Main Content

Department of CSE – Artificial Intelligence & Machine Learning
About Us

Department of Artificial Intelligence and Machine Learning

Introduction

The Department of Artificial Intelligence and Machine Learning (AI & ML) is committed to imparting quality education and fostering innovation in the rapidly evolving fields of intelligent systems and data-driven technologies. The department aims to equip students with strong theoretical foundations and practical skills required to design, develop, and deploy intelligent solutions for real-world problems.

The Department encourages students to attend various events from various colleges and conferences. Training our students for the campus placements.

The curriculum is structured to cover core areas such as Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Natural Language Processing, Computer Vision, and Robotics, along with strong fundamentals in mathematics, programming, and computer science. Emphasis is placed on hands-on learning through laboratories, projects, internships, industry collaborations, and research activities.

The department encourages students to develop analytical thinking, problem-solving abilities, and ethical awareness while working with emerging technologies. With a dedicated team of experienced faculty members, modern computing facilities, and industry-oriented teaching practices, the AI & ML department strives to produce competent professionals, innovators, and researchers who can contribute effectively to academia, industry, and society.

Vision

To groom with foundational knowledge and practical skills to develop intelligent systems that can analyze data, make predictions, and solve complex problems.

Mission

  • To provide a comprehensive understanding of AI and ML theories, algorithms, and tools aligned with industry standards.
  • Provide hands-on learning opportunities through projects, labs, and real-world problem-solving.
  • Emphasize the importance of ethical considerations and responsible use of AI/ML technologies in societal and industrial contexts.

Programme's PEO's, PSO's and PO's

Program Educational Objectives (PEO)

  • PEO1: Apply their technical competence in computer science to solve real world problems, with technical and people leadership.
  • PEO2: Conduct cutting edge research and develop solutions on problems of social relevance.
  • PEO3: Work in a business environment, exhibiting team skills, work ethics, adaptability and lifelong learning.

Program Outcomes (POs)

  • PO1: Engineering Knowledge: Apply knowledge of mathematics, natural science, computing, engineering fundamentals and an engineering specialization as specified in WK1 to WK4 respectively to develop to the solution of complex engineering problems.
  • PO2: Problem Analysis: Identify, formulate, review research literature and analyze complex engineering problems reaching substantiated conclusions with consideration for sustainable development. (WK1 to WK4)
  • PO3: Design/Development of Solutions: Design creative solutions for complex engineering problems and design/develop systems/components/processes to meet identified needs with consideration for the public health and safety, whole-life cost, net zero carbon, culture, society and environment as required. (WK5)
  • PO4: Conduct Investigations of Complex Problems: Conduct investigations of complex engineering problems using research-based knowledge including design of experiments, modelling, analysis & interpretation of data to provide valid conclusions. (WK8).
  • PO5: Engineering Tool Usage: Create, select and apply appropriate techniques, resources and modern engineering & IT tools, including prediction and modelling recognizing their limitations to solve complex engineering problems. (WK2 and WK6)
  • PO6: The Engineer and The World: Analyze and evaluate societal and environmental aspects while solving complex engineering problems for its impact on sustainability with reference to economy, health, safety, legal framework, culture and environment. (WK1, WK5, and WK7).
  • PO7: Ethics: Apply ethical principles and commit to professional ethics, human values, diversity and inclusion; adhere to national & international laws. (WK9)
  • PO8: Individual and Collaborative Team work: Function effectively as an individual, and as a member or leader in diverse/multi-disciplinary teams.
  • PO9: Communication: Communicate effectively and inclusively within the engineering community and society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations considering cultural, language, and learning differences
  • PO10: Project Management and Finance: Apply knowledge and understanding of engineering management principles and economic decision-making and apply these to one's own work, as a member and leader in a team, and to manage projects and in multidisciplinary environments.
  • PO11: Life-Long Learning: Recognize the need for, and have the preparation and ability for i) independent and life-long learning ii) adaptability to new and emerging technologies and iii) critical thinking in the broadest context of technological change. (WK8)

Program Specific Outcomes (PSOs)

  • PSO1: Exhibit design and programming skills to build and automate business solutions using cutting edge technologies.
  • PSO2: Strong theoretical foundation leading to excellence and excitement towards research, to provide elegant solutions to complex problems.
  • PSO3: Create, select and apply the theoretical knowledge of AI and Data Analytics along with practical industrial tools and techniques to manage and solve wicked societal problems.

Faculty

S.No Name of the Staff Designation Qualification
1 Mr. C. Cyrilraj Assistant Professor M.E.
2 Mrs. J. Sophia Assistant Professor M.E.
3 Mr. M. Vivek Kumar Assistant Professor M.E.
4 Mrs. P. Subalakshmi Assistant Professor M.E.
5 Mrs. B. Saranya Assistant Professor M.E.
6 Mrs. L. Shobana Assistant Professor M.E.

Facilities

Infrastructure Facilities

  • Total Number of Classrooms: 08
  • Tutorial Hall: 01
  • Seminar Hall: 01
  • Laboratories: 08
  • Faculty Cabin: 25

Events

Image
Introduction To AWS Cloud

Department of AIML Organising on 20th August, 2025.

Read More
Image
Power BI for Intelliegence: Transforming Data into Insights.

Department of AIML Organising on 07th July, 2025.

Read More
Image
Recent Trends in Artificial Intelligence

Department of AIML Organising on 20th August, 2025.

Read More

Placements

Projects

Sl.No Academic year Course/Semester Total number of projects Project Details / View
1 2024-2025 Classification of Project (2024-2025) 33
2 BATCH 2024 CS8811 - PROJECT WORK 29
3 BATCH 2023 CS8811 - PROJECT WORK 29
4 2020-2021 CS6811 Project Work / VIII 24
5 2019-2020 CS6811 Project Work / VIII 28
6 2018-2019 CS6811 Project Work / VIII 08
7 2017-2018 CS6811 Project Work / VIII 12

Gallery

Alumni's Feedback