Multidisciplinary Data Science and AI Researcher
Resume:
Oluleye Babatunde, Ph.D
**** ****** **, ****, *****, VA
608-***-**** ! ********@*****.*** è https://www.linkedin.com/in/hezekiah/ ¥ I am a greencard holder About Me
I completed my PhD degree (on-site) in Computer Science from the School of Computer and Security Science, Edith Cowan University, Perth, WA, Australia in 2015. I developed an award-winning computer-based vision system for automatic identification of plant species based on the images of their leaves during my Ph.D. candidacy. I also hold a B.Sc degree in Mathematical Sciences (computer major) and three different MSc degrees in Applied Mathematics, Computer Sciences and Organizational Leadership from FUNNAB, University of Ibadan and Charleston Southern University (USA) respectively. I was a Postdoctoral Research Associate in Systems Biology in Professor John Yin’s Laboratory at the university of Wisconsin, Madison, USA where I studied and made research on Systems Biology. My interests cut across machine learning, image and signal processing, systems biology, operations research, mathematical modeling (using ODE, PDE and SDE). My educational, teaching, and research experiences span the region of Africa, Australia, and North America (USA). I have been teaching both online and in-class courses for more than 12 years, using several LMS tools such as Blackboard, Moodle, Canvas and Zoom. I use other tools suitable for teaching computer programming, IT, and mathematics courses, and such includes Microsoft whiteboard, Google classrooms and few others. I am an Arcitura Certified Big Data Consultant/Scientist and currently conducting research on data science solutions, information security, and systems biology (mathematical modeling and simulation of chemical and biological systems).
Software Skills
C/C++, Java, MATLAB, Python, R, JS, SQL, MongoDB,Tableau, SPSS, MS Office, Linux, SPSS, Mathemati- cal, Latex, Big Data Technologies [NoSQL, MongoDB, Apache Hadoop, Apache Spark, Amazon Redshift, Google BigQuery, Microsoft Azure HDInsight, Databricks.]
Link to my presentations/Lectures
Sample Presentations/Lectures
Education
1Edith Cowan University July 2012 – Oct 2015
Ph.D in Computer Science Perth, WA, Australia
Thesis: A Neuro-Genetic Approach To Automatic Identification of Plant Species 2 University of South Africa March 2021 - 2026
Ph.D in Applied Mathematics Pretoria, South Africa Thesis: Reaction-Diffusion Equations in Epidemiology 3Charleston Southern University March 2023
M.A in Organizational Leadership North Charleston, SC, USA 4University of Ibadan April 2009
M.Sc in Mathematics Ibadan, Oyo State, Nigeria
Thesis: On Numerical Simulation of a Class of Stochastic Differential Equation with Boundary Values 5Federal University of Agriculture Nov 2009
M.Sc in Computer Science Abeokuta, Ogun State, Nigeria Thesis: A Cellular Neural Networks-Based Model for Edge Detection 6Federal University of Agriculture May 2002
B.Sc in Mathematical sciences(Computer major) Abeokuta, Ogun State, Nigeria Thesis: Video Conferencing
Current Position
Assistant Professor of Computer Science Aug 2024 - Present Southwest Minnesota State University [SMSU], 56258, MN, USA. Postdoctoral Research Work (University of Wisconsin, Madision) Postdoctoral Research Associate March 2016 - June 2017 Worked with the Discovery Institute under Professor John Yin at the University of Wisconsin, Madison, WI, USA. Work description: Machine learning, mathematical modeling, and analysis of chemical and biological systems.
