For any information related to CSE-AIML & IoT, please contact aimliotadmissions@vnrvjiet.in

Department of CSE-AIML , IoT & Robotics and AI

The Department of CSE- Artificial Intelligence and Machine Learning (AIML) and Internet of Things (IoT) stands at the forefront of innovation, shaping a future that transcends boundaries and revolutionizes the way we interact with technology. The Department of CSE-AIML & IoT started in the year 2020, offers 2 UG courses namely B. Tech- CSE (AIML) and B. Tech-CSE (IoT). B. Tech-CSE (AIML) started with an intake of 60 students and eventually increased to 180 in 2021. Currently we are having an overall intake of 180 in AIML. B. Tech-CSE (IoT) has an intake of 60 students. The department also offers Minor programme in AIML and IoT for the circuit and non-circuit branches.

About the Department

At the core of this department, lies Artificial Intelligence (AI), the driving force behind groundbreaking breakthroughs in various fields. The department's relentless pursuit of AI excellence unlocks the potential to unravel complex problems and improve the efficiencies of the students to meet the industry needs. The department's expertise in machine learning drives the development of robust and adaptable models, empowering the students to unlock the untapped potential from various data assets. In synergy with AI and machine learning, the department embraces the transformative potential of the Internet of Things (IoT), which interconnects a myriad of devices, sensors, and systems. By seamlessly integrating the physical and digital worlds, IoT creates an intricate network of intelligent endpoints that generate a vast ocean of data. The department guides the students to harness the data generated through various devices, sensors and also work on real time datasets to unlock the new possibilities facilitating intelligent decision-making. The students are encouraged to work on real-time monitoring projects across diverse domains.

Vision

To emerge as an epicenter having transformative impact in the education and research of Artificial Intelligence & Machine Learning and Internet of Things with an ecosystem that contributes to the society through innovativeness and creativeness.

Mission

M1: To Impart innovative teaching and learning methodologies to generate knowledge through the state-of-the-art concepts and technologies in AI-ML and IoT with personal and professional responsibilities and commitment to lifelong learning with societal aspirations.

M2: To produce successful Computer Science and Engineering graduates with a specialization in AI-ML and IoT.

M3: To establish centers of excellence in leading areas of AI-ML and IoT in collaboration with industry to uplift innovative research and development.

Department of CSE- AIML & IoT strives to create an ecosystem that not only excels in education and research but also actively contributes to the society through innovation and creativity. The primary goal is to pursuit excellence in education and research by creating solutions that address global challenges. The faculty members within the department are highly skilled and well-versed in their respective fields, acting as valuable resources in seminars, faculty development programs, conferences and delivering invited talks. With certifications in Artificial Intelligence and Machine Learning from renowned institutions such as IIIT Hyderabad, they bring a wealth of expertise to the table. By staying up to date on the latest trends and developments, they ensure that their teaching methodologies and curriculum remain relevant and aligned with industry standards. The faculty's commitment to continuous learning and professional development enables them to provide the students with valuable exposure to real-world scenarios and industry best practices, bridging the gap between academia and industry.

In summary, our department is driven by a motto that prioritizes experiential learning through hands-on training, course-based projects, interdisciplinary projects, research projects and summer internships. By integrating experiential learning into our curriculum, students gain valuable practical skills that complement their theoretical knowledge. The interdisciplinary environment fosters an exchange of ideas, promotes collaboration, and nurtures a culture of continuous learning, ensuring that the department remains at the forefront of global AI and IoT advancements.

Department of B. Tech CSE (Artificial Intelligence & Machine Learning)

Programme Educational Objectives (PEOs):

  1. PEO-1: Analyze, design, and implement solutions to the chosen field of profession for a successful career.(Professional accomplishment)
  2. PEO-2: Pursue higher education for professional development or career paths in research. (Continuing Education)
  3. PEO-3: Function effectively in the workplace with demonstrable attributes like leadership, lifelong learning, work with teams towards the accomplishment of society needs with ethical responsibility. (Attitudes)
  4. PEO-4: Adapt, contribute, and innovate new technologies with good soft skills to become successful entrepreneurs.

Programme Specific Outcomes (PSOs):

On successful completion of the program, the graduates of B. Tech CSE (Artificial Intelligence & Machine Learning) will be able to:

  1. PSO-1: Apply the knowledge of Artificial Intelligence & Machine Learning principles to solve complex engineering problems which are cost effective and find appropriate solutions to build and design intelligent systems.
  2. PSO-2: Monitor and adopt to consistently changing Artificial Intelligence & Machine Learning landscape for futuristic challenges to meet specific needs of the society
  3. PSO-3: Understand, design, and implement the concepts of Artificial Intelligence & Machine Learning to build intelligent models and systems that are meeting industry 4.0 standards with ethical values.

