Innovative Teaching Methods

Flipped Classroom

Flipped Classroom Session

Student-Centered Learning Approach

In our flipped classrooms, students review lecture materials at home through videos and readings, while classroom time is dedicated to discussions, problem-solving, and hands-on activities with faculty guidance.

Key Benefits:
  • Increased student engagement and participation
  • More personalized instruction time
  • Better preparation for practical sessions
  • Flexible learning pace for students
Students Discussing Concepts

Interactive Learning Sessions

Classroom time transforms into active learning spaces where students collaborate on projects, engage in peer instruction, and clarify concepts with faculty through targeted discussions.

Implementation:

Problem-Based Learning (PBL)

PBL Session

Real-World Problem Solving

Students work in small groups to investigate and solve complex, real-world problems, developing critical thinking and practical engineering skills through guided discovery.

Key Features:
  • Authentic, industry-relevant problems
  • Development of research and analysis skills
  • Enhanced teamwork and communication
  • Integration of multiple knowledge areas
PBL Teamwork

Structured Learning Process

Our PBL approach follows a structured cycle of problem analysis, self-directed learning, solution development, and reflection, guided by faculty facilitators.

Process Steps:
  • Problem identification and analysis
  • Knowledge gap identification
  • Self-directed research
  • Solution proposal and evaluation

Project-Based Learning

Student Project

Hands-On Engineering Projects

Students engage in semester-long projects that require them to design, build, and test solutions to real engineering challenges, applying theoretical knowledge to practical scenarios.

Project Teamwork

Industry-Aligned Projects

Many projects are developed in collaboration with industry partners, ensuring relevance to current technological needs and providing students with professional experience.

Learning Outcomes:
  • Practical application of concepts
  • Project management skills
  • Technical documentation
  • Presentation and demonstration skills
  • Prototype/Product Development

Field-Based Learning

Industry Visit

Industry Visits and Internships

Regular visits to industries and research organizations complement classroom learning, exposing students to real-world applications and current industry practices.

Activities Include:
  • Industrial facility tours
  • Equipment demonstrations
  • Interaction with professionals
  • Summer internship programs
Field Work

Community Engagement Projects

Students apply their technical skills to solve local community problems through field projects that address real needs while developing social responsibility.

Recent Projects:
  • Bael Tea Production as a Potential Rural Empowerment Solution

Research Repository

Open-Source Research Materials

Promoting reproducible research through open datasets, code, and documentation from our experimental works.

TU-RTN is an Octave (MATLAB) program which can be used to generate RTN waveforms using results from TCAD tool based on semiconductor devices.

D. Deb, R. Goswami and R. K. Baruah, "Random Telegraph Noise Due to Dielectric-Semiconductor Interface Traps in MOS Transistors," in IEEE Transactions on Dielectrics and Electrical Insulation. https://doi.org/10.1109/TDEI.2024.3491672.

FlatB is an open source tool which can be used for accurate computation of flatband voltage in MOS capacitor using user-defined constants, functions and discrete values.

Hazarika, P., Ray, M., Hazarika, A. et al. Flatband voltage in MOS structures for spatial fixed oxide charge distributions. Journal of Material Science: Materials in Electronics 34, 1242 (2023). https://doi.org/10.1007/s10854-023-10626-0

In this project I intend to develop a python script to be use as an automatic web scraper of any google search result. It is an interesting project and most importantly very common application in the field of data science.

Bhabesh Deka, Debarun Chakraborty

This repository mainly contain the necessary python code for algorithms required to understand the basic of Image and video processing

Bhabesh Deka, Debarun Chakraborty