(ISC)2 Certified in Cyber Security (CC) - Credential ID: 1154749
• Domain 1: Security Principles
• Domain 2: Business Continuity (BC), Disaster Recovery (DR) & Incident Response Concepts
• Domain 3: Access Controls Concepts
• Domain 4: Network Security
• Domain 5: Security Operations
Arcitura Big Data Certifications (Consultant and Scientist) - Credential ID: 114973
• BDSCP Module 1: Fundamental Big Data
• BDSCP Module 2: Big Data Analysis & Technology Concepts
• BDSCP Module 3: Big Data Analysis & Technology Lab
• BDSCP Module 4: Fundamental Big Data Analysis & Science
• BDSCP Module 7: Fundamental Big Data Engineering
• BDSCP Module 8: Advanced Big Data Engineering
• BDSCP Module 9: Big Data Engineering Lab
• BDSCP Module 10: Fundamental Big Data Architecture
• BDSCP Module 11: Advanced Big Data Architecture
• BDSCP Module 12: Big Data Architecture Lab
Certification in Pedagogy (Education): June-July 2016
• High Impact Principles and Practices for STEM Education (HIPPSE)
• Advancing Learning Through Evidence-Based STEM Teaching (ALTES) Presentations, Talks, and Invited Lectures
• 2023 Annexing MATLAB Map-Reduce Capability for Big Data Analytics. Open Data Science Conference - East 2023
• 2023 Information Security Awareness – Tips to understand, identify and prevents cyber-attacks. UVA-Wise Lecture Committee Colloquium Presentation. March 2, 2023,
• 2023 Data Science and Machine Learning: ‘What is Deep about Deep Learning ’ ? UVA-Wise Lecture Com- mittee (March 10, 2023).
• 2023 A Neuro-Genetic Dynamical System On COVID-19 Host-Virus Interaction. Poster Presentation for the 3C Cavaliers 2023 Annual Symposium at UVA Charlottesville on May 3rd, 2023
• 2023 Advanced E-Learning Management Systems. Nigerian Computer Society, 2nd Technology-Enhanced Learning/Computing Education Forum (E-LEARNING 2023)
• 2022 Standardized Exam Scores as Predictor for NCLEX-RN® First-Time Pass Rates in a BSN Program.
• 2020 Introduction to Systems Biology. UVA-Wise Campus wide Seminar.
• 2021 From Machine Learning to Deep Learning: Mathematical secrets and underpinnings. Department of Biomedical Engineering, University of Virginia (October 14-16, 2021) Professional Activities
• Subject Matter Expert Cybersecurity[CC] Exam Development Volunteer for (ISC)2 Jan 2024 - March 2nd, 2024. SME6b
• Revewer: Intelligent Systems With Applications [ISWA]. The following articles were reviewed between [2021 and 2024]: ISWA-D-21-00030, ISWA-D-21-00030R1, ISWA-D-21-00057, ISWA-D-21-00073, ISWA-D-22-00101, ISWA-D-22-00588, ISWA-D-23-00233, ISWA-D-23-00254, ISWA-D-23-00319, ISWA-D-23-00372R1
• Subject Matter Expert CyberSecurity[CC] Exam Development Volunteer for (ISC)2 2023.
• 2023 I served as one the Panelist (Reviewers) for the NSF POSE Phase II SBE on January 5 and 6, 2023.
• Reviewer: PLOS Computational Biology PlosCompBIO
• Reviewer: Journal of Advances in Mathematics and Computer Science. JAMCS
• Reviewer: Machine Vision and Applications (MVAP).
• During 2022/2023 academic session, I gave expert advice to TechGuide Magazine on Computer Science Degree Programs. 2023 Tech Guide
• I attended series of meeting with AWS (Data Science) and (ISC)2 (Cyber Security) Organizations in May 2023
• Reviewer: Asian Federation for Information Technology in Agriculture (conference).[AFITA]
• Reviewer: The 2018 ACM Southeast Conference ”, Kenturcky, USA. ACMSE
• Teach coach: IBM regional Inter-collegiate programming contest (West-African, 2009).[ICPC] College and Community Service
2026 SMSU MN Computer Science Search Committe 2026 Conferences and Online seminars Attended
• In-Person: (ISC)2 SECURITY CONGRESS 2023; October 25 - 27, 2023 Nashville, TN, USA.
