Introduction
Artificial intelligence (AI) is wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. The field of artificial intelligence has been an interdisciplinary endeavor, requiring deep knowledge of both computational and human sciences. Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.
Advancements in machine learning and deep learning are creating a paradigm shift in virtually every sector of the tech industry. Moreover, the growing impact of AI on society demands that graduates are capable and ethical collaborators, able to ensure the safe and effective adoption of new technologies across domains.
The program begins with introductory courses in programming, computer science, mathematics, and statistics that provide a firm technical foundation. From there, learn core AI concepts and techniques including AI & ML Techniques, Virtual Reality, Web Applications using Machine Learning Techniques, Natural Language and Image Processing, Robotic Process Automation, Business Analytics, Speech Processing, Cognitive systems, Biometrics Systems, computer vision, and language understanding. The program includes a variety of advanced AI electives, enabling technical mastery in specific subfields. Also, specific electives are introduced that will focus on the Application of AI in various industry.
Labs and Practicals
- Data Structures Lab, Algorithms Lab
- Micro-controller and Embedded Systems Lab
- AI and Machine Learning Lab
- Web Applications Lab
- Natural Language and Image Processing Lab
- Mobile Application Development & Robotics Lab
- Internet of Things Lab
Vision
To create well groomed, technically competent and skilled AIML professionals who can become part of industry and undertake quality research at global level to meet societal needs.
Mission
- Provide state of art infrastructure, tools and facilities to make students competent and achieve excellence in education and research.
- Provide a strong theoretical and practical knowledge across the AIML discipline with an emphasis on AI based research and software development.
- Inculcate strong ethical values, professional behaviour and leadership abilities through various curricular, co-curricular training and development activities.
Program Educational Objectives (PEOs)
- Graduates will follow logical, practical and research-oriented approach for solving the real world problems by providing AI based solutions.
- Graduates will work independently as well as in multidisciplinary teams at workplace.
- Graduates will setup start-up and become successful entrepreneurs.
Program Specific Outcomes (PSOs)
The graduates of AIML department will be able to
- Train machine learning models to address real life challenging problems using acquired AI knowledge.
- Develop applications using ML techniques related to the field of medical, agriculture, defence, education and various scientific explorations.
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
Course Outcomes (COs)
2018 Scheme Click Here
Department Advisory Board
- Puneet Mittal, Associate Professor & HoD, Chairperson
- M S Ganesha Prasad, Principal, Member
- Shreekumar, Associate Professor, CSE
- Rajesh Kamath, Assistant Professor, ISE
- Radha E G, Assistant Professor, Member
- Shruthi Kotekar, Adjunct Faculty & Industry Expert, Member
- Narendra VG, Associate Professor Department of Computer Science & Engineering, MIT, Manipal, Academic Expert
- Kavyashree Kotekar, Glowtouch Technologies, Mangalore, Industry Expert
- Prarthana Bhat, CSE-2011, Sr. Data Scientist, GSK, Alumni Representative
Faculty
Mr. Sunil Kumar S.
Educational qualification
BE – Computer Science and Engineering
M.Tech – Software Engineering
Pursuing Ph.D in Computer Science and Engineering (Wireless Sensor Networks)
Total experience
10 Years 6 Months
Area of Interest
- IoT
- Data Analytics
Professional Memberships
ISTE
Subjects Handled
- Big Data Analytics
- DBMS
- Computer Network
- Storage Area Network
- Information Network Security
- Data Mining
- Software Engineering
- File Structures
- 8086 Microprocessor
- Wireless Ad Hoc Networks
- C++ Programming
- C# Programming
- Advanced DBMS
- Unix System Programming
- System Simulation & Modelling
Workshops/FDP’S/SDP’S Attended
10
Conference/Journal Publications
- Sunil Kumar S., Aithal G., Venkatramana Bhat P. (2021) Design, Calibration, and Experimental Study of Low-Cost Resistivity-Based Soil Moisture Sensor for Detecting Moisture at Different Depths of a Soil. In: Chiplunkar N., Fukao T. (eds) International Conference on Advances in Artificial Intelligence and Data Engineering (AIDE2019), NMAMIT, Nitte, published in book series “Advances in Intelligent Systems and Computing”, vol 1133. Springer, Singapore. https://doi.org/10.1007/978-981-15-3514-7_104.