Program Outcomes (POs):

The graduates of B. Tech CSE (Artificial Intelligence & Machine Learning) will be able to:

  1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
  2. 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.
  3. 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.
  4. 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 for complex problems.
  5. 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.
  6. 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.
  7. 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.
  8. Ethics:Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
  9. Individual and team work: : Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
  10. 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.

Department of B. Tech CSE (Internet of Things)

Programme Educational Objectives (PEOs):

  1. PEO-1: Practice the engineering skills in the profession of Internet of Things (IoT) to identify and solve contemporary problems. (Foundation)
  2. PEO-2: Exhibit leadership capability with ethical and professional behavior through a lifelong learning attitude. (Lifelong Learning)
  3. PEO-3: Promote Design, Research and Entrepreneurial skills to Support the growth of country economy. (R&D and Entrepreneur)

Programme Specific Outcomes (PSOs):

On successful completion of the program, the graduates of : B. Tech CSE (Internet of Things) will be able to:

  1. PSO-1: Understand the fundamental concepts of Computer Science & Engineering with specialization in IoT and aligned mezzanine technologies.
  2. PSO-2: Design and Integrate hardware and software systems in the areas of IoT with a strong emphasis on lifelong learning to create feasible engineering solutions
  3. PSO-3: Analyze, Design, Implement, Test and Deploy smart applications related to industry and research for the advancement of society.

Program Outcomes (POs):

The graduates of B. Tech CSE (Internet of Things) will be able to:

  1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
  2. 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.
  3. 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.
  4. 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 for complex problems.
  5. 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.
  6. 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.
  7. 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.
  8. Ethics:Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
  9. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
  10. 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.
  11. 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.
  12. 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.

Department of B. Tech CSE (ROBOTICS AND ARTIFICIAL INTELLIGENCE)

Programme Educational Objectives (PEOs):

  1. PEO-1: To provide graduates with a strong foundation in core engineering principles, mathematics, and computing sciences, enabling them to pursue successful careers in the fields of Robotics, Artificial Intelligence, and Automation.
  2. PEO-2: To enable graduates to apply advanced knowledge in AI, Machine Learning, and Control Systems to design, develop, and implement intelligent and autonomous robotic solutions for complex industrial, commercial, and research challenges.
  3. PEO-3: To equip graduates with the skills to engage in lifelong learning, pursue higher studies, and undertake research and development in emerging technological areas like Deep Learning, Generative AI, and advanced robot kinematics.
  4. PEO-4: To instill the qualities of leadership and entrepreneurship in graduates, preparing them to manage projects, innovate, and create new ventures in the technology sector, while working effectively in multidisciplinary teams.
  5. PEO-5: To ensure graduates practice their profession with a commitment to professional ethics, societal responsibility, and environmental sustainability, recognizing the global impact of Robotics and AI technologies.

Programme Specific Outcomes (PSOs):

  1. PSO-1: Graduates will be able to formulate, analyze, design and develop robotic systems using sensors, actuators, embedded systems and control strategies for real world applications.
  2. PSO-2: Graduates will be capable of integrating hardware and software to create semi- autonomous and autonomous robotic solutions, emphasizing innovation, safety and sustainability.
  3. PSO-3: Graduates will be able to develop intelligent systems by incorporating advanced contemporary technologies like Generative AI, Agentic AI and Artificial General Intelligence.

Program Outcomes (POs):