• Webinar 1: Validating and optimizing the security operations center (SOC) [06/28/2023]
• Webinar 2: New Phishing Benchmarks Unlocked:Is Your Organization Ahead of the Curve in 2023
• Webinar 3: Navigating the Cloud Maze:Protecting Your Workloads in a Multi-Cloud Environment [05/23/2023]
• Webinar 4: (ISC)2 Spotlight: Conversations with LeadersHow Can You Prepare for a Secure Future with Generative AI? - Sponsored by Extrahop [07/25/2023]
• Webinar 5: (ISC)2 - Learning Bytes: Unearthing Hidden Threats Through Detection Engineering [10/26/2023]
• Webinar 6: (ISC)2 A Practical Approach to Securing Workloads with Cloud-Agnostic Microsegmentation
[10/27/2023]
• Webinar 7: (ISC)2 Exam Item Development SME Training [06/10/2023] Research Experience
Postdoctoral Research Associate in Systems Biology at Professor John Yin’s Lab at the University of Wisconsin, Madison, WI, USA.
Work description: Quantitative modeling and analysis of chemical and biological systems.
• Mathematical modelling and computer simulation of viral infection spread [WID].
• Machine Learning for recognition of microscopic cell images (published article).
• Bioinformatics using Linux, R and MATLAB:
• Development of functions for genomic, proteomic, and gene expression
• Accessing genetic databases from the internet
• Sequence Analysis
• Microarray Analysis and Visualization
• Phylogenetic Analysis
• Mass Spectrometry pre-processing and Visualization
• Attended series gran writing seminars from 2016 till 2017
• Participated in group discussion and inter-disciplinary research meetings.
• Published an article on image-based machine learning fr cell identification. Research Interest
• Mathematical Modeling and Numerical Methods
• Machine Learning and Data Science
• Big Data Science, Architecture and Engineering
• Image Analysis and Computer Vision
• Systems Biology
• CyberSecurity
Relevant Coursework
• Operations Research
• Partial Differential Eq
• Ordinary Differential Eq
• Database Management
• Mathematical Modeling
• Numerical Analysis
• Computer Programming
• Computer Architecture
Teaching Experience
Sample courses taught in the past
COURSES TAUGHT
• CSC 1100 – Computer Literacy
• CSC 1180 – C++ Programming
• CSC 2180 – Data Structures
• CSC 3170 – Discrete Structures
• CSC 3600 – Operations Research
• CSC 3180 – Algorithms
• CSC 4150 - Introduction to Robotics and Artificial Intelligence
• CSC 4990/MIS 4990 – Seminar
• MATH 1110 – PreCalculus I
• MATH 1210 – PreCalculus II
• MATH/STAT 2180 – Applied Probability and Statistics
• MATH 3110 – Ordinary Differential Equations
• CSC 210 (Intro to Robotics)
• CSC 235 (C++ Programming)
• CSC 312 (Quantitative Modeling and Computer Simulation)
• CSC 325 (Java Programming).
• CSC 405 (Algorithms).
• CSC 442/542 (Data Mining)
• CSC 515 (M.Sc: Advanced Algorithm).
• CSC 519 (M.Sc Thesis Supervision: Machine Learning).
• CSC 635 (M.Sc: Advanced Network Security)
2Assistant Professor of Computer Science Aug 01, 2017 - July 30, 2020 Charleston Southern University [CSU], North Charleston, South Carolina, USA. COURSES TAUGHT
• CSC 210 (Intro to Robotics)
• CSC 235 (C++ Programming)
• CSC 312 (Quantitative Modeling and Computer Simulation)
• CSC 325 (Java Programming).
• CSC 405 (Algorithms).
• CSC 442/542 (Data Mining)
• CSC 515 (M.Sc: Advanced Algorithm).
• CSC 519 (M.Sc Thesis Supervision: Machine Learning).
