Department of CSE (Artificial Intelligence & Machine Learning)
The Department of Computer Science and Engineering (Artificial Intelligence & Machine Learning) was established in 2020 to equip students with cutting-edge knowledge and skills in the rapidly evolving fields of Artificial Intelligence (AI), Machine Learning (ML), Deep Learning and Data Science (DS).
The Department offers B.Tech programs in CSE (AI&ML) and B.Tech in AI&ML, carefully designed to provide a strong foundation in AI-driven technologies. Artificial Intelligence (AI) and Machine Learning (ML) are two fast-emerging sectors of technology that have acquired prominence in the undergraduate program curriculum. B.Tech CSE in AI & ML provides unlimited opportunities for students to learn and explore the fascinating world of intelligent machines.
B.Tech in CSE(AI&ML) is best suited for students who are seeking to build world-class expertise in Artificial Intelligence and Machine Learning. The curriculum include courses on programming, algorithms, data structures, computer networks, database management, and operating systems. In addition, the program educates them on emerging areas of AI and ML topics such as data mining, Neural Networks, Computer Vision, NLP, Deep Learning and many more. This helps the students to stand apart in the fellow graduates and grow careers in the upcoming technological era.
With a strong research-oriented approach, industry partnerships, and a future-focused curriculum, the Department of CSE (AI&ML) is dedicated to shaping the next generation of AI professionals and thought leaders. The department is dedicated to societal well-being through its impactful social outreach program, wherein high school students receive foundational training in computer literacy. This initiative aims to bridge the digital divide, empowering young minds with essential technological skills for a brighter future.
Graduates in CSE (AI&ML) have many career prospects such as Artificial Intelligence Engineer, Machine Learning Engineer, Deep Learning Engineer, Big Data Engineer, Research Scientist, AI Data Analyst, Robotics Scientist, etc. Leading giants likeApple, Amazon, Google, Facebook, Microsoft, Deepmind, Cognizant, Capgemini, Ernst & Young, HCL Technologies are currently among the top recruiters hiringgraduates with skills in AI and ML with a salary package ranging from 8 Lakhs to 50 Lakhs annually.
Labs
- 6 B.Tech. Labs with high end systems
Equipment
- Acer, Lenovo dual core, i3 and i5 desktops with LED monitors
- Access to all major cloud service providers (including EC2, Azure)
- LCD projectors
- HP LaserJet printers
Software
- All Microsoft software (through Microsoft Imagine subscription)
- All Oracle software (through Oracle Academy membership)
- Various flavors of Linux
Faculty, CSE (DS)
Dr. S. V. Suryanarayana, M.Tech., Ph.D.
Professor & HoD
Dr. N. Satyanarayana, M.Tech., Ph.D.
Professor
Dr. LNC Prakash K, M.Tech., Ph.D.
Associate Professor
Dr. A. Srinivasa Reddy, M.Tech., Ph.D.
Associate Professor
Dr. Varaprasad Rao M, M.Tech., Ph.D.
Associate Professor
Dr. Rama Krishna B, M.Tech., Ph.D.
Associate Professor
Dr. Shaik Janbhasha, M.Tech., Ph.D.
Associate Professor
Dr. Basavaraj Chunchure, M.Tech., Ph.D.
Associate Professor
Dr. M. Sreenu, M.Tech., Ph.D.
Associate Professor
Mrs. A Srichandana, M.Tech.
Sr. Assistant Professor
Mrs. S. Vineela Krishna, M.Tech.
Sr. Assistant Professor
Mr. Ahmed Shahebaaz, M.Tech.
Sr. Assistant Professor
Dr. Annapurna Gummadi, M.Tech., Ph.D.
Sr. Assistant Professor
Dr. Yasmeen, M.Tech., Ph.D.
Sr. Assistant Professor
Mrs. E. Nitya, M.Tech.
Sr. Assistant Professor
Mrs. P. Padma, M.Tech.
Sr. Assistant Professor
Mr. P. Hari Shankar, M.Tech.
Sr. Assistant Professor
Mr. K. Harish Kumar, M.Tech.
Sr. Assistant Professor
Mr. K. S. Ranadheer Kumar, M.Tech.
Sr. Assistant Professor
Ms. S. Lalitha, M.Tech.
Assistant Professor
Mrs. P. Nagarani, M.Tech.
Assistant Professor
Mr. S. Balakrishna Reddy, M.Tech.
Assistant Professor
Mrs. M. Nikita, M.Tech.
Assistant Professor
Mr. Prashanth Donda, M.Tech.
Assistant Professor
Mr. V. Ramesh, M.Tech.
Assistant Professor
Ms. Arava Nagasri, M.Tech.
Assistant Professor
Mrs. M. Srivani, M.Tech.
Assistant Professor
Mrs. T. Ramya, M.Tech.
Assistant Professor
Mr. V. Praveen Kumar, M.Tech.
Assistant Professor
Mrs. B. Sabitha, M.Tech.
Assistant Professor
Mr. Moghal. Yaseen Pasha, M.Tech.
Assistant Professor
Mrs. Afreen Fatima Mohammed, M.Tech.
Assistant Professor
Mr. Erugu Krishna, M.Tech.
Assistant Professor
Mrs. V. Swathi, M.Tech.
Assistant Professor
Mr. K. Ravikiran Reddy, M.Tech.
Assistant Professor
Vision
To evolve as a Center of Excellence in emerging areas, impart quality education to produce ethical, motivated and skilled professionals to meet the ever-increasing technological & social challenges.
Mission
M1: To impart students with self-discipline, hard work, all-round personality development and creative problem-solving approach.
M2: To provide quality-education by using the latest infrastructure and nurturing collaborative culture.
M3: To provide students an opportunity to learn both foundational and experimental components in emerging areas.
M4: To promote and nurture the spirit of innovation and entrepreneurship in our students.
M5: To emerge as a Center of Excellence through Research, Consultancy and Development Activities.
Program Educational Objectives (PEOs)
PEO 1: Graduates will acquire capability to apply their knowledge and skills to solve various kinds of computational engineering problems.
PEO 2: Graduates will exhibit the ability to apply the acquired skills in various domains and multi-disciplinary areas, to function ethically and meet the ever-increasing technological and social challenges.
PEO 3: To evolve as resourceful engineers catering to dynamic industrial needs and engage in life-long learning.
PEO 4: Graduates will acquire soft skills to adapt and excel in diverse global environment.
Program Specific Outcomes(PSOs)
- Make critical evaluation of the theories, techniques, tools and systems that are used to build data science based solutions in different domains.
- Apply analytic techniques and algorithms (including statistical, data mining, machine learning, Artificial Intelligence and soft computing approaches) to large data sets to extract meaningful insights by using relevant software tools, languages, data models, and environments for data analysis and visualization.
- Formalize data analysis problems in terms of the underlying statistical and computational principles and then provide technological pipeline to ingest, stage, transform and design solutions to the problems encountered in industry or academia.
- Interpret results of analysis, assess their credibility and communicate the results effectively (visually and verbally) to a broad audience within an organization.
Program Outcomes(POs)
PO1 - Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
PO2 - Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
PO3 - Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.
PO4 - Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
PO5 - Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
PO6 - The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
PO7 - Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
PO8 - Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
PO9 - Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
PO10 - Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
PO11 - Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
PO12: Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.