Teaching
My teaching portfolio includes undergraduate and graduate courses in measurements and instrumentation, system modeling, control systems, robotics, engineering economics, senior design, mechatronics, mechanical design, computer-aided engineering, and graduate research. Across these courses, I emphasize the integration of engineering theory, computational tools, hands-on experimentation, and real-world problem solving. My teaching approach connects mathematical modeling, simulation, hardware implementation, data acquisition, and engineering design so that students can develop both conceptual understanding and practical skills.
Instructor @ Miami University
MME 305: Measurements and Instrumentation
Measurements and Instrumentation introduces students to the fundamental principles and practical applications of engineering measurement systems, instrumentation, and experimental methods. The course covers sensors and transducers, signal conditioning, uncertainty analysis, calibration, data transmission, data acquisition systems, and computer-controlled measurement. Students learn how physical quantities such as displacement, force, pressure, temperature, strain, acceleration, and electrical signals can be measured, processed, and interpreted in engineering applications.
The course emphasizes both theory and hands-on laboratory experience. Students work with MATLAB, LabVIEW, Arduino, sensors, and data acquisition hardware to design and implement measurement systems for real-time monitoring and control. Through laboratory activities, students develop practical skills in experimental setup, sensor selection, data collection, signal processing, troubleshooting, and technical reporting. The course prepares students to apply instrumentation principles in industrial, research, and mechatronic system environments.
MME 321: System Modeling, Analysis, and Control
System Modeling, Analysis, and Control introduces students to the process of developing mathematical models of physical systems and using those models to understand, analyze, and control system behavior. Students learn to formulate governing equations for mechanical, electrical, thermal, fluid, and electromechanical systems using fundamental engineering principles. These models are then represented using differential equations, transfer functions, block diagrams, and state-space methods.
The course emphasizes time-domain and frequency-domain analysis, transient response, steady-state behavior, stability, system performance, and controller design. Students use computational tools such as MATLAB and Simulink to simulate dynamic systems, evaluate system response, and design basic controllers. By the end of the course, students develop a strong foundation for analyzing complex engineering systems and improving performance through feedback control.
MME 341: Engineering Economics
Engineering Economics prepares students to make informed financial decisions in engineering projects, product development, manufacturing, infrastructure, and technology management. The course introduces students to the time value of money, cash-flow analysis, present worth, annual worth, future worth, rate of return, benefit-cost analysis, payback period, and decision-making among multiple alternatives.
Students also study inflation, depreciation, taxes, replacement analysis, risk, uncertainty, and sensitivity analysis. Microsoft Excel is used extensively for engineering economic calculations, spreadsheet modeling, and scenario evaluation. The course helps students connect technical design decisions with economic feasibility, cost effectiveness, and long-term project value.
MME/ECE 436/536: Control of Dynamic Systems
Control of Dynamic Systems provides an in-depth study of mathematical modeling, analysis, and controller design for dynamic engineering systems. Students develop models for mechanical, electrical, electromechanical, and other physical systems using first-principles modeling and system identification concepts. The course covers transfer functions, block diagrams, state-space representation, transient response, stability analysis, root locus, frequency response, and performance specifications.
A major focus of the course is feedback controller design. Students learn how proportional, proportional-derivative, proportional-integral, and proportional-integral-derivative controllers can be designed and tuned to achieve desired closed-loop performance. MATLAB, Simulink, and LabVIEW are used for simulation, analysis, controller implementation, and laboratory experiments. The course prepares students for advanced work in robotics, mechatronics, automation, and dynamic system control.
MME 438/MME 538: Mechanics, Analysis, and Control of Robots
Mechanics, Analysis, and Control of Robots provides a comprehensive introduction to robotic systems with emphasis on kinematics, dynamics, trajectory planning, and control. Students study coordinate transformations, homogeneous transformation matrices, forward and inverse kinematics, Jacobian analysis, velocity relationships, manipulator dynamics, and robotic motion control. The course connects theoretical robotics concepts with practical applications in industrial automation, autonomous systems, and human-interactive robots.
Students use MATLAB and Simulink to model robotic manipulators, simulate motion, analyze dynamic behavior, and evaluate control strategies. The course emphasizes both mathematical rigor and engineering application, helping students understand how robotic systems are designed, analyzed, and controlled for accurate and reliable performance.