• CSC 635 (M.Sc: Advanced Network Security)
2Lecturer April 2009 - Feb 2011
Joseph Ayo Babalola University [JABU], Ikeji-Arakeji, Osun State, Nigeria. COURSES TAUGHT
• CSC 221, 213 (Assembly Language 1 & 2).
• CSC 222 (C++ Programming).
• CSC 314 (Numerical Linear Algebra).
• CSC 316 (Operations Research).
• CSC 411 (Advanced Numerical Analysis)
• CSC 499 (Undergraduate Projects Supervision).
3Lecturer March 2007 - April 2009
ICT Polytechnic [GatewayICT], Itori-Ewekoro, Ogun State, Nigeria COURSES TAUGHT
• MAT 111 (Algebra).
• MAT 112 (Calculus and Trigonometry)
• MAT 214 (Ordinary Differential Equation)
• MAT 212 (Linear Algebra).
• CSC 214 (Digital Design)
4GCE Alevel Instructor Sep 2005 - Sep 2006
Global International College [GIC], Ibadan, Nigeria. SUBJECTS TAUGHT
• Mathematics for SAT (Scholastic Aptitude Test).
• GCE A Level Pure Mathematics (Cambridge, Edexel).
• GCE A Level ICT.
• IGCSE Mathematics/ICT.
5GCE Alevel Instructor Jan 2004 - Sep 2005
Educational Advancement Centre [EAC], Old Bodija, Ibadan, Nigeria. SUBJECTS TAUGHT
• Mathematics for SAT (Scholastic Aptitude Test)
• GCE Olevel, IGCSE Mathematics and ICT
• IJMB Mathematics, -GRE and GMAT
• GCE A Level Pure Mathematics (Cambridge, Edexel). 6Assistant Instructor @ NYSC Sept 2002 - Aug 2003
Federal Polytechnic Ede, [FederalPolytechnic], Osun State, Nigeria. SUBJECTS TAUGHT
• MTH 111 (Introductory Algebra).
• MTH 112 (Calculus).
• STA 221 (Mathematical Methods).
• MTH 312 (Advanced Mathematics).
• SEC 412 (Office Machines-ICT).
Statistical Computing
• Macroeconomic Forecasting: I have participated in Macroeconometric Forecasting course organized by International monetary fund (IMF) and we applied econometric techniques for modelling the dynamic behaviour of macroeconomic variables and their response to variable changes (using eViews software package. Specifically, we employed Australian-Fiji Macroeconomic dataset from 1980 to 2012 and other dataset from other countries. The following are the actual contents of this course:
• Module 1: EViews Basics.
• Module 2: Introduction to Forecasting with EViews.
• Module 3A: Statistical Properties of Time Series Data.
• Module 3B: Statistical Properties of Time Series Data.
• Module 4: Forecast Uncertainty & Model Evaluation.
• Module 5: Vector Autoregressions (VARs).
• Module 6: Vector Error Corrections Models (VECMs).
• Module 7: Evaluating Regression Models.
• Module 8: Final Assignment: Bringing It All Together.
• Further Learning: Combination Forecasting
• SPSS
• I have top notch experience in the production and interpretation of numerical and graphical outputs from statistical software.
• Strategic Information Planning: I have experimented with enterprise planning software (SPSS Data Modeller, SAS, and IBM Cognos) to implement collaborative planning, budgeting and forecasting solutions, as well as analytical and reporting application.
• Application of ANOVA, MANOVA, MANCOVA, ANCOVA and other tests for hypothesis testing: I have been specifically involved in theory and application of categorical data and using Pear- son’s chi-square test, Fisher’s exact test, the likelihood ratio, Yate’s correction, etc in my role as SOAR Ambassador at Graduate Research School of Edith Cowan University, Perth, WA, Australia
• Formulation of hypothesis for real-life scenario such as biomedical sciences or health informatics.
• Forecasting and data mining: I have practically carried forecasting of sales, weather and other dataset using Discriminant analysis, Neural Networks and regression techniques.
