Gonsalge Almeida

Lecturer (Full-time), Department of Mathematics, Applied Mathematics, and Statistics

Case Western Reserve University
Office: Sears Library 569
Email: gsa19@case.edu
Phone: (216) 816-0342

Biography

I am a Lecturer in the Department of Mathematics, Applied Mathematics, and Statistics at Case Western Reserve University. In addition, I serve as an Adjunct Professor at Trine University and as an Adjunct Instructor at Stark State College. My teaching spans statistics, applied mathematics, business analytics, and data science across undergraduate, graduate, and doctoral programs.

At Case Western Reserve University, I teach STAT 312/312R (Basic Statistics for Engineering and Science) and MATH 201 (Introduction to Linear Algebra for Applications).

At Stark State College, I teach MTH124 and MTH024 (Mathematics Fundamentals and Statistics), serving multidisciplinary students in medical, health sciences, technical, and applied programs. These courses emphasize quantitative literacy, applied statistics, and real-world problem solving.

At Trine University, I teach BA6933 (Statistics and Quantitative Methods) in the MBA program, focusing on graduate-level statistical modeling, decision analysis, and business applications. I am also developing the online platform for RSH7033 (Applied Multivariate Statistics) for the DBA program, integrating multivariate methods with forecasting and advanced analytics in business contexts using Moodle.

I hold a Ph.D. in Applied Mathematics (concentration in Statistics) and have also pursued Ph.D.-level study in Mathematics (concentration in Statistics) at Central Michigan University. I have taught in the United States for more than 13 years. In all of my courses, I integrate real-world datasets, especially from finance, business, and data science, so that students develop modeling fluency, a strong grasp of statistical concepts and their visualization, computational literacy, and the ability to translate applied-mathematics concepts into practical tools for data science.

I also completed a Data Engineering Fellowship at The Data Incubator, focusing on practical machine-learning workflows, data engineering, and end-to-end analytics.

Areas of Interest

Statistical modeling and inference for finance and data science
Financial mathematics: Lévy processes, stochastic modeling, and risk analytics
Time series and predictive modeling for markets and operations
Applied probability and stochastic processes
Trading education: integrating Lévy processes into stochastic dynamic trading models (strategy design and risk management)

Teaching at CWRU

STAT 312/312R — Basic Statistics for Engineering and Science (with R practice)
MATH 201 — Introduction to Linear Algebra for Applications

Course pages, schedules, syllabi, and assignment repositories are linked from the Courses section of this site.

Teaching Philosophy

My approach is problem-driven and computation-forward. Students learn theory in tandem with practice: deriving results, implementing them in code, and validating conclusions with data. I emphasize clear communication of statistical evidence and ethical use of data. In STAT 312/312R, I align R assignments with Montgomery, Runger, and Hubele so that learners build both conceptual and computational mastery.

Education