Machine Learning North Dakota

Curriculum Vitae Mostofa, PhD

Mohammad Gulam

Mostofa

Biostatistician III

Institute for Medical Research

Durham, North Carolina

*************@*****.***/

701-***-**** (Cell)

PROFILE

With a unique educational background in Statistical Science and Biostatistics, I bring versatile skills to consulting as a Statistician. My extensive experience in teaching and research covers various data types and statistical methods. My consulting expertise extends to utilizing statistical and biostatistical methods to address research questions across diverse sectors, including health, and nursing. I am also adept at reporting, writing, and editing the analytics sections of grants, articles, and manuscripts. Additionally, I hold a permanent resident card (Green Card) EDUCATION

Ph.D. in Applied Statistics (2022, Summer), Department of Statistics, North Dakota State University, Fargo, ND, USA

Thesis Title: Comparing Prediction Accuracies of Cancer Survival Using Machine Learning Techniques and Statistical Methods in Combination with Data Reduction Methods. Master of Science in Applied Statistics (2020), North Dakota State University, Fargo, ND, USA

Thesis Title: Propensity Score and Survival Analysis for Lung Cancer Master of Science in Applied Economics (2016), University of North Dakota, Grand Forks, ND, USA

Thesis Title: Impact of Seasonality on Agricultural Productivity in Bangladesh Bachelor of Science in Agricultural Economics (2003), Bangladesh Agricultural University, Mymensingh-2202, Bangladesh

Curriculum Vitae Mostofa, PhD

RESEARCH INTEREST

My broad research interests encompass Biostatistics, Data Science, Data Analytics, Environmental Statistics, Business Analytics, Time Series and Forecasting, Econometrics, Statistical Machine Learning, and Data Mining. I plan to develop and apply a variety of techniques in diverse fields such as health care industry.

EMPLOYMENT

Biostatistician III (From December 16 to till)

Institute for Medical Research (IMR)

Job responsibilities:

• Collaborate effectively with programmers, statisticians, investigators, research staff, and external collaborators

• Represent the statistical team in project team meetings; make recommendations about study design and execution in relation to statistical analysis

• Participate in conference calls, project meetings, weekly meetings with leadership, and other team meetings

• Provide support and training for junior-level biostatisticians

• Serve as a resource for other research staff

• Participate in most statistical aspects of a medical research project

• Conduct power analyses/sample size calculations

• Evaluate research studies and recommend statistical procedures to analyze the data

• Contribute meaningfully to discussions of analyses and identify next steps for analyses

• Write statistical analysis plans

• Perform quality assurance reviews of datasets before beginning analysis

• Learn new statistical methods, as needed, and apply new skills to future projects

• Perform intermediate and advanced statistical analyses, including but not limited to survival analysis, linear regression, and generalized linear modeling.

• Check results for accuracy and consistency

• Prepare comprehensive statistical reports to communicate findings with investigators

• Be able to work on any phase of a manuscript project, from initial meeting with an investigator to final review of a manuscript prior to submission for publication, with guidance

• Prepare statistical components of presentations, abstracts, study protocols, and manuscripts including methods and results sections

Curriculum Vitae Mostofa, PhD

Visiting Assistant Professor (From August 2023 to December 2024) Miami University, Oxford, Ohio, Department of Information System and Analytics I taught the following course:

• ISA 125. Introduction to Business Statistics

Visiting Assistant Professor (One year Position from August 2022 to May 2023) Roanoke College, Department of Mathematics and Economics, Salem, Roanoke, VA

• Course Taught: INQ 240 Statistical Reasoning: Here’s to Your Health, DATA 248 Data Visualization, 121-A Principles of Macroeconomics. Graduate Research Assistant

University of North Dakota, Grand Forks, ND-58202

• As part of my responsibilities, I collaborated on research design, conducted data analysis, interpreted results, trained other research assistants, and drafted and edited manuscripts and presentations. My duties were not limited to these tasks. Instructor

North Dakota State University, Fargo, ND-58102

• STAT 471: Introduction to the R Language, fall 2020.

• STAT 331: Regression Analysis, fall 2018, spring 2019. Graduate Teaching Assistant

North Dakota State University, Fargo, ND-58102

• STAT 330: Introductory Statistics in 2017, 2018, 2019, 2020 fall and spring. Curriculum Vitae Mostofa, PhD

2017 – 2021: Statistical Consultant, North Dakota State University, Fargo, ND

• Answering research questions and delivering timely results to clients, students, and faculty using Base SAS, R, and simulations.

• Offering statistical consulting services for research studies of faculty, staff, and students (both graduate and undergraduate) at NDSU and throughout the N.D. University System

• Assisting at different phases of the research process, which encompass project planning, design, data organization, statistical analysis, and communication of results.

• Providing consultation on data acquisition, data analysis, and the presentation of results, which includes creating graphics.