- Sunil Kumar S, Nagesh H.R, “WSN based Soil Moisture Stress Monitoring and identifying its association on Other Parameters on plants growth using hadoop Framework,” International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.51-54, 2016.
- S. G. Kanbargi and Sunil Kumar S, “Cache utilization for enhancing analyzation of Big-Data & increasing the performance of Hadoop,” 2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15), Bangalore, India, 2015, pp. 1-7, doi: 10.1109/ITACT.2015.7492645.
- Sunil Kumar S, Sanjeev G Kanabargi, “Challenges for HDFS to Read and Write Using Different Technologies”, International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=SUB154956, Volume 4 Issue 5, May 2015, 2837 – 2842
- S. Pai, Y. Sharma, S. Kumar, R. M. Pai and S. Singh, “Formal Verification of OAuth 2.0 Using Alloy Framework,” 2011 International Conference on Communication Systems and Network Technologies, Katra, India, 2011, pp. 655-659, doi: 10.1109/CSNT.2011.141.
- Kumar, Sunil S., Shyam S. Karanth, K. C. Akshay, Ananth Prabhu, and Bharathraj M. Kumar. “Improved aprori algorithm based on bottom up approach using probability and matrix.” International Journal of Computer Science Issues (IJCSI) 9, no. 2 (2012): 242.
- Kumar, Sunil S., Santhosha Rao, and Shivaray Pai. “Moving Object Detection using Frame Interleaving and Clustering based Compression.” International Journal of Computer Technology and Applications 3, no. 4 (2012): 1583-1586.
Funded Projects
Title : Technology Aided Agriculture Optimization
Funding Agency : VGST
Funding Amount : 40 Lakh
Role : Co-Investigator
Mr. Sunil Kumar S.
Senior Assistant Professor
Dr.Prashanth C M
Principal & Professor
Ms. Radha E G
Educational qualification
B.E – Computer Science & Engg
M.Tech – Computer Science & Engg
Total Experience: 3.5 years
Area of Interest: Image processing, Machine Learning
Subject Handled · Data Structures and Applications · Discrete Mathematical Structures · Data Communication · Computer programming · Database management system· Computer Organization and Architecture· Digital Image Processing· Design and Analysis of Algorithms· Social Connect and Responsibility
Workshops/FDP/SDP Attended:
- Five Days Online Faculty Development Programme on “RPADD” Organized by UI path academic alliance, MITE, Mangalore [27th September to 1st October 2021].
- One week AICTE-VTU joint teacher traninng program on “An Overview of Teaching Techniques in Innovation & Design Thinking” Organized by VTU-HRDC, Centre for PG Studies, VIAT, Muddenahalli, Chikkaballapur[27th to 31st December 2021].
- Ten days online Faculty Development Programme on “Blockchain Technology-Applications,Issues and Challenges” organized by E&ICT Academy,NIT Waragangal and Mangalore Institute of Technolgy & Engineering,Mangalore during 21st February-2nd March,2022.
- Ten days online Faculty Development Programme on”AI/ML for computer vision and medical image analysis applications” organized by E&ICT Academy,NIT Waragangal and REVA university,Bengalur during 18th-27th April,2022.
- Five days online Faculty Develeopment Programme on “Introduction to Python and Its applications” Organized by VTU,Centre for PG Studies, VIAT, Muddenahalli, Chikkaballapur[13th to 17th March 2023].
- Five days online Faculty Develeopment Programme on “Robotics & Artificial Intelligence” Organized by VTU,Centre for PG Studies, VIAT, Muddenahalli, Chikkaballapur[24th to 28th March 2023].
Conference/Journal Publications
- Radha E G “Design and Implementation of Image dehazing using Histogram Equalization” in 3rd International Conference on Mobile Radio Communications & 5G Networks (MRCN 2022) on Feb 15,2023 [Springer Nature]
Ms. Radha E G
Assistant Professor
Dr. Maryjo M George
EDUCATIONAL QUALIFICATION: Ph.D.
EXPERIENCE: 2.5 years teaching
AREA OF INTEREST: Biomedical image processing, Multi
SUBJECTS HANDLED: Information theory and coding, Programming in C, Cyber security
WORKSHOPS/FDP/SDP ATTENDED:
- Three days FDP on ‘Writing Effective R&D Project Proposal and Funding Opportunities from Government Scientific Departments’ organized by IQAC and Research Council, MITE, Mangalore from 8th to 10th July 2023
- SERB sponsored two-day FDP on ‘Recent trends in bio-signal acquisition and research perspective in signal analyses’ organized by NSS college of engineering, Palakkad from 25th to 26th March 2022.