MME 448/449: Senior Design Capstone
The Senior Design Capstone is a culminating engineering experience in which students apply their technical knowledge to real-world design problems. Students work in teams to identify needs, define engineering requirements, generate concepts, perform analysis, build prototypes, conduct testing, and present final design solutions. The course emphasizes the complete engineering design process from problem definition to validation.
Students develop important professional skills including teamwork, project management, technical communication, design documentation, budgeting, engineering ethics, and interaction with faculty or industry mentors. The capstone experience serves as a bridge between academic training and professional engineering practice.
MME 700: Research for Master’s Thesis
Research for Master’s Thesis is a graduate-level course focused on independent, faculty-guided research in mechanical or manufacturing engineering. Students conduct research aligned with their thesis objectives, including literature review, problem formulation, theoretical development, computational modeling, experimental design, data analysis, and technical writing.
The course supports the development of advanced research skills and prepares students to produce a formal Master’s thesis. Students are expected to demonstrate critical thinking, methodological rigor, scholarly communication, and the ability to contribute original or applied knowledge to their field of study.
MME 704: Non-Thesis Project
Non-Thesis Project is a graduate-level course for students pursuing a project-based Master’s degree in mechanical or manufacturing engineering. The course involves applied research, engineering analysis, product development, system design, simulation, experimentation, or an industry-relevant technical project under faculty supervision.
Students integrate graduate-level engineering knowledge to address practical challenges and produce a professional technical report or presentation. The course emphasizes problem solving, technical documentation, communication, and the ability to apply advanced engineering concepts to real-world applications.
Instructor @ University of Wisconsin–Milwaukee
Computational Tools for Engineers — ME 101
Computational Tools for Engineers introduced students to MATLAB and Simulink as essential tools for engineering computation, modeling, and simulation. Students learned MATLAB programming fundamentals, including variables, arrays, matrices, built-in functions, user-defined functions, logical operations, loops, symbolic mathematics, plotting, and graphical user interface development.
The course emphasized computational thinking and problem solving for engineering applications. Students completed practical exercises involving numerical calculations, dynamic system simulation, data visualization, and algorithm development. The course helped students build a foundation for using computational tools in later engineering courses and professional practice.
Mechanical Design I — ME 360
Mechanical Design I provided instruction in the modeling, analysis, and synthesis of mechanical systems and mechanisms. Students studied four-bar linkages, six-bar linkages, cam-follower systems, gear trains, motion analysis, and dynamic force analysis. The course emphasized how mechanical components and mechanisms are designed to achieve desired motion and force transmission.
Students applied analytical methods and engineering software tools to solve mechanism design problems. The course helped students develop practical design skills, improve their understanding of machine motion, and prepare for more advanced mechanical design and machine system analysis.
Computer-Aided Engineering Laboratory — ME 370
Computer-Aided Engineering Laboratory provided hands-on training in engineering drawing, solid modeling, assembly modeling, mechanism simulation, and finite element analysis. Students used Creo/Pro-Engineer to develop three-dimensional models, create assemblies, generate engineering drawings, and analyze mechanical components.
The course emphasized practical design and analysis skills needed in modern engineering practice. Students learned how computer-aided engineering tools support product development, design communication, mechanism evaluation, and structural analysis.
Control and Design of Mechatronic Systems — ME 479
Control and Design of Mechatronic Systems introduced students to the principles and methods used to develop integrated mechatronic systems. The course covered microcontroller programming, sensor-actuator interfacing, signal conditioning, calibration, data acquisition, embedded control, and system integration. Students worked with analog and digital sensors, communication protocols, and electromechanical actuators.
Topics included temperature, humidity, force, torque, infrared, light, and sound sensors; I2C and SPI communication; PCB design; solenoids; DC motors; stepper motors; servo motors; AC circuit control using microcontrollers; Wi-Fi modules; oscilloscopes; signal generators; and controller interfaces. Students also gained hands-on experience developing low-cost data acquisition systems and visualization interfaces using MATLAB apps or LabVIEW graphical programming.
Teaching Assistant @ University of Wisconsin–Milwaukee
As a teaching assistant at the University of Wisconsin–Milwaukee, I supported laboratory instruction, recitations, grading, student mentoring, and hands-on engineering learning activities. My teaching assistant experience strengthened my ability to explain technical concepts, guide students through laboratory and computational assignments, and support student learning in core mechanical engineering and mechatronics courses.
- Control and Design of Mechatronic Systems — ME 479
- Introduction to Control Systems — ME 474
- Basic Heat Transfer — ME 321
- Basic Engineering Thermodynamics — ME 301