Teaching

Teaching Overview

ISAT 449: Emerging Topics in Applied Data Science (Lecture)

School of Integrated Sciences, James Madison University

Course Description:

This course will cover selected emerging topics in applied data science of interests (e.g., automation, data privacy and security, data science in the cloud, artificial neural network and deep learning, natural language processing, text mining). It will help students develop the meta-cognitive skills needed to become proficient in using and identifying new technologies (including programming languages, architectures, modalities, etc.) that may best contribute to solving a problem in an environment in which technologies are changing briskly. Prerequisite(s): ISAT 341 or permission of the instructor.

Semester(s): Fall 2026

GEOG 350/465: Topics in Geography — Quantitative Geospatial Thinking (Lecture)

School of Integrated Sciences, James Madison University

Course Description:

This course introduces students to quantitative geospatial thinking through data, maps, and spatial analysis. Students learn how to identify patterns, evaluate spatial variation, recognize clusters and “hot spots,” and distinguish meaningful geographic trends from random noise. The course emphasizes hands-on learning through problem solving, visualization, and practical exercises using quantitative reasoning and introductory computational tools.

Semester(s): Fall 2026

GEOG 469: Applications of Geographic Information Systems — Urban Analytics (Lecture)

School of Integrated Sciences, James Madison University

Course Description:

This course advances students’ knowledge of GIS in theory and practice through a focused application area: urban analytics. Students create and work with spatial databases and complex attribute data, and apply GIS modeling techniques to analyze problems relevant to urban systems and processes. The course emphasizes quantitative and computational approaches to urban analytics and data science, including large-scale urban data, urban morphology, mobility, networks, spatial interaction models, (spatial) regression, geodemographics, and smart cities.

Semester(s): Spring 2026

GEOG 367: Programming for Geographic Information Science (Lecture)

School of Integrated Sciences, James Madison University

Course Description:

Geographic information science relies on programming for effective geospatial analysis for large datasets and the automation of resource-intensive analytical methods. This course advances the knowledge of programming for geographic information systems. In addition to providing a solid foundation in Python programming language, the course introduces several libraries and applications that are commonly used for working with geospatial data in GIS software.

Semester(s): Fall, Spring 2026, Fall 2025

GEOG 215: Introduction to Geographic Information Science and Cartography (Lecture)

School of Integrated Sciences, James Madison University

Course Description:

This course introduces the fundamental principles of geographic information systems, including various data models and their spatial relationships. Students learn to make maps and to process and analyze spatial data. The course also explores the use of many types of geospatial data. Students learn how these data can be used to aid visualization and decision-making.

Semester(s): Fall 2025

GEO 211: Univariate Statistics in Geography (Lecture)

Department of Geography, University at Buffalo

Course Description:

Introduces probability as a measure of uncertainty. Addresses the use of such measures of uncertainty for describing data, and for making inferences about large populations from small samples. These descriptive and inferential aspects of statistics are illustrated using geographic examples from a wide variety of different fields.

Semester(s): Fall 2023

GEO 381: Cartography (Lab)

Department of Geography, University at Buffalo

Course Description:

Introduces fundamentals of computer cartography, which is the study and practice of making map representations of the Earth. Provides practical training in the techniques for the representation, manipulation and display of spatial data using computer software.

The laboratory course will assist students in furthering their understanding of cartography techniques for representing, manipulating, and displaying spatial data using computer software. The lab will provide students with exposure to various advanced cartography techniques and procedures including: data collection, cloud computing, map projection, map reading, map making, digitizing, classifying, symbolizing.

Semester(s): Spring 2025

GEO 211: Univariate Statistics in Geography (Lecture)

Department of Geography, University at Buffalo

Course Description:

Introduces probability as a measure of uncertainty. Addresses the use of such measures of uncertainty for describing data, and for making inferences about large populations from small samples. These descriptive and inferential aspects of statistics are illustrated using geographic examples from a wide variety of different fields.

Semester(s): Fall 2023

GEO 481/506: Geographical Information Systems (Lab)

Department of Geography, University at Buffalo

Course Description:

Introduction to the use of high-speed digital computers in geographic research. Topics include advanced programming, introductory machine architecture, large file handling and data base management systems, computer graphics and digitizing. Students are expected to complete a major applications programming project as part of the course requirement.

Semester(s): Spring 2022, Fall 2022, Spring 2023

Award:

• Excellence in Teaching Award, Department of Geography, UB

Computational Urban Analysis (Lab)

MSc Urban Science, Policy & Design, Singapore University of Technology & Design

Responsibility:

• Provided assistance to graduate students in practical programming lab
• Assisted and mentored students in groups and on an individual basis
• Evaluated students’ assignments together with the professor

Semester(s): Spring 2020

Research Methodology for Urban Analysis (Lab)

MSc Urban Science, Policy & Design, Singapore University of Technology & Design

Responsibility:

• Enhanced class productivity by providing assistance in class
• Discussed students’ questions with professor & mentored students in final projects

Semester(s): Fall 2019