his commitment to creating scalable, impactful tools for healthcare and beyond, particularly in under-resourced and developing contexts.

Award and HonoršŸ†

Mohsin Hasan has earned recognition for his dedication to academic excellence and impactful research, positioning him as a strong candidate for prestigious honors. His most notable achievement is his contribution to high-impact, SCIE-indexed journals such as Engineering Applications of Artificial Intelligence and Annals of Operations Research, where his research on epileptic seizure prediction has gained international attention. In addition to academic publications, Mohsin has been involved in global policy discussions and training sessions, including regional dialogues hosted by the Asian Institute of Technology and certification courses by the World Health Organization on emerging health threats and COVID-19 response. His ability to translate complex data science techniques into meaningful healthcare solutions reflects both innovation and social commitment. These accomplishments highlight his exceptional talent, work ethic, and relevance in critical global issues. Such recognition not only underscores his scholarly contributions but also establishes him as a deserving candidate for awards celebrating research excellence and societal impact.

Research SkillšŸ”¬

Mohsin Hasan possesses a comprehensive set of research skills that enable him to conduct advanced, data-driven investigations with real-world impact. He is highly proficient in Python programming and well-versed in tools such as Jupyter Notebook, PyCharm, and Google Colab, which he utilizes for building and testing machine learning models. His core expertise lies in deep learning, particularly in applying algorithms like Long Short-Term Memory (LSTM), 1D-ResNet, and attention mechanisms for medical data analysis, especially EEG-based epileptic seizure prediction. Mohsin is skilled in big data analytics, neural network development, and SHAP-based model interpretation, which enhances the transparency and usability of AI models. Additionally, he is experienced in academic research writing, LaTeX formatting, and data visualization using software like Edraw Max and Visio. His ability to integrate technical depth with scientific communication, along with a strong foundation in statistical methods and real-time problem-solving, marks him as a capable and innovative researcher.

ConclusionšŸ’”

āœ… Yes, Mohsin Hasan is a strong and deserving candidate for the Best Researcher Award.

His profile demonstrates a rare and valuable combination of technical AI research, medical applications, and community-level engagement. His high-quality publications, technical skills, and international academic involvement position him as a rising researcher with significant impact potential.

Publications Top Notedāœ

  • Title: Long Short-Term Memory and Kolmogorov Arnold Network Theorem for Epileptic Seizure Prediction

  • Authors: Mohsin Hasan, Xufeng Zhao, Wenjuan Wu, Jiafei Dai, Xudong Gu, Asia Noreen

  • Year: 2025

  • Journal: Engineering Applications of Artificial Intelligence

  • Volume and Issue: Volume 154

  • Pages: Article 110757

  • Publisher: Elsevier

  • Indexing: SCIE

  • Citation Format (APA Style):
    Hasan, M., Zhao, X., Wu, W., Dai, J., Gu, X., & Noreen, A. (2025). Long Short-Term Memory and Kolmogorov Arnold Network Theorem for epileptic seizure prediction. Engineering Applications of Artificial Intelligence, 154, 110757. https://doi.org/10.1016/j.engappai.2025.110757 (DOI placeholder if needed)