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Departments

Computer Science & EngineeringFacilities

Network Systems Lab

This laboratory is dedicated to experiments described in the curriculum in the area of Networking and Programming. The lab is equipped with state-of-the-art components required for the completion of the lab cycle. A computer science workshop, which includes Python programming, is carried out in this lab. The Data Structure Lab and Graphics lab were supported with C programming. LEX and YACC compilers are used for doing Compiler Design Lab. It provides modern computational facilities to undergraduate students. The lab is also utilized for project-related work for final-year students. A wired network is provided to all computers in the lab. The Network Systems lab is implemented with a UPS backup system

Database and Multimedia Lab

Database lab is well equipped with modern systems to develop the knowledge on database and implementation using Oracle. The lab is also used to familiarise the students to implement and deploy web applications. C programming, Data structure and Compiler Design Experiments are also carried out in this lab. The lab is also utilised for project related works. All the systems in this lab are interconnected as well as backed up with UPS

Computer Hardware Lab

The main objective of the hardware lab is to provide the students with knowledge and working of the hardware devices used in the computer like motherboard, RAM, Processor, SMPS, different add-on cards and other peripherals like printers. Hardware Lab provides students hands on experience in computer hardware. C programming, Data structure and Compiler Design Cycles are also carried out in this lab. System level programming like MASM is also incorporated in this lab. The lab is also utilised for project related works. All the systems in this lab are interconnected as well as backed up with UPS

Research Lab / Embedded Systems lab

The Research Lab is a specialized facility designed to support cutting-edge research, innovation, and practical learning in computing and related technologies. These labs provide a collaborative space for students, faculty, and researchers to explore diverse areas such as artificial intelligence, machine learning, cybersecurity, data science, cloud computing, software engineering, and human-computer interaction. Equipped with high-performance computers, advanced software tools, simulation platforms, and dedicated servers, they enable the development and testing of algorithms, applications, and systems.
The lab’s activities often include conducting experiments, developing software prototypes, analyzing large datasets, and implementing novel computational models. Workshops, hackathons, and seminars are frequently organized to enhance practical knowledge and foster creativity. Faculty and students utilize the lab for academic projects, thesis work, and research publications, often collaborating with industry partners and leveraging government or private funding

Software Engineering Module

The lab focuses on equipping students with the knowledge and skills required to design, develop, test, and maintain high-quality software systems. It covers key concepts such as software development life cycles, requirements analysis, software design principles, coding practices, testing methodologies, and project management techniques. Students learn to apply engineering principles to solve complex software problems, often working on collaborative projects to gain hands-on experience. The module also emphasizes emerging trends like agile development, DevOps, and secure coding practices, preparing graduates for dynamic roles in the software industry.

Cyber Security Module

The lab is designed to provide students with a comprehensive understanding of protecting digital systems, networks, and data from cyber threats. It covers key areas such as network security, cryptography, ethical hacking, risk assessment, incident response, and secure software development. Students gain hands-on experience with tools and techniques for detecting vulnerabilities, preventing attacks, and ensuring system integrity. The module also emphasizes legal, ethical, and regulatory aspects of cybersecurity, preparing graduates to address the evolving challenges of the digital age and pursue careers as cybersecurity analysts, consultants, or engineers

Programming Lab

This lab is dedicated for the students to develop and enhance their coding skills through practical experience. Equipped with modern computers, programming software, and development tools, the lab provides an environment for learning various programming languages like C, Java, Python, and more. Students use the lab to write, debug, and test code, working on projects ranging from basic algorithms to advanced applications. The lab also supports collaborative learning, with instructors providing guidance and hosting activities like coding challenges and workshops. It plays a vital role in strengthening problem-solving abilities and preparing students for real-world software development tasks.

