Cornerstone Projects (CoPs)

Cornerstone projects designed for a single semester with a small team upto 2 students in the second or third year of their studies. Faculty can choose the students of their choice.

Cornerstone projects in each department are as follows:

• Computer Science and Engineering
• AI&ML
• Cyber Security
• Data Science
• Information Technology
• Electronics and Communication
• Electrical and Electronics
• Mechanical
• Civil

Computer Science and Engineering (CSE)

CSE cornerstone projects address contemporary issues in domains like software development, data science, artificial intelligence, cybersecurity, or web/mobile applications. By working on a cornerstone project, students gain practical exposure to the software development life cycle, project management, version control, and documentation. These projects form a vital part of a student’s academic portfolio and lay the groundwork for more advanced capstone or industry-based projects in later semesters.

AI&ML

AI&ML cornerstone projects allow students to apply the mathematical and statistical knowledge as well as principles of algorithms and data structures to solve real-world problems. ML project develops a range of skills, from data preprocessing and feature engineering to model building, evaluation, and tuning. These projects help students to understand how machine learning can be applied to various fields, such as healthcare, finance, and robotics. It involve working with large datasets, complex models, and intricate problem-solving processes. These projects often involve using modern libraries, frameworks, and technologies, such as TensorFlow, Keras, Matplotlib, PyTorch, and Scikit-learn.

Cyber Security

Cyber Security cornerstone projects focus on various aspects, from network security and malware analysis to incident response and threat intelligence. These projects can involve building tools, simulating attacks, or assessing vulnerabilities to improve security practices. This HIPs – cybersecurity project experience creates bigger opportunities in the industry.

Data Science

Data Science cornerstone projects typically involves using data analysis techniques, machine learning, and statistical methods to solve a real-world problem or gain insights from data. Projects can range from basic exploratory data analysis to complex predictive modelling.

Information Technology

Cornerstone projects in Information Technology (IT) are foundational, hands-on experiences that expose students to real-world IT challenges and practices. These projects, often undertaken in the early stages of a degree program, help students develop practical skills, project management capabilities, and a deeper understanding of the software development lifecycle. Examples include projects in Cloud, Databases and web/mobile applications.

Electronics and Communication

The Cornerstone Projects (CoPs) for Electronics and Communication Engineering span across key domains such as analog electronics, embedded systems, IoT, and FPGA-based digital design. Projects include the design of multi-output regulated DC power supplies with protection features, automatic LDR-based street lighting, and low-distortion audio amplifiers using BJT-MOSFET stages. Embedded applications involve thermistor-based temperature control systems, infrared burglar alarms, handheld metal detectors, and sound-responsive switching circuits. Digital system design projects emphasize FPGA implementations such as multifunctional clocks, traffic control systems using FSMs, and 4-bit synchronous up-down counters using VHDL/Verilog, bridging real-time control with hardware-level programming.

Electrical and Electronics

Cornerstone projects in Electrical and Electronics Engineering provide students and professionals with essential hands-on experiences, allowing them to apply theoretical knowledge to practical challenges across various engineering domains. These projects enhance technical proficiency, problem-solving skills, and innovation in areas like power systems, power electronics, control systems, embedded systems, and electrical machines. Power electronics projects emphasize efficient energy conversion and control techniques, particularly in electric vehicles and renewable energy applications. Control system projects involve the design and simulation of automation strategies, while embedded systems projects leverage microcontrollers and real-time operating systems for IoT applications.

Mechanical

Mechanical Engineering cornerstone projects blend core principles with emerging technologies like AI, ML, IoT, and automation to address real-world issues across domains. Design and Manufacturing projects utilize CAD/CAM, generative design, and predictive maintenance systems powered by ML. Mechatronics and Robotics involve smart systems, autonomous robots, and IoT devices using Arduino and AI control. Industrial Engineering and Thermal Engineering projects employ simulation, sensor-based IoT monitoring, and ML for efficient thermal management and energy systems.

Civil

Civil cornerstone projects apply engineering concepts with AI, IoT, and simulations to address real-world challenges in construction, transport, water systems, and structural monitoring.