I earned my Bachelor of Science in Mathematics from the University of Barishal, Bangladesh, with a CGPA of 3.91/4 (class rank: 2). Currently, I am pursuing my Master's(by research) in the final semester, major in Data Mining at the Computer Science and Technology Department at Yanshan University, China, under the Fulbright Chinese Government Scholarship (class rank: 1,GPA: 4/4). I have been working as a research assistant at the Data Mining Key Laboratory under the supervision of Professor Dr. Jing Feng Guo.

1. Muhammad Noman Sohail, Jiadong Ren, Shake Ibna Abir (2019). Group covariates assessment on real-life Diabetes patient’s by Fractional Polynomials: a study based on Logistic Regression Modeling. Journal of Biotech Research 2019;10:116-125 http://btsjournals.com/assets/2019v10p116-125.pdf

2. Muhammad Noman Sohail, Jiadong Ren, Shake Ibna Abir. Data mining techniques for Medical Growth: A Contribution of Researcher reviews. IJCSNS International Journal of Computer Science and Network Security, Vol.18 No.10, October 2018 http://paper.ijcsns.org/07_book/201810/20181002.pdf

3. Muhammad Noman Sohail, Jiadong Ren, Shake Ibna Abir. Why Only Data Mining? A pilot study on the Inadequacy and Domination of Data Mining Technology. IJRSFP(USA) International Journal of Recent Scientific Research vol 9, Issue, 10B, PP 29066-29073,2018 http://www.recentscientific.com/why-only-data-mining-pilot-study-inadequacy-and-domination-data-mining-technology

4.Presented my undergraduate project in 20^th International Mathematics Conference 08-10 December 2017, Department of Mathematics, University of Dhaka, Bangladesh.

Completed Undergraduate Project under Ms. Samima Akhter, Assistant Professor, University of Barishal, Bangladesh.
Topic: Solving Volterra Integro-Differential Equation by using Homotopy Perturbation Method, He’s Homotopy Perturbation Method, Variational Iteration Method, Series Solution, Adomian Decomposition Method, and Laplace Transformation Method. https://github.com/15703396763/Undergraduate-Project.git

Project on GitHub

1. Using Deep Learning to identify whether a person has worn a mask on his face or not during this Covid-19 pandemic (Convolution Neural Networks-CNN, Kera’s, Tensor Flow, and OpenCV). 

2. Predicting whether a loan case will be paid off or not by using five Machine Learning Classifier Algorithms (K Nearest Neighbor, Decision Tree, Support Vector Machine, and Logistic Regression) and find the best model using different evaluation metrics (Jaccard, F1-score and Log Loss). 

3. Data Visualizing of the Breast Cancer Wisconsin (Diagnostic) Data Set.

4. Using Linear Regression Model to predict the price of house sales in king country, USA, and calculate the coefficient of determination (