  1. 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.
  2. Problem Analysis: Identify, formulate, review research literature and analyze complex engineering problems reaching substantiated conclusions with consideration for sustainable development. (WK1 to WK4).
  3. 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).
  4. 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).
  5. Engineering Tool Usage: Create, select and apply appropriate techniques, resources and modern engineering & IT tools, including 5 prediction and modelling recognizing their limitations to solve complex engineering problems. (WK2 and WK6).
  6. 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)
  7. Ethics: Apply ethical principles and commit to professional ethics, human values, diversity and inclusion; adhere to national & international laws. (WK9).
  8. Individual and Collaborative Team work: Function effectively as an individual, and as a member or leader in diverse/multi-disciplinary teams.
  9. 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.
  10. 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.
  11. Life-Long Learning: Recognize the need for, and have the preparation and ability for i) independent and life-long learning ii) 6 adaptability to new and emerging technologies and iii) critical thinking in the broadest context of technological change. (WK8).
S.No Name of the Faculty Designation Profiles Joining Date Qualification Nature of Association E-mail JNTUH ID
1 Dr Sandhya N Prof & RDC Head 19-06-2014 Ph.D Regular sandhya_n@vnrvjiet.in 14150402-120027
2 Dr Sagar Yeruva Assoc.Prof & HOD 23-05-2012 Ph.D Regular sagar_y@vnrvjiet.in 16150407-122941
3 Dr Rayudu Manjula Sri Professor 08-12-1998 Ph.D Regular manjulasree_r@vnrvjiet.in 58150405-142724
4 Dr Kousar Nikhath Alpuri Associate Professor 20-06-2007 Ph.D Regular kousarnikhath@vnrvjiet.in 3415-0405-102222
5 Dr Malige Gangappa Associate Professor 27-09-2000 Ph.D Regular gangappa_m@vnrvjiet.in 75150406-222443
6 Dr Bandari Jalender Associate Professor 23-09-2008 Ph.D Regular jalender_b@vnrvjiet.in 3119-150408-102555
7 Dr Awari Harshavardhan Sr.Assistant Professor 27-03-2021 Ph.D Regular harshavardhan_a@vnrvjiet.in 1958-150417-101629
8 Dr Kakumani Aruna Kumari Assistant Professor 02-01-2007 Ph.D Regular arunakumari_k@vnrvjiet.in 30150404-203404
9 Dr Gujjeti Nagaraju Assistant Professor 24-05-2011 Ph.D Regular nagaraju_g@vnrvjiet.in 8924-150407-231234
10 Apparasu Adithya Kashyap Assistant Professor 27-06-2011 M.Tech Regular adithyakashyap_a@vnrvjiet.in 4360-150408-213505
11 Mannepalli Venkata Krishna Rao Assistant Professor 01-10-2012 M.Tech Regular venkatakrishnarao_cse@vnrvjiet.in 1036-161214-171157
12 Dr Dasari SriLaxmi Assistant Professor 14-03-2016 Ph.D Regular srilaxmi_d@vnrvjiet.in 8927-160314-171553
13 Dr Kunka Bheemalingappa Assistant Professor 14-11-2016 Ph.D Regular bheemalingappa_k@vnrvjiet.in 6678-161119-152720
14 Dr Challabotla Naveen Reddy Assistant Professor 02-01-2017 Ph.D Regular naveenreddy_ch@vnrvjiet.in 3702-160307-012243
15 Dr Chalumuru Suresh Assistant Professor 05-01-2017 Ph.D Regular suresh_ch@vnrvjiet.in 6575-160227-133435
16 Dr Sayeedakhanum Pathan Assistant Professor 30-03-2021 Ph.D Regular sayeedakhanum_p@vnrvjiet.in 9812-160201-105457
17 Kancharagunta Kishan Babu Assistant Professor 29-04-2022 M.Tech Regular kishanbabu_k@vnrvjiet.in 7603-220518-151322
18 Bhupesh Deka Assistant Professor 20-08-2022 M.Tech Regular bhupesh_d@vnrvjiet.in 3172-220719-162334
19 Preety Singh Assistant Professor 07-09-2022 M.Tech Regular preety_s@vnrvjiet.in 8664-160112-104621
20 Korukonda Naga Durga Saile Assistant Professor 21-11-2022 M.Tech Regular nagadurgasaile_k@vnrvjiet.in 9639-150409-134549
21 Kakumanu Sreenivasa Rao Assistant Professor 30-12-2022 M.Tech Regular sreenivasarao_k@vnrvjiet.in 8430-230109-231226
22 Jakkula Sravanthi Assistant Professor 04-03-2022 M.Tech Regular sravanthi_j@vnrvjiet.in 3383-160307-153908
23 Rajulapati Sudha Assistant Professor 01-06-2022 M.Tech Regular sudha_r@vnrvjiet.in 5285-200307-152714
