- EAMCET/ECET/ICET CODE: VMEG
CSE AIML ENGINEERING
Department of Computer Science and Engineering (Artificial Intelligence & Machine Learning)
Department of Computer Science and Engineering (Artificial Intelligence & Machine Learning)
The Department of Computer Science and Engineering (AI & ML) at Vardhaman College of Engineering is supported by a team of highly qualified, experienced, and research-oriented faculty dedicated to academic excellence and innovation. The faculty possess expertise in core and emerging areas such as Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Gen-AI, Computer Vision, and Natural Language Processing, and contribute actively through research publications, patents, and academic activities. Through effective teaching, research mentorship, industry interaction, and project guidance, the department focuses on developing technically competent, ethically responsible, and industry-ready graduates with strong analytical, programming, and problem-solving skills to address real-world challenges and contribute to advancements in Artificial Intelligence and Machine Learning.
Professor & HOD
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Programmer
DTP Operator
The Department of Computer Science and Engineering (Artificial Intelligence & Machine Learning) has constituted various committees to ensure effective academic planning, quality enhancement, and smooth functioning of departmental activities. These committees focus on curriculum implementation, research and innovation, industry interaction, student development, and continuous improvement. Through their coordinated efforts, the department strives to maintain academic excellence and align its programs with emerging technologies and industry requirements in the field of AI and Machine Learning.
The Department Advisory Committee (DAC) of the CSE (Artificial Intelligence & Machine Learning) department acts as a strategic body that guides the continuous growth and development of the program. It comprises Senior Faculty Members, Industry Experts, Alumni, and Academic professionals with expertise in Artificial Intelligence, Machine Learning, and related computing domains. The committee periodically reviews the department’s academic progress, curriculum relevance, laboratory facilities, and research activities in emerging AI technologies. Through valuable recommendations, the DAC helps strengthen teaching–learning practices, promote innovative research, enhance industry collaboration, and improve students’ technical skills and employability in the evolving field of AI and Machine Learning.
The Program Assessment and Quality Improvement Committee (PAQIC) of the CSE (Artificial Intelligence & Machine Learning) department is responsible for monitoring and enhancing the quality of the academic program. The committee reviews Program Outcomes (POs), Program Educational Objectives (PEOs), and Course Outcomes (COs) through systematic assessment and evaluation. Based on outcome analysis and academic performance, it recommends improvements in curriculum, teaching–learning methods, and academic processes. The committee ensures continuous quality improvement and aligns the program with outcome-based education practices and accreditation requirements such as NBA and NAAC, while maintaining relevance to emerging trends in AI and Machine Learning.
The Board of Studies (BoS) of the CSE (Artificial Intelligence & Machine Learning) department is responsible for designing, reviewing, and updating the curriculum in line with academic advancements, industry requirements, and regulatory guidelines such as AICTE/JNTUH. The board comprises Head of the Department (Chairman), Internal Faculty Members along with External Experts from Academia and Industry. It ensures that the curriculum remains relevant, outcome-oriented, and aligned with emerging technologies in Artificial Intelligence and Machine Learning, thereby preparing students for professional careers and higher education opportunities.
The Curriculum Committee of the CSE (Artificial Intelligence & Machine Learning) department works in coordination with the Board of Studies to design, review, and implement the academic curriculum. It focuses on course structure, content relevance, credit distribution, and the integration of practical and skill-based learning in areas such as Artificial Intelligence, Machine Learning, and Data Science. The committee ensures that the curriculum promotes interdisciplinary learning, innovation, and industry readiness while effectively achieving the program outcomes.
The Project Review Committee of the CSE (Artificial Intelligence & Machine Learning) department supervises and evaluates student projects at different stages of development. It ensures that projects are innovative, technically robust, and aligned with emerging technologies in Artificial Intelligence and Machine Learning. The committee conducts periodic reviews to monitor progress, provide technical guidance, and ensure proper implementation and documentation, thereby helping students develop high-quality projects with strong practical and research relevance.