• Using R, Python, and SAS to analyze and model statistical relationships.

• Prepare data for statistical analysis by transforming, cleaning, and reformatting.

• Write code to test research hypotheses in various fields, including health, pharmacy, business, and engineering.

• Execute statistical methods including ANOVA, frequencies/associations (chi-square tests), linear models, regressions, logistic regression, nonlinear regression, discriminant analysis, Survival Analysis using Kaplan Meier methods and Cox Regression.

• Prediction diseases survival using machine learning techniques including decision tree, Random Forest, artificial neural network, factor analysis, simulation, principal component analysis, etc.

• Transform data from univariate to multivariate structure and vice versa for statistical modeling and times series analysis.

• Assist with writing for research journal publications.

• Work effectively with individuals from a wide variety of backgrounds while maintaining ethical standards.

• Collaborate on statistical content for research proposals with master's students. Curriculum Vitae Mostofa, PhD

Research Data Scientist (2010 to 2013)

Statistics and Information & Communication Technology Division, Bangladesh Agricultural Research Institute, Joydebpur, Gazipur, Bangladesh-1701 Job responsibilities included as a research scientist but not limited to:

• Data Management

• Data Mining

• Data Modeling

• Data Visualization

• Big Data Analysis

• Designing questionnaire

• Categorical Data Analysis

• Used statistical tools like Multivariate Regression, Random Forest, Decision Tree, Cluster Analysis, GLM analysis, Tobit model, ARIMA and SARIMA model for forecasting and time series analysis, VECM model, Logistic Regression, Probabilistic Model, Instrumental Variables, Simultaneous equation model etc. LECTURER (2004 to 2009)

East West University, Dhaka, Bangladesh

Taught: Introductory Statistics, Linear Algebra, Business Analytics by R, Calculus I, Econometrics, Probability and Mathematical Statistics I. UNDERGRADUATE STUDENTS MENTORED

• MD Raduan Ahmed.

“ Capstone Project Title: Predicting Customer Churn in a Subscription-Based Business in the context of Bangladesh”.

• Md Abdul Ali.

“Capstone Project Title: Predicting Agricultural Productivity in the Southern Part of Bangladesh”.

• MRS. Souravi.

“Capstone Project Title: Visualizing Global Climate Change Trends”.

• Shilpi Das.

“Capstone Project Title: E-commerce Sales and Customer Behavior Analysis using Decision Tree”.

Curriculum Vitae Mostofa, PhD

CONFERENCE AND PRESENTATIONS

• “World Data Summit” Amsterdam, The Netherlands, May 17-19, 2023

• Joint Statistical Meeting (JSM), Denver Colorado, July 27-August1, 2019

• Prediction of Lung Cancer Survival using Machine Learning and Statistical Techniques”, Ninth Annual Red River Valley Statistical Conference, North Dakota State University, May 1, 2019.

• Invited Speaker “ IJCCI 2019 : 3rd International Joint Conference on Computational Intelligence, Dhaka, Bangladesh”.

COMPUTER AND PROGRAMMING SKILLS

• Statistical programming: R, SAS, SPSS, JMP, Minitab, STATA, MySQL, Python, R Shiny, R Markdown, Power BI, Tableau.

• Office Tools: Microsoft office (All versions), open office, Advanced Excel, PowerPoint

PUBLICATIONS

• M.G. Mostofa, M. Reazaul Karim, M.A. Monayem, Miah (2010). Growth and Supply response of winter vegetables production in Bangladesh. Thai journal of Agricultural Science. Vol 43(3) : 175-182

PUBLISHIED BOOK

• Climate change and cost-benefit of T. Aman rice in Bangladesh. Lambert Academic Publishing GmbH &Co.KG, Germany, ISBN : 978-3-8454-0087-7

(https://www.amazon.in/Climate-Change-Cost-Benefit-T-Aman- Bangladesh/dp/384-***-****)

Curriculum Vitae Mostofa, PhD

PUBLICATIONS IN PREPARATION

1. M.G.Mostofa, and Orr, Megan, “ Propensity Score and Survival Analysis of Lung Cancer”

2. M.G. Mostofa, and Orr, Megan, “Prediction of Lung Cancer Survival using Machine Learning and Statistical Techniques.”

3. M.G. Mostofa, and Fatima, “Predicting Colon Cancer Survivability: a comparison of four data mining methods.”

4. M.G. Mostofa, “Predicting Leukemia Survivability: a comparison of three data mining methods.

SKILLS OF DATA SCIENCE AND MACHINE LEARNING TECHNIQUES

• Statistics and Probability Skills: Descriptive Statistics, Inferential Statistics, Probability Distributions, Hypothesis Testing, Analysis of Variance, Outlier Detection, Boxplot concepts, Bayesian Inference, Regression Analysis, Bias- Variance Tradeoff, Generalization Error, Model Complexity, Generalized Linear Models, Time Series and Forecasting Analysis, and other advanced level of statistical models.

