Dr. MD Khalid Hossen 🎓 is a Ph.D. researcher in Social Networks and Human-Centered Computing at National Chengchi University, Taiwan. His work focuses on PM2.5 pollution prediction, time series analysis, and neural networks 🤖. With multiple publications in renowned journals 📚 and hands-on experience in AI projects, he blends data science with real-world solutions 🌍. Dr. Hossen is skilled in Python, machine learning, and statistical analysis, making him a promising contributor to global scientific innovation 🚀.

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🎓 Early Academic Pursuits

Dr. MD Khalid Hossen began his academic journey in Electronics and Communication Engineering at Khulna University, Bangladesh, focusing his thesis on reducing PAPR in OFDM systems. He pursued a Master’s in Computer Science Engineering from UESTC, China (2016–2018), where he developed expertise in statistical analysis through web crawling techniques. Currently, he is completing a Ph.D. in Social Networks and Human-Centered Computing (SNHCC) at National Chengchi University and Academia Sinica, Taiwan , under the guidance of Prof. Meng Chang Chen.

💼 Professional Endeavorsc

Dr. Hossen has worked in both academia and industry. He served as a Part-Time Lecturer at Daffodil Institute of IT, Dhaka and worked as an Engineer at ROBI, Bangladesh. His professional roles have been instrumental in bridging theoretical research with real-world applications.

🔬 Contributions and Research Focus On Environmental Engineering

His research expertise spans Time Series Data, PM2.5 Pollution Prediction, Neural Networks, Statistical and Data Analysis, and Human-Centered Computing. He has led multiple projects in machine learning, including COVID-19 detection, flight delay prediction, and health diagnosis systems, utilizing cutting-edge tools like PyTorch, TensorFlow, and NLP frameworks.

🌍 Impact and Influence

Dr. Hossen’s work on PM2.5 forecasting using neural networks is published in top-tier journals such as PLOS ONE and Scientific Reports. His interdisciplinary research integrates AI with environmental data, offering practical solutions for pollution forecasting and public health safety.

🧠 Research Skills

Dr. Hossen is proficient in:

• Programming: Python, C++, Java, R, MATLAB, SQL

• Machine Learning: PyTorch, TensorFlow, Keras, XGBoost

• Data Tools: Pandas, NumPy, Seaborn, ggplot2
  His capabilities cover model design, data mining, visualization, and predictive analytics with high precision and innovation.

🏅 Awards and Honors

• TIGP Fellowship, Taiwan (2018–2025) 🎓

• Excellent Performance Award, UESTC, China (2016) 🌟

• Academic Scholarship, UESTC (2016–2018) 🎖️

🏛️ Legacy and Future Contributions

Dr. Hossen is committed to advancing AI-driven environmental analytics and human-centered technology design. His future contributions aim to harness deep learning for sustainable development, particularly in climate science and public health prediction systems, leaving a significant legacy in AI for social good.