- Five days FDP on ‘Data analysis and mining with python’ organized by CMR Engineering college, Hyderabad from 8th-12th Nov 2021
- Seminar on Large Scale computational Bio medical Image Analysis and
Informatics – Micro to Macro organized by SCOPE, VIT on 25th Oct 2017 - One day workshop on ‘Introduction to Molecular imaging- An educational session in pre-clinical and clinical imaging modalities’ organized by SELECT and SBST, VIT on 28th August 2017
- One week FDP on ‘Advanced image processing’ organized by SCOPE, VIT from 28th Nov to 2nd Dec 2016
- One day workshop on ‘Writing funded project proposals and publishing quality research papers’ organized by ASC, VIT on 20th Aug 2016
- Short term course on ‘Digital image processing and its applications’ organized by Communication Engineering division, SENSE, VIT from 14th to 22nd March 2016
- Three day national workshop on ‘Pattern recognition and classification’ organized by Digital Signal Processing division, SENSE, VIT from 12th to 14th Nov 2015
- One day workshop on ‘Scientific writing’ organized by Periyar E.V.R Central Library, VIT in association with Dept. of Library and Information Science, University of Madras on 30th Oct 2015
- Two days workshop on “Embedded Systems and Industrial Applications” organized by Dept. of ECE, SSN College of Engineering, Kalavakkam from 4th April to 5th April 2014
JOURNALS:
- Maryjo M George and Kalaivani S., “Retrospective correction of intensity inhomogeneity with sparsity constraints in transform-domain: Application to brain MRI”, Magnetic Resonance Imaging, Vol. 61, pp.207-223, Sept 2019, ISSN: 0730-725X. (SCI indexed, Impact factor: 3.13)
- Maryjo M George, Kalaivani S., Sudhakar M.S, “A non-iterative multi-scale approach for intensity inhomogeneity correction in MRI”, Magnetic Resonance Imaging, Vol.42, pp.43-59, Oct 2017, ISSN: 0730-725X (SCI indexed, Impact factor: 3.13)
- Maryjo M George and Kalaivani S., “A Diffusion based compensation approach for intensity inhomogeneity correction in MRI”, International Journal of Imaging Systems and Technology, Vol.30, No. 3, pp. 761-778, Sept 2020 (SCI indexed, Impact factor: 2.12)
- Maryjo M George and Kalaivani S., “A multi-scale framework for bias field estimation in MRI brain images,” International Journal of Engineering and Technology, Vol. 7 No.4.10, pp.197-201. Oct 2018, ISSN: 2227-524X. (Scopus indexed)
- Maryjo M George and Kalaivani S., “Intensity inhomogeneity correction and tissue segmentation of MR images: A parametric approach”, International Journal of Pure and Applied Mathematics, Vol.115, No.9, pp.409-416, Jul 2017, ISSN: 1311-8080. (Scopus indexed)
- Maryjo M George and K Vadivukkarasi, “Kalman Filtering For RSSI Based Localization System in Wireless Sensor Networks”, International Journal of Applied Engineering Research, Vol. 10, No.7, pp. 16429-16440, 2015, ISSN: 0973-4562. (Scopus indexed)
- Maryjo M George and Kalaivani S., “A view on atlas-based neonatal brain MRI segmentation”. In ICTMI 2017, Proceedings of the International Conference on Translational Medicine and Imaging, Springer, pp.199-214, 2019. ISBN: 978-981-10-4166-2. (Scopus indexed)
- Maryjo M George and S. Kalaivani, “Automatic tissue segmentation of neonatal brain MRI,” 2016 International Conference on Communication and Electronics Systems (ICCES), Coimbatore, pp. 1-5, 2016, E-ISBN: 978-1-5090-1066-0. (Scopus indexed)
CONFERENCES:
- Maryjo M George and Kalaivani S., ‘A multi-scale framework for bias field estimation in MRI brain images’, Presented at Cambridge summit 2018, Cambridge university, UK, Jan 2018
- Maryjo M George and Kalaivani S., ‘Intensity inhomogeneity correction and tissue segmentation of MR Images: A parametric approach’ , Presented at International conference on mathematical applications in engineering and technology, Tirupatur, Tamilnadu, Jan 2017
- Maryjo M George and Kalaivani S., ‘A view on atlas-based neonatal brain MRI segmentation’, Presented at Springer ICTMI 2017, Vellore, Tamilnadu, Sep 2017
- Maryjo M George and Kalaivani S., ‘Automatic tissue segmentation of neonatal brain MRI’, Presented at IEEE International conference on communication and electronics systems, Coimbatore, Tamilnadu, Oct 2016
- Maryjo M George and Kalaivani S., ‘Image compression techniques for medical images’, Presented at 11th national conference on Science, engineering and technology, Vellore, Tamilnadu, Nov 2015
Dr. Maryjo M George
Assistant Professor
Mrs. M.Amirthavalli
Educational Qualification: M.E (CS&E)
Total Experience:7
Area of Interest: Cryptography and Network Security, Machine Learning, Secure Programming
Subjects Handled: Computer Networks, Python Programming, Unix and Network Programming, Secure Programming, Java.