Data Analytics Lab

The Data Analytics Lab is designed to train students and researchers in analyzing and interpreting large datasets. It focuses on data preprocessing, statistical analysis, machine learning, data visualization, and predictive modeling, providing hands-on experience with real-world applications in fields like business intelligence, healthcare, and finance. The lab is equipped with high-performance computers for handling complex data processing, software tools like Python, R, Tableau, and Hadoop, and cloud platforms such as AWS or Google Cloud for scalable computation. It also includes database systems like MySQL and MongoDB, big data frameworks like Apache Spark, and AI libraries such as TensorFlow and Scikit-learn for implementing machine learning models. Advanced data visualization tools help students create interactive and meaningful representations of data. The lab prepares students for careers in data science and analytics by fostering practical skills and innovative problem-solving capabilities.

Artificial Intelligence Lab

The Artificial Intelligence (AI) Lab is a cutting-edge facility dedicated to exploring and advancing AI technologies. It provides students and researchers with the tools and resources to work on machine learning, deep learning, natural language processing, computer vision, robotics, and intelligent systems. Equipped with high-performance computing systems, GPUs, and AI development platforms like TensorFlow, PyTorch, and Keras, the lab enables the implementation and testing of complex AI models. It also offers access to datasets, simulation environments, and cloud computing services for scalable AI research. Students gain hands-on experience through projects, workshops, and collaborative research, addressing real-world challenges across various domains such as healthcare, autonomous systems, and smart cities. The AI Lab fosters innovation and prepares students for cutting-edge careers in the rapidly evolving field of artificial intelligence.

Machine Learning Lab

The Machine Learning (ML) Lab is a modern facility dedicated to advancing machine learning research and applications. It offers students and researchers access to powerful computing systems, GPUs, and frameworks like Scikit-learn, TensorFlow, and PyTorch. With resources such as extensive datasets, simulation platforms, and cloud services, the lab supports the development of advanced ML models. Through projects, workshops, and collaborations, students gain hands-on experience solving real-world challenges in areas like predictive analytics, natural language processing, and personalized medicine, preparing them for impactful careers in ML.

Neural Networks Lab

The Neural Networks Lab is a specialized facility focused on the study and development of neural network models and their applications. It provides students and researchers with cutting-edge tools, including high-performance GPUs, deep learning frameworks like TensorFlow, PyTorch, and Keras, and access to large datasets. The lab supports experimentation with architectures such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers. Students engage in hands-on projects and research addressing challenges in computer vision, speech recognition, natural language processing, and autonomous systems. The Neural Networks Lab fosters innovation and equips students with the skills to excel in the evolving field of deep learning and AI.

The Student Industry Connect Lab

The Computer Science and Engineering Department has established an industry-supported laboratory named “Keystone: The student Industry Connect” in collaboration with Key Value Software Systems, Kochi. The lab consists of high-end machines that will enable the students to work on projects using the latest technology that require intense and fast processing. Through the establishment of the laboratory, a stronger partnership has been established by the department with the industry. Industry-oriented projects and internship facilities are promoted through this initiative. The department endeavours to produce engineers who are well-equipped and industry-ready.

FIST Lab

The Fund for Improvement of S&T Infrastructure (FIST) lab is intended to provide basic infrastructure and enable facilities to promote R&D activities in new and emerging areas and attract fresh talent in universities & other educational institutions.

Department Library

The Library of Computer Science represents a comprehensive collection of 2432 books, including textbooks, reference books, seminar reports, and project reports that encompass the theories, principles, technologies, and methodologies used in the study and application of computers and computational systems. This library is both physical and digital, existing in textbooks, research papers, academic repositories, codebases, documentation platforms, and online learning environments.
The Library of Computer Science includes knowledge from several major domains:

  • Algorithms and Data Structures, Programming Languages, Computer Architecture, Operating Systems,Databases,and Information Systems.

 

The library is also equipped with textbooks related to the latest technologies in Computer Science, including Artificial Intelligence and Machine Learning, Data Science, and Data Analytics.

In the digital age, the library of computer science has expanded to include:

  • Online Databases: IEEE Xplore, SpringerLink, and ScienceDirect host peer-reviewed papers and conference proceedings.

We have a subscription to 98 Science–Direct Journals,240 Springer, and 210 IEEE journals