B.Tech Specialization | AICTE Approved
CSE (Artificial Intelligence & Machine Learning)
The Department of CSE (Artificial Intelligence & Machine Learning) at SVS is a specialized center of excellence dedicated to the most transformative technologies of the 21st century. Affiliated with JNTU Hyderabad, this program is designed to create engineers who can build autonomous systems, design predictive models, and lead the global shift toward intelligent automation.
To be a renowned department for education in Artificial Intelligence and Machine Learning in Telangana State, moulding students into professional engineers.
- Impart rigorous training to generate knowledge through individual concepts and technologies in Artificial Intelligence and Machine Learning.
- Mould students to become technically competent through innovation and leadership.
- Instill values of professional ethics, social responsibility, environmental protection, and lifelong learning.
- Establish Centers of Excellence in leading areas of computing and artificial intelligence.
🤖 HOD’s Message
Welcome to the Future of Intelligence
Welcome to the Department of Artificial Intelligence and Machine Learning at SVS. It is a pleasure to have you join a community where your curiosity meets the most transformative technology of our time. My primary goal is to provide you with a supportive and inspiring environment where you do not just study algorithms, but learn to harness them to solve real-world human problems.
Our curriculum is meticulously designed to take you from the mathematical foundations of data to the cutting edge of cognitive computing. We focus on a purpose-driven education, where you will master predictive modeling, neural networks, and natural language processing through hands-on projects and laboratory immersion.
We believe that true expertise is built when technical mastery is guided by strong ethical values, ensuring that the intelligence you build today creates a safer and more inclusive world tomorrow.
At SVS, we are deeply committed to your personal and professional growth. This course is more than a degree; it is a journey toward becoming a visionary who can turn vast data into meaningful action. I am excited to support you as you develop the skills to innovate, disrupt, and lead in this fast-evolving landscape.
Together, let us architect the intelligent systems of the future.
Dr. [Name]
Professor & Head, Department of Artificial Intelligence and Machine Learning
Faculty – AI & Machine Learning
| S.No | Name of the Faculty | Designation | Qualification |
|---|
| 1 | RANJITH GYADERLA | Associate Professor | Ph.D |
| 2 | SINGARAPU SUNIL | Assistant Professor | M.Tech |
| 3 | PRANEETH KUMAR MULPUR | Associate Professor | M.Tech |
| 4 | RAJANIKAR GANTA | Assistant Professor | M.Tech |
| 5 | PERUMANDLA AJAY TEJA | Assistant Professor | M.Tech |
| 6 | DEEKSHITH BURUGULA | Assistant Professor | M.Tech |
| 7 | BANDI NAGA RAJU | Assistant Professor | M.Tech |
| 8 | KAVVA SANDYA | Assistant Professor | M.Tech |
| 9 | KODIPAKA VENKATESHWAR RAO | Assistant Professor | M.Tech |
| 10 | CHIGURU APARNA | Assistant Professor | M.Tech |
| 11 | CHIRRA PRIYANKA | Assistant Professor | M.Tech |
| 12 | CHIRRA SHARATH | Assistant Professor | M.Tech |
| 13 | NIKHAT FARHANA | Assistant Professor | M.Tech |
| 14 | SWETHA GATLA | Assistant Professor | M.Tech |
| 15 | NANDINI REPALLY | Assistant Professor | M.Tech |
| 16 | SARESH KUMMARI | Assistant Professor | M.Tech |
| 17 | BHAVANI KRUPA BOGA | Assistant Professor | M.Tech |
| 18 | DARSHINI KOTHA | Assistant Professor | M.Tech |
| 19 | MANOJ KUMAR BANDARI | Assistant Professor | M.Tech |
| 20 | SWETHA BANDARI | Assistant Professor | M.Tech |
| 21 | SWATHI PANJALA | Assistant Professor | M.Tech |
| 22 | SUJITH KUMAR LONE | Assistant Professor | M.Tech |
| 23 | BANGARI KOMALA | Assistant Professor | M.Tech |
| 24 | AREMAN SAI KRISHNA LAL | Assistant Professor | M.Tech |
| 25 | MAMIDALA SRINIVAS TEJA | Assistant Professor | M.Tech |
| 26 | HARISH THUMMA | Assistant Professor | M.Tech |
| 27 | P SAGAR | Assistant Professor | M.Tech |
Program Educational Objectives (PEOs)
PEO1: Implement appropriate theories, practices, and tools to provide effective solutions for multidisciplinary challenges.
PEO2: Function effectively in the workplace, demonstrating professional competence and continuous professional growth.
PEO3: Adapt, contribute, and innovate new technologies in key domains of Artificial Intelligence and Machine Learning during higher studies and product development.
Program Outcomes (POs)
PO1: Engineering Knowledge
Apply knowledge of mathematics, science, engineering fundamentals, and specialization to solve complex engineering problems.
PO2: Problem Analysis
Identify, formulate, review literature, and analyze complex problems using first principles.
PO3: Design/Development of Solutions
Design solutions for complex problems considering public health, safety, cultural, societal, and environmental aspects.
PO4: Investigations of Complex Problems
Use research-based methods including design of experiments, data analysis, and information synthesis for valid conclusions.
PO5: Modern Tool Usage
Create, select, apply appropriate techniques and modern engineering tools including prediction and modeling.
PO6: Engineer and Society
Apply contextual knowledge to assess societal, health, safety, legal, cultural issues and responsibilities.
PO7: Environment and Sustainability
Understand impact of engineering solutions and demonstrate commitment to sustainable development.
PO8: Ethics
Apply ethical principles and commit to professional ethics, responsibilities, and norms.
PO9: Individual and Teamwork
Function effectively as an individual and as a member/leader in diverse and multidisciplinary teams.
PO10: Communication
Communicate effectively on complex engineering activities through reports, presentations, and documentation.
PO11: Project Management and Finance
Demonstrate knowledge of management principles and apply them to manage projects in multidisciplinary environments.
PO12: Life-long Learning
Recognize the need for independent and lifelong learning to adapt to rapid technological change.
Program Specific Outcomes (PSOs)
Apply core concepts of Artificial Intelligence and Machine Learning, including Data Structures, Database Systems, Operating Systems, Networking, and Intelligent Systems to solve futuristic and complex problems.
Implement automated solutions for real-world problems through laboratory experiments, projects, and internships.
🚀 AICTE Approved | Affiliated to JNTU Hyderabad | Center of Excellence in AI&ML
The CSE (AI&ML) program at SVS blends rigorous academics with hands-on AI/ML labs, industry projects, and research-driven learning — producing engineers ready to lead the intelligent automation revolution.
