Teaching

I geenrally teach two courses each semester at Oklahoma State University. Please sign up for courses on the University website. If you have any specific questions about course topics, feel free to message my office, and a teaching staff member will respond as soon as possible.

CS 4153/5153 Mobile Applications Development

Semester: Spring

Offered: Every Spring

The history of mobile apps and their implication on computing in general. Survey of the various platforms and approaches used for mobile apps. Examine the differences between "conventional" programs and mobile apps. Learn tools and techniques to develop mobile apps, and demonstrate proficiency through development assignments. Must have access to computer running Mac OS.

CSXXXX: Responsible AI Development and Deployment in Healthcare

Semester: TBA

Offered: Expected Spring 2025

"Responsible AI Development and Deployment in Healthcare" is a core course in the online Master’s program because it addresses key technical, ethical, and regulatory challenges in the growing field of healthcare AI. It equips students to bridge the gap between AI development and its real-world application in clinical settings, ensuring they are prepared to contribute to AI initiatives across healthcare environments. The course complements other technical courses by providing a multidisciplinary approach and practical focus, while also building a foundation for advanced electives in AI ethics, healthcare data science, and machine learning.

This course provides a comprehensive exploration of the development, implementation, and management of AI systems in healthcare, with a special emphasis on ethical, regulatory, and human-centered considerations. As AI technologies become integral to modern healthcare, it is crucial to ensure that these tools are designed and deployed responsibly. The course will cover the technical foundations of AI/ML, explainable AI (XAI) models, and the challenges of data bias, security, and privacy specific to healthcare applications. Students will explore real-world examples of AI success and failure, analyze how bias can be introduced and mitigated through datasets and algorithms, and assess the ethical implications of deploying AI in clinical settings.

In addition, students will engage with critical concepts in human-centered AI design, ensuring that both clinicians and patients are part of the AI development process. Through case studies, and technical assignments, students will gain the skills to design, evaluate, and manage AI systems that support clinical decision-making, enhance patient care, and comply with regulatory standards. The course emphasizes the importance of transparency, accountability, and inclusivity in AI systems to build trust and improve healthcare outcomes.

CSXXXX: Bioinformatics

Semester: TBA

Offered: Expected Fall 2026

Computational Bioinformatics (CS-XXXX) is an interdisciplinary course for undergrdautes and graudaute students designed to provide students with a deep understanding of how computer science and biology intersect to drive discoveries in the biological sciences. This course empowers students with foundational knowledge and practical skills in bioinformatics, focusing on data-driven computational methods to analyze and interpret complex biological data.

Throughout the course, students will engage with advanced algorithms, data analysis techniques, and programming applications tailored for bioinformatics, gaining experience in topics such as genomic data analysis, sequence alignment, and molecular modeling. By exploring real-world bioinformatics challenges, students will build a skill set that aligns with industry demands, preparing them to make valuable contributions to fields like genomics, personalized medicine, and biotechnology.

CS1013: CS 1013 Principles of Computer Science

Semester: Fall

Offered: Every Fall

Computing as a creative human activity, abstraction to reduce detail and focus on concepts relevant to understanding and solving problems, describing data and information to facilitate the creation of knowledge, discuss algorithms as tools for developing and expressing solutions to computational problems, use programming is a creative process that produces computational artifacts; and discuss digital devices, systems, and the networks that interconnect them.