• Exploratory factorial analysis. I have been involved in using graphical representation, mathematical representation, comparing factorial analysis and principal component (PCA), etc,.
• Estimation of time-to-event models in the presence of censored data using survival analysis.
• Analysis of frequency counts of observations falling into each cross-classification category in a cross tabulation or a contingency table.
• Application of model selection Loglinear analysis and its hierarchical fitting to multidimensional cross tabulation using an iterative proportional fitting algorithm.
• Application of Logistic regression in determining the impact of multiple independent variables pre- sented simultaneously to predict membership of one or other of the two dependent variable categories.
• Use of generalized estimating equations for analysis of repeated measurements and or other correlated observations such as clustered data.
• Use of variance components for estimation of random effects to a model
• SPSS Syntax with Python statements: I have written lots of SPSS syntax embedded with python statements to do lot of regular routines.
• Statistical process control (SPC): I have applied SPC methods to monitor the quality of the product and process.
Image Analysis and Computer Vision
• I have (since 2003) been involved in basic image processing operations such as basic point operations, histogram normalization, histogram equalization, thresholding, template convolution, mathematical morphology including several morphological operators, gray-level morphology, erosion and dilation and Minkowski operators.
• I have applied textural orientation, conditional histograms, image Boolean operations, Euclidean distance maps, watershed segmentation and boundary lines and thickening.
• I have successfully applied the following techniques in building computer-based vision systems for image identi- fication: first-order edge operators, second-order edge operators, high-level feature extraction involving Fourier transforms, Zernike moments, and Legendre moments, colour features, geometrical and morphological features.
• I have single-handedly developed a dimensionality reduction system based on Genetic Algorithm and Particle Swam Optimization using novel fitness function.
• I have applied machine learning techniques such as k Nearest Neighbour, Artificial Neural Networks, and Statistical techniques in building several image identification and pattern recognition systems. Publications
1. Oluleye H Babatunde, OlaOluwa S. Yaya, Oluwasegun B. Adekoya Oluwagbenga T. Babatunde (2024). Testing Fractional Persistence and Nonlinearity in Infant Mortality Rates of Asia Countries. South Asian Journal of Social Studies and Economics. Vol 21, Issue 3; pg 58-70 2. Oluleye H. Babatunde, OlaOluwa S Yaya, and Oluwasegun B Adekoya (2024). Convergence among them- selves and Middle-income trap of South-East Asian Nations: Findings from a New approach. South Asian Journal of Social Studies and Economics. Vol 21, Issue 3, pg 46-57 3. Babatunde Oluleye, Baltes Ashley, Yin John (2017). Image-based identification of cell cultures by machine Learning. Journal of Advances in Mathematics and Computer Science. 23(1): 1-25. 4. Babatunde Oluleye, Armstrong Leisa J, Leng Jinsong and Diepeveen Dean (2015a). A survey of computer- based vision systems for automatic identification of plant species. Journal of Agricultural Informatics, 6(1),61- 71.
5. Babatunde Oluleye, Armstrong Leisa J, Leng Jinsong and Diepeveen Dean (2015b). A computer-based vision system for automatic identification of plant species using kNN and genetic PCA. Journal of Agricultural Informatics.
6. Babatunde Oluleye, Armstrong Leisa J, Leng Jinsong and Diepeveen Dean (2015c). Comparative analysis of Genetic Algorithm and Particle Swam Optimization: An application in precision agriculture. Asian Journal of Computer & Information Systems.
7. Babatunde Oluleye, Armstrong Leisa J, Leng Jinsong and Diepeveen Dean (2015d). A neuronal classification system for plant leaves using genetic image segmentation. British Journal of Mathematics & Computer Science, 9(3), 261-278. doi: 10.9734/BJMCS/2015/14611.
8. Babatunde Oluleye, Armstrong Leisa J, Leng Jinsong and Diepeveen Dean (2014). Zernike Moments and Genetic Algorithm: Tutorial and Application. British Journal of Mathematics & Computer Science. 4(15)
:2217- 2236.