Mrs. M.Amirthavalli
Assistant Professor
Mrs. M. ANBURAJAM
Educational Qualification:
B. E (Information Technology), M. Tech (Software Engineering)
Area of Interest: Java, DBMS, AI
Subjects Handled: Artificial Intelligence
Workshops/FDP/SDP Attended
- Attended Implant Training in Mobile Technology at Matrix cube Technologies.
- Attended Workshop in Java and Advanced Java at MIT
- Attended Implant Training in Java at Aadhityaa Infomedia Solutions.
- Attended a Diploma Programme in Java at Aadhityaa Infomedia Solutions.
Conference/Journal Publications:
- Presented a paper Entitled “Optimized Resource Utilization in Network Environment” in the International Conference on Science and Innovative Engineering”.
Mrs. M. ANBURAJAM
Assistant Professor
Mrs. Vasudha G Rao
Educational Qualification: M.Tech(CSE)
Total Experience: 2 years
Area of Interest: AI,ML,DL,Data Science
Subjects Handled: OS,DBMS,UNIX programming, GOlang, Competitive programming in C++, Python Programming, NLP
Mrs. Vasudha G Rao
Assistant Professor
Infrastructure
All the laboratories are well designed and equipped with latest computer systems. All systems are interconnected through LAN having sophisticated servers and internet connectivity with adequate bandwidth. All the laboratories have requisite software for undertaking all kinds of latest projects.
Major Labs
Algorithms Lab/ Artificial Intelligence Lab
The lab is equipped with 32 personal computers with latest configuration. PCs have windows 11 operating system with Java, Eclipse, Python and latest browsers. Students carry out programs related to Algorithms in Eclipse and Java and Artificial Intelligence practical in Python.
Data Structures/ DBMS lab
The lab is equipped with 32 personal computers with latest configuration. PCs are installed with Ubuntu operating system, C/C++, Java, MySQL and latest internet browser. Students perform practical related to solving data structure problems. Students perform database related practical and develop mini project in this lab.
Research Center
Department Forum – ARTIFERA
ARTIFERA – ARTIFICIAL INTELLIGENCE ERA is a student association of Artificial Intelligence & Machine learning department established on 17 th November, 2021. Its main objective is to create awareness and groom professionals skilled in the area of Artificial Intelligence & Machine learning. All students of Artificial Intelligence and Machine learning department are members of this association. It provides platform to the students to enhance their technical as well as non technical skills. ARTIFERA organizes various technical events like technical talks, workshops, quiz, project competition and exhibitions etc. In addition, department forum aims to promote research and entrepreneurial skills in students. Students are encouraged to participate in non technical events also for their holistic development.
“Our intelligence is what makes us human, and AI is an extension of that quality.” – Yann LeCun
Committee Members – Academic Year 2021-22
1. Mr. Prajeet Chendekar President, Second year
2. Mr. Karthik Raj Shetty Secretary, Second year
3. Mr. Dhruva Kumar Shetty Treasurer, Second year
4. Mr. Shreevatsan Placement Coordinator, Second year
5. Mr. Vishal Cultural Coordinator, Second year
6. Mr. Nandu Krishna G Sports Coordinator, Second year
Activity Report
Academic Year 2021-22 Click Here