This course is designed for senior undergraduate and graduate students in engineering, focusing on practical training for effective data collection and systematic analysis from manufacturing shop floors. It provides hands-on experience in real-time monitoring of equipment and processes using AI-based modeling techniques. Students work in groups of 2–3 and collaborate with small-to-medium-sized manufacturing enterprises in Indiana. Through these collaborations, students identify real-world challenges and develop Industrial IoT (IIoT)-based solutions.
In this course, I led a 10-week Machine Learning (ML) module (ML1–10), teaching students to analyze industrial data using Python and Colab. I provided hands-on guidance for developing AI models and mentored students on implementing IIoT solutions and ML-driven approaches to solve real-world manufacturing challenges as part of their industrial projects.
This course introduces mechanical engineering students to a wide range of data mining, machine learning (ML), and deep learning (DL) techniques, emphasizing both conceptual understanding and hands-on practice. I designed and developed comprehensive coding exercises using Python, tailored to bridge theoretical concepts with real-world applications in mechanical engineering. Additionally, I deployed challenges such as the "Data Challenge" and "ML/DL Challenge," providing students with opportunities to evaluate and demonstrate their skills in applying AI techniques to solve engineering problems.
This workshop provided professionals from various industries and research institutes with practical training on data analysis and AI application for improving productivity in industrial systems. I developed Python-based instructional materials and led hands-on sessions to guide participants in processing and analyzing data from industrial equipment.
This course provided professionals from energy-related organizations and companies, such as power plants, with training on understanding and analyzing data collected from their systems. I specifically designed and delivered instructional materials on analyzing mechanical and sensor data and applying AI modeling techniques.
This online summer course was attended by 400–500 students from various disciplines. I developed accessible instructional materials on data analysis and AI for non-engineering students with no prior coding experience. I conducted live-streamed and recorded hands-on sessions and actively supported students at different skill levels, enhancing their data engineering capabilities through tailored guidance and responsive interaction.
This workshop provided professionals from various industries and research institutes with practical training on data analysis and AI application for improving productivity in industrial systems. I developed Matlab-based instructional materials and led hands-on sessions to guide participants in processing and analyzing data from industrial equipment.
This course focused on the fundamental principles of designing mechanical components such as gears, shafts, and bearings, emphasizing their application in engineering systems. As a teaching assistant, I supported students by conducting supplementary tutorials, assisting with design projects, and providing feedback on assignments to help them master the concepts and practical aspects of machine element design.
This tutorial introduced participants to the fundamental concepts of Artificial Intelligence (AI) and its integration into smart factory systems. As an assistant instructor, I contributed to developing and delivering instructional materials, focusing on explaining key principles and technologies driving smart manufacturing innovations.
This capstone design course focused on guiding students through the process of conceptualizing, designing, and prototyping engineering solutions to real-world problems. As a Master Teaching Assistant, I led the design and management of diverse capstone projects over several years, mentored and trained other teaching assistants, and conducted multiple sessions to directly instruct and support students. My role emphasized fostering creativity, teamwork, and practical problem-solving skills in students.