9. Babatunde Oluleye, Armstrong Leisa J, Leng Jinsong and Diepeveen Dean (2014). A Genetic Algorithm- Based Feature Selection. International Journal of Electronics and Communication and Computer Engineering, IJECCE 5(4); 889-905.
10. Babatunde Hezekiah, Folorunso Olusegun, Akinwale Adio (2010): A Cellular Neural Networks-Based Model for Edge Detection: England, U.K Journal of Information and Computing Science, Vol.5, No.1 Pg.3-010. 11. Babatunde, H.O, Akanbi, C.O, Eludire, A.A, Fadare, O.G, Egbedokun, O.M, Aluko, O.B (2012): On Numer- ical Simulation of Boundary -Valued Neuronal Model: World J of Engineering and Pure and Applied Sci, Vol.2, No. 1, pg 20-25.
12. Babatunde Oluleye H (2014). Modelling, Simulation and Visualization of Heat Equation Dynamics. British Journal of Mathematics and Computer Science. 4(15), 2155-2169. 13. Babatunde Oluleye, Armstrong Leisa J, Leng Jinsong and Diepeveen Dean (2014). On The Application of Genetic Probabilistic Neural Networks and Cellular Neural Networks in Precision Agriculture. Asian Journal of Computer & Information Systems. 2(4); 90-100
14. Babatunde Oluleye, Armstrong Leisa J, Leng Jinsong and Diepeveen Dean (2014). Application of Cellu- lar Neural Networks and NaiveBayes Classifier in Agriculture. 9th Conference of the Asian Federation for Information Technology in Agriculture.
Professional Activities
• Reviewer: PLOS Computational Biology PlosCompBIO
• Reviewer: Journal of Advances in Mathematics and Computer Science. hrefhttp://www.journalrepository.org/media/ AsianFederationforInformationTechnologyinAgriculture(conference).[AFITA]
• Reviewer: The 2018 ACM Southeast Conference ”, Kenturcky, USA. ACMSE
• Teach coach: IBM regional Inter-collegiate programming contest (West-African, 2009).[ICPC]
• Reviewer: Machine Vision and Applications (MVAP) Awards
• Best Paper Award at 9th Conference of the Asian Federation for Information Technology in Agriculture, WA Australia (AFITA 2014).
• Top 10 Fresh Scientists in WA, Australia( FreshScienceWA)
• Edith Cowan University International Postgraduate Research Scholarship (ECUIPRS 2013) Award-Highly pres- tigious and competitive PhD scholarship.
• Industry and PhD Research Engagement Program of Western Australia (iprepWA 2015)
• Tertiary Education Trust Fund of Nigeria (TETF 2012): Training fund for scholars in higher instutitions. Professional Affiliations
• The Society for Mathematical Biology (Member ID: 32868931)
• Virginia commonwealth cyber initiative (since 2023 till date): URL:https://cyberinitiative.org/research/researcher- directory/babatunde-oluleye.html
• Upsilon Pi Epsilon [CSU Charleston Chapter] (Member ID:2018113468clssu)
• British Computer Society (Member ID: 990410678)
• Association for Computer Machinery (Member ID: 6577014)
• Australian Computer Society (Member ID 684934)
• Society for Industrial and Applied Mathematics, Philadelphia (001031435)
• Australian Society of Information and Communication Technologies in Agriculture (20121004)
• New Zealand Computer Society (NZCS) (Member ID: 164460)
• IEEE Student Member (Member ID: 92268741)
Extra-Curricular
• Animal documentaries, Children course and welfare, theology Referees
• Dr Ramoni Lasisi, Department of Computer Science, VMI, Virginia, USA [**********@*****.***; +1 540- 464-7495]
• Dr Jinsong Leng, Australia [ ***********@*****.***; +614*-***-****]
• Prof Dean Diepeveen, Department of Agriculture and Food, South Perth, WA, Australia [********@*****.***;
Contact this candidate