Teaching

My teaching integrates fundamentals, computational thinking, and real-world context—aiming to help students develop intuition, problem-solving confidence, and transferable skills.

Teaching philosophy

Principles that guide course design, classroom engagement, and assessment.

I view teaching as a process of enabling students to connect theory with physical intuition and practical relevance. My approach emphasizes clarity of fundamentals, structured problem-solving, and the use of computational tools to explore complex engineering behavior. I aim to create an inclusive learning environment where students are encouraged to ask questions, make informed assumptions, and learn through iteration.

Courses taught

Representative courses taught or assisted at the undergraduate and graduate levels.

  • Research Methodology — scientific method, literature review, research design, and communication skills
  • Waste Management for Material Engineers — waste management principles, recycling processes, and sustainability in materials engineering
  • Material Software Tool Lab — introduction of various software tools used in metallurgy and computational materials science
  • Mechanics of Materials — stress–strain behavior, failure theories, and material response
  • Introduction to Finite Element Analysis Lab — fundamentals of discretization, boundary conditions, and interpretation
  • Biomechanics - Assistant — mechanical principles applied to biological systems
  • Advanced Heat Transfer - Assistant — conduction, convection, radiation, and numerical approaches

Mentoring and supervision

Student guidance in coursework, projects, and research-oriented activities.

I have mentored undergraduate and graduate students through coursework, computational projects, and research-focused activities. My mentoring style emphasizes goal-setting, clear expectations, and iterative feedback, helping students develop both technical competence and professional confidence.

Pedagogical interests

Areas of focus in teaching innovation and curriculum development.

  • Integration of computation and simulation in core engineering courses
  • Use of real data and case studies to reinforce theoretical concepts
  • Project-based learning and open-ended problem formulation
  • Bridging mechanics, materials science, and data-driven methods