Computer Science and Engineering
Computer Science and Engineering (CSE) at Indian Institute of Technology Palakkad offers undergraduate, postgraduate and research programs. The discipline offers a conducive environment for students to satisfy their intellectual appetite, and strives to impart knowledge across the depth and breadth of computer science and engineering. We build a strong foundation in our students and prepare them for pioneering roles in the industry and academia. The discipline currently offers an undergraduate program (B.Tech. in Computer Science and Engineering), three interdisciplinary postgraduate programs (M.Tech. in Computing and Mathematics, M.Tech. in Data Science, and M.Tech. in System-on-Chip Design), and two research programs (MS and PhD). The curricula introduces students to state-of-the-art technologies through well designed courses and encourages innovation through projects. The curriculum undergoes regular revisions to keep pace with the ever-changing needs of the community.
The faculty of the Computer Science and Engineering discipline have active collaborations with leading researchers across the world. There are also several ongoing research projects with leading industries and government agencies.
Areas of Research
Theoretical Computer Science - combinatorics, graph theory, algorithms, data structures, type theory, logic and complexity theory.
Faculty: Deepak Rajendraprasad, Jasine Babu, Krishnamoorthy Dinesh, Krithika Ramaswamy, Piyush P Kurur
Systems and Software - Computer Architecture, Operating Systems, Compilers and Programming Languages, Cyber Security, IoT, Distributed systems, High performance computing.
Faculty: Piyush P Kurur, Sandeep Chandran, Satyajit Das, Unnikrishnan Cheramangalath, Vivek Chaturvedi, Albert Sunny
Artificial Intelligence and Machine Learning - Kernel Learning, Multiview Learning, Optimization, Natural Language Processing, Information Retrieval, AI on Edge.
Faculty: Koninika Pal, Sahely Bhadra, Satyajit Das
Bachelor of Technology in Computer Science and Engineering - As a science, it is a way to look at the world through the lens of computation. As a branch of Engineering, it is a systematic approach to problem solving. We introduce state-of-the-art topics such as Artificial Intelligence early in our program and encourage students to innovate. Most of our courses have associated labs. This strengthens the theoretical understanding of our students and motivates them to tackle practical problems. Our program prepares students for both industry and higher education. We have an excellent placement record, and Our alumni have a strong presence in reputed Universities both in India and Abroad.
M.Tech in Computing and Mathematics (MCaM) offers a mix of computer science and mathematics courses that together cover the fundamentals of computation. The curriculum is designed to prepare students to pursue careers that require non-trivial applications of mathematics in computer science. Further details can be found at https://iitpkd.github.io/mcam/.
M.Tech in System on Chip Design (SoCD) is an interdisciplinary program that is jointly offered by the Computer Science and Engineering and Electrical Engineering disciplines. This program delves deep into various challenges faced, and techniques used to solve them, when designing and integrating various sub-systems into a chip. Further details can be found at https://iitpkd.github.io/msocd/.
Master of Science (by Research) and Ph.D. in Computer Science and Engineering are research-based programs that require students to push the frontiers of human knowledge through a thesis on a topic of their choice. The discipline hosts researchers who work on a wide range of areas such as Theoretical Computer Science, Intelligent and Collaborative Systems, Data Science, and Computer Systems.
Labs, Centres and Hubs
Centre for Research and Education in Data Science (CREDS): CREDS has been established jointly by faculty members from CSE, EE, CE, ME, MA, PHY, and HSE with the vision to provide world class education, pursue cutting edge research, and develop data science and artificial intelligence for the benefit of society. CREDS hosts a MTech program in Data Science in addition to training MS and PhD students. A major agenda of CREDS is to foster active industrial as well as academic collaborations.
Technology Innovation Hub on Intelligent Collaborative System (TIH-ICS): TIH-ICS has been established by National Mission on Interdisciplinary Cyber-Physical Systems (NM-ICPS) to create a strong foundation and a seamless ecosystem for CPS technologies by coordinating and integrating nation wide efforts encompassing knowledge generation, translation research, technology and product development, human resource development, innovation & commercialization standards and international collaborations. TIH-ICS is backed by faculty members from CSE, EE, ME, CE with expertise in various aspects of Cyber-physical systems.
Advanced Architecture Lab (AAL): This lab is set up to pursue research on various aspects of Computer architecture and design including research and development of novel system architectures, micro-architectural features, and design methodologies that are secure and energy-efficient in addition to achieving high-performance.
Centre for Computational Imaging (CCI): This central interdisciplinary center is engaged in pushing the frontiers in all aspects of imaging - sensing and image acquisition, processing and visualization, and acceleration. The center aims to synergize research across several layers of the computational system to identify new opportunities for improvements.
Lab for Advanced VLSI and Artificial Intelligence (LAVA): This lab is established jointly with faculty from EE to achieve excellence in IC design and research using the latest technology at the global level with state-of-the-art synthesis and simulation facilities. The goal in the future is to work towards setting up an IC design hub that develops in-house IP cores for IoT applications and to facilitate research in Artificial Intelligence for the entire spectrum of high performance computing to embedded platforms.
High Performance Computing Cluster: The Central High Performance Computing cluster consists of 64 compute nodes, each with a dual 12-core (2.2 GHz and 4 GB RAM) Intel processor.