• Mathematical Skills: Vectors, Matrix, Matrix Operations, System of Linear Equation, Determinants, Gaussian Elimination, Matrix Inversion, Matrix Factorization, Cramer’s Rule, Eigen Values, Eigen Vectors, Vector Spaces, Linear Independence, and Span, Derivatives, Partial Derivatives, Gradients, Hessians, Integration, Numerical Integration, Interpolation, Root Finding, Differential Equations, Optimization Techniques, Linear Programming, Convex Optimization, and Non-Linear Optimization

• Supervised Machine Learning Algorithm Skills: Classification Models including Decision Trees, Random Forest, Support Vector Machine, Naïve Bayes Classifier, K-Nearest Neighbors (KNN), Gradient Boosting Machines (GBM), Neural Networks, Ensemble Methods, Logistic Regression, and Linear Discriminant Analysis (LDA).

• Unsupervised Machine Learning Algorithm Skills: Clustering including K-Means Clustering, Hierarchical Clustering, and Density-Based Spatial Clustering of Applications with Noise, Dimensionality Reduction including Principal Component Analysis (PCA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Autoencoders, Anomaly Detection including Isolation Forest, and One-Class SVM, Generative Models including Gaussian Mixture Models (GMM), and Variational Autoencoders (VAEs).

Curriculum Vitae Mostofa, PhD

• Features Engineering Skills: Types of Variables, Measure of Central Tendency, Label Encoder, One Hot Encoder including Dummy Variable, and Multicollinearity problem, Binary Encoding, and Ordinal Encoding.

• Features Selection for High Dimensionality Reduction Skills: Filter Methods, Wrapper Methods, Embedded Methods, PCA analysis, and Boruta Algorithm.

• Data Preprocessing and Regularization Techniques Skills: Data Normalization, Feature Scaling, Handling Missing Values, Data Augmentation, L1/L2 (Lasso and Ridge Regression), and standardization.

• Text Data Preprocessing and Features Vectorizer Skills: Tokenization including Word Token, Sentence Token, Sub Word Token, Character Token, and Name Entity Token, Text Normalization including Stemming, and Lemmatization, Vectorizer including Bag of Words, TF-IDF Vectorizer, Term Frequency, Inverse Document Frequency, and TF-IDF Score.

• Deep Learning and Neural Networks Skills: Feed forward Network, Convolutional Network, Recurrent Network, Transform Network, Neural Network Architecture, and Bayesian Neural Network.

• Model Evaluation and Validation Skills: Cross- Validation, Confusion Matrix, Accuracy, Precision, Recall, F-1 Score, Area Under the Curve (AUC), and Receiver Operating Characteristics (ROC).

Curriculum Vitae Mostofa, PhD

SKILLS OF BIOSTATISTICS

• Longitudinal data analysis

• Survival analysis

• Mixed effects modeling

• Generalized additive modeling.

• Bayesian modeling

• Structural equation modeling

• Latent Class Analysis

• Factor Analysis

• Power Analysis

• Sample Size Calculation

SKILLS OF APPLIED STATISTICS

• Regression Models

• Robust Regression

• Mixed Effects Modeling

• Generalized additive modeling.

• Bayesian modeling

• Structural equation modeling

• Multinomial Logistic Regression

• Multivariate Multiple Regression

• Logistic Regression

• Negative Binomial regression

• Categorical and Discrete Data Analysis

• Time Series and Forecasting (ARIMA, SARIMA, GARCH)

• Probit Regression

HONORS AND AWARDS

• 2019 Travel Grant, North Dakota State University

• 2011 Best Young Scientist Award, Bangladesh Agricultural Research Institute

• 2002 Gold Medal for undergraduate results, Bangladesh Agricultural University Curriculum Vitae Mostofa, PhD

MEMBERSHIPS

• The American Statistical Association (ASA)

• International Biometric Society (ENAR)

• Bangladesh Statistical Association (BSA)

• Bangladesh Economist Association (1999—present)

LEADERSHIP & COMMUNITY SERVICE

Secretary, Graduate Student Association of College of Business and Public Administration at University of North Dakota (2015-2016).

President, Bangladesh Student Association at the University of North Dakota,

(2015-2016).

Senator at Student Government, NDSU- Representing graduate studies, and discuss student issues, and decide whether to approve various funding requests or legislation for student organizations. (2017-2018)

Graduate Student Council (GSC), NDSU, Programming /Professional Development Committee co-chair- Enhanced collaboration to create workshops for the graduate students. (2018-2019).

Organizing Secretary, English Debating Society, Bangladesh Agricultural University (2001-2003)

Joint Secretary, Padochinno Cultural Organization of Bangladesh Agricultural University (1998-2000).

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