My research program bridges two lines of inquiry: (1) the neurobiology of affect and stress-related psychopathology and (2) discipline-based education research (DBER) focused on how emerging AI tools—especially generative AI—reshape learning, assessment, and instructional design in analytics-oriented business education. In my earlier and ongoing biomedical work, I investigate neural and immunological mechanisms underlying anxiety and affective disorders, with emphasis on risk factors that influence onset and persistence (e.g., inflammation, genetic predisposition, circadian disruption, and microbiome development). A major focus has been the role of the serotonin system in the production and maintenance of psychopathology. Using a range of experimental paradigms—including anxiogenic pharmacology, knock-out models, circadian disruption, and neurodevelopmental models—I have quantified expression changes in key serotonin-related genes and examined how immunoregulatory and anti-inflammatory interventions may prevent or attenuate maladaptive affective outcomes. A current priority is characterizing microbiome–host interactions that drive these molecular changes, including how microbiome perturbations influence gene expression and related behavioral phenotypes. My current educational research examines evidence-based integration of AI in teaching and learning. My current work with DBER focuses on how generative AI can support students’ analytical reasoning, feedback-seeking, and skill transfer—while also assessing risks (overreliance, inequities, privacy, and academic integrity). This work includes designing and evaluating AI-enabled instructional interventions (e.g., structured prompt literacy, and course-specific assistants)
keywords
Serotonin, psychopathology, microbiome, anxiety, depression, therapy, AI teaching, AI use
Teaching
courses taught
BAIM 4065 - Leadership in a Digital Age
Primary Instructor
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Summer 2021
In the digital age, leaders have to orchestrate radical redesign of everything from their internal processes to their business model on an ongoing basis. This requires leaders to adopt new approaches to leadership and new behaviors. This course provides students with the skills required in identifying business opportunities, finding appropriate information related technologies and leading innovation efforts to success. Formerly MGMT 4065.
BCOR 1025 - Statistical Analysis in Business
Primary Instructor
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Spring 2020 / Spring 2021 / Spring 2022 / Summer 2022 / Spring 2023 / Summer 2023 / Spring 2024 / Summer 2024 / Spring 2025 / Summer 2025 / Spring 2026
Covers sampling concepts, graphical and numerical data summaries, basic probability theory, discrete and continuous probability models, sampling distributions, hypothesis testing, correlation and both simple and multiple regression analysis. Students learn decision making and solving business problems by using data. Uses statistical features of Excel. Course requirements: laptop with Microsoft Excel; iClickers.
BCOR 2202 - Principles of Management
Primary Instructor
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Spring 2024
Focuses on the fundamentals of management from an organizational behavior perspective. Students will learn the basic concepts and best practices in the behavioral sciences that can improve their abilities to lead and manage in organizations. Frameworks for individual, team, and organizational behavior are presented and discussed. Topics include personality traits, culture, decision making, teams, planning, motivation, leadership, and well-being. A semester-long team project provides practice in teamwork and in applying the course concepts.
BCOR 2205 - Introduction to Management Information Systems
Primary Instructor
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Fall 2020 / Spring 2021 / Fall 2021 / Fall 2022 / Fall 2023 / Fall 2024 / Summer 2025 / Fall 2025
Focuses on the fundamentals of managing information in a data driven business environment. Students will learn the basic concepts and best practices in Information Management that can improve their abilities to lead and manage in organizations. The class teaches cutting-edge tools and approaches to the analysis of data, including "big data," for effective decision-making.It creates data connoisseurs through hands-on exposure to supervised machine learning. Application areas covered include human resources, marketing, finance, and supply chain. At the end of class, all students should be able to formulate common business problems in terms addressable through machine learning, and use automated machine learning tools to conduct the analysis and present deep insights to business leaders. Course requirements: clickers. Credit not granted for this course and BCOR 2500.
BUSM 3010 - Product Development I
Primary Instructor
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Spring 2021 / Fall 2021 / Spring 2022 / Fall 2022 / Spring 2023
Examines structures that support organizational innovation and change. Focuses on effective teamwork and tools needed during new product development to improve success. Degree credit not granted for this course and BUSM 3001.
IPHY 3415 - Human Anatomy Laboratory
Primary Instructor
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Spring 2018 / Fall 2018
Introduces structures of the human anatomical systems using human cadavers and animal tissue. This laboratory is meant to complement IPHY 3410. All registration restrictions will be strictly enforced by the department.
NRSC 2100 - Introduction to Neuroscience
Teaching Assistant
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Spring 2019
Provides an introduction to fundamental concepts in neuroscience. The goal of this first course is to provide a strong foundation in neurobiology-cell biology, physiology of the neuronal membrane, interneuronal communication, neurotransmission, gross anatomy, and how the brain develops. Students will also learn principles of sensory systems functions. Recitation will reinforce lecture concepts through discussion of current research.