24 Rudra Yamini Rani Assistant Professor 12-08-2022 M.Tech Regular yaminirani_r@vnrvjiet.in 2028-160227-153135
25 Shaik Mabasha Assistant Professor 13-02-2023 M.Tech Regular mabasha_sk@vnrvjiet.in 8218-230217-103759
26 Dr Kalidindi Archana Assistant Professor 12-04-2023 Ph.D Regular archana_kalidindi@vnrvjiet.in 85150330-135618
27 Dr Yavanamandha Prasanthi Assistant Professor 21-08-2023 Ph.D Regular prasanthi_y@vnrvjiet.in 49150330-141115
28 Etikala Gurumohan Rao Assistant Professor 01-09-2023 M.Tech Regular gurumohan_e@vnrvjiet.in 04150404-115423
29 Vorem Kishore Assistant Professor 18-10-2023 M.Tech Regular kishore_v@vnrvjiet.in 0485-200229-130713
30 Venkannagari Manjula Assistant Professor 02-11-2023 M.Tech Regular manjula_v@vnrvjiet.in 7420-120412-131817
31 Manthena Swapna Kumari Assistant Professor 08-11-2023 M.Tech Regular swapnakumari_m@vnrvjiet.in 7406-220125-161509
32 Ravula Jyothsna Assistant Professor 08-11-2023 M.Tech Regular jyothsna_r@vnrvjiet.in 8690-150413-163035
33 Yellanki Veda Sahiti Assistant Professor 22-11-2023 M.Tech Regular sahiti_y@vnrvjiet.in 9624-150409-144855
34 Muthyala Mehar Sharanya Assistant Professor 09-02-2024 M.Tech Regular meharsharanya_m@vnrvjiet.in 2323-240218-010538
35 Kothakonda Akhila Tejaswini Assistant Professor 12-02-2024 M.Tech Regular akhilatejaswini_k@vnrvjiet.in 0421-240214-111828
36 Chilukuri Divya Assistant Professor 14-02-2024 M.Tech Regular divya_c@vnrvjiet.in 9678-240208-122556
37 Kapu Prathyusha Assistant Professor 15-02-2024 M.Tech Regular prathyusha_k@vnrvjiet.in 5913-240214-163718
38 Bappanna Bhagyashree Assistant Professor 08-05-2024 M.Tech Regular bhagyashree_b@vnrvjiet.in 3750-240629-151738
39 Dr Sayanti Chatterjee Assistant Professor 01-08-2024 Ph.D Regular sayanti_ch@vnrvjiet.in 4506-181120-142944
40 Koneru Anitha Assistant Professor 17-10-2024 M.Tech Regular anitha_k@vnrvjiet.in 1654-241125-142725
41 Uppara Veeresh Assistant Professor 21-12-2024 M.Tech Regular veeresh_u@vnrvjiet.in 6790-161210-155930
42 Nelluru Anjaneyulu Assistant Professor 27-09-2024 M.Tech Regular anjaneyulu_n@vnrvjiet.in 8945-240130-160732
43 Dr Koganti Nishanth Professor of Practice 01-03-2024 Ph.D Regular nishanth_k@vnrvjiet.in
44 Dr Jasthi Kiran Assistant Professor 02-01-2024 Ph.D Regular kiran_j@vnrvjiet.in 7663-191108-101534
45 Marlapudi Shara Lydia Assistant Professor 12-02-2025 M.Tech Regular sharalydia_m@vnrvjiet.in 53150402-131929
46 Kanchari Bavajigari Anusha Assistant Professor 29-05-2025 M.Tech Regular anusha_kb@vnrvjiet.in 6904-211211-091606
47 Manjusha Nambiar Assistant Professor 16-07-2025 M.Tech Regular manjusha_n@vnrvjiet.in 5439-230414-123740
48 Dondeti Sowmya Chowdary Assistant Professor 01-08-2025 M.Tech Regular sowmyachowdary_d@vnrvjiet.in
49 Potnuru Lakshmi Prasanna Assistant Professor 28-11-2025 M.Tech Regular lakshmiprasanna_p@vnrvjiet.in 2445-251129-150744
50 Kondepati Anusha Assistant Professor 28-11-2025 M.Tech Regular anusha_k@vnrvjiet.in 2031-151223-235004
51 Pandula Sujatha Assistant Professor 28-11-2025 M.Tech Regular sujatha_p@vnrvjiet.in 4563-251129-155509
52 Kolli Veena Assistant Professor 05-12-2025 M.Tech Regular veena_k@vnrvjiet.in 8662-210312-180219
53 N Jaya Sri Assistant Professor 28-01-2026 M.Tech Regular jayasri_n@vnrvjiet.in 3722-230421-135126
54 Vaidehi Ramadugu Assistant Professor 13-02-2026 Masters Regular vaidehi_r@vnrvjiet.in

NON-Teaching Staff

S.No Name of the Staff Designation E-Mail ID
1 Ms Birru Sandhya Computer Operator sandhya_aiml@vnrvjiet.in
2 Mrs Bollampalli Pravalika JCP pravalika_aiml@vnrvjiet.in
3 Mrs Sunkam Navya Computer Operator navya_aiml@vnrvjiet.in
4 Mrs. H. Sulekha Computer Operator sulekha_admin@vnrvjiet.in
5 Mrs. T. Divya Bharathi JCP divyabharathi_aiml@vnrvjiet.in
6 Mrs. Kasa Manasa JCP manasa_aiml@vnrvjiet.in
7 Mrs. Naru Jahnavi JCP jahnavi_aiml@vnrvjiet.in
8 Mrs. Yegupati Ragini JCP ragini_aiml@vnrvjiet.in
9 Mrs. Devineni Prathyusha JCP prathyusha_aiml@vnrvjiet.in
10 Mr. T. Ganesh JCP ganeshkumar_aiml@vnrvjiet.in
11 K.Sri Meghala JCP srimeghala_aiml@vnrvjiet.in

Alumni

Placement and Higher Education