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Department of Artificial Intelligence and Machine Learning

Achievements

Industry Collaboration

Research

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About the Department

Vision and Mission

PEO,PO’S,PSO’S

HOD Profile

Faculty List

Milestone

Professional Society

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About the Department

  • The department of Artificial Intelligence and Machine Learning has been established in the year 2022, recognized by AICTE. Artificial Intelligence specialization will create engineers, who can build solutions, with intelligence as humans.
  • The department conducts co-curricular activities such as Guest Lectures, Seminars, Training programs, Workshops, etc. The Department also organizes industrial visits to help students to update their knowledge.
  • An exclusive Training and Placement cell is functioning for providing continuous training and placement assistance to the students during their course of study. The students are trained by internal trainers and industry experts with various training partners to improve their employability skills like soft skills, technical, analytical and logical skills. Apart from training, to enhance the innovative thinking and managerial skills of young minds, they are encouraged to organize and participate in various events like paper presentations, technical symposia and project presentations.
  • Currently, the world is being driven digitally with technology and data being present everywhere. It is because many leading companies in the world today, such as Face book, Google and Uber, make machine learning as a central part of their operations. The machine learning market size has been steadily growing. It is a type of data mining that allows computers to learn on their own experience.
  • Nowadays, it's not an exaggeration to say that each of us encounters machine learning multiple times daily. Until the 1960s AI and ML were more or less synonymous, but thereafter they diverged and now they are rampant in the tech industry, mass media and academia.
  • Data scientists and machine-learning engineers are two of the top-ranked jobs globally. Professionals with critical expertise in the domain of data science and machine learning are highly sought after by tech and finance organizations.
  • This course dives deep into the foundational as well as advanced concepts of data science and machine learning to enable students to devise practical solutions in real context.
  • The department provides state-of-the-art computing facilities to the students enabling them to stay a step ahead. They are exposed to various opportunities such as in plant training, internships, and workshops during their course of study.

Vision and Mission

VISION

To be a center of excellence in the field of Artificial Intelligence and Machine Learning applications through appropriate use and diffusion of emerging techniques.

MISSION

  • To develop students with strong capabilities in Artificial Intelligence by continuously enhancing teaching and learning with state-of-the-art technologies.
  • To provide high-quality, value-based education to gain competence in Artificial Intelligence and Machine learning in terms of research and innovation activities.
  • To implement engineering solutions for the benefit of society by the use of AI and ML.

Programme Educational Objectives(PEOs)

  • PEO 1: To perform well in their professional career by acquiring enough knowledge in the domain of Artificial Intelligence and Machine Learning.
  • PEO 2: To enable graduates to research, design and implement AI/ML products and services with effective Communication and Entrepreneurial Skills.
  • PEO 3: To modernize the students with evolving technology and use it for career advancement.

Programme 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.
  • PO 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.
  • PO 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.
  • PO 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.
  • PO 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.
  • PO 8: Ethics:
    Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
  • PO 9: Individual and team work:
    Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
  • PO 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.
  • 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.

Programme Specific Outcomes (PSOs)

  • PSO1: Professional Skills: To develop models in Data Science, Machine learning, Deep learning and Big data technologies, using AI and modern tools.
  • PSO2: Problem-Solving Skills: To create solutions for interdisciplinary AI problems through acquired programming knowledge in the respective domains fulfilling with real-time constraints.
  • PSO3: Successful Career and Entrepreneurship: Able to take up higher studies, Research & Development and Entrepreneurships in Artificial Intelligence and Machine Learning with ethical values.

HOD Profile

Dr.B.Anni Princy M.E, Ph.D.,

Professor and Head of the Department in Artificial Intelligence & Machine Learning

Dr. Anni Princy .B has completed 28 years of teaching Experience. She received M.E., degree in Computer Science & Engineering in the year 2004 and Ph.D. in Computer Science & Engineering in the year 2015 from Sathyabama University, Chennai; she has published 50+ articles in various reputed National and International Journals and patented 6 of her ideas. Her areas of interest include Software Reliability Engineering, Networking and Machine Learning. She received fund Rs.7,85,000/- from AICTE for MODROB . She is affiliated with the Institute of Electrical and Electronics Engineers (IEEE) & Computer Society of India (CSI).

Received Inspiring Senior Faculty Award - ADVANCED MATERIALS & APPLICATIONS (ISSN: 2582-5070) An International peer reviewed journal published by Madras Journal Series Pvt Ltd , Received “Best Teacher Award” in the year 2007-2008, Panimalar Engineering College and also received Certificate of appreciation as a proctor to guide and oversee competing teams for the IEEE Xtreme 11.0 programming competition that hosted 8,300 participants 14th October 2017

Faculty List

S.No. Name of the Faculty Designation

1.

Dr.ANNI PRINCY.B

Professor

2.

Dr.SURESH .G

Professor

3.

Dr.SASIKUMAR. D

Professor

4.

Dr.ANAND BABU.R

Associate Professor

5.

Dr.KANIMOZHI.S

Associate Professor

6.

Dr.PRABHA.B

Associate Professor

7.

Mr.NAGARAJ.J

Assistant Professor GR-I

8.

Mr. MUTHU. V

Assistant Professor

9.

Mrs. VANIPRIYA.B

Assistant Professor

10.

Mrs.PANDI KUMARI.M.R

Assistant Professor

11.

Mrs.SARANYA . A

Assistant Professor

12.

Mrs.BHARANI .M

Assistant Professor

13.

Mr.EZHILVENDAN .M

Assistant Professor

14.

Mrs.RAMATHILAGAM A

Assistant Professor

15.

Mr.RIZWAN BASHA. A

Assistant Professor

16.

Mrs.THAMIZHARASI .K

Assistant Professor

17.

Ms.ALAMELU .R

Assistant Professor

18.

Mr.VENKATESAN .R

Assistant Professor

19.

Mr.AKASH S D

Assistant Professor

20.

Ms. DERISHA MAHIL

Assistant Professor

21.

Ms.MEENAKSHI L

Assistant Professor

22.

Ms.HASHINI S

Assistant Professor

23.

Mr.THIYAGARAJAN C

Assistant Professor

24.

Mrs.VENITHA E

Assistant Professor

25.

Mrs.SARANYA V

Assistant Professor

26.

Mr.RAJASEKARAN S

Assistant Professor

27.

Mrs.SARANYA K

Assistant Professor

28.

Mrs.KIRUTHIKA S

Assistant Professor

First Year Faculty List

S.No. Name of the Faculty Designation

1.

Mrs.VINODHINI.S

Assistant Professor

2.

Mrs.RAJALAKSHMI.A

Assistant Professor

3.

Mr.MAHADEVAN P

Assistant Professor
4.

Mr.MANIKANDAN J

Assistant Professor

Department Highlights

Name of the Department Start Year Sanctioned Intake
AI & ML 2022-23 60
2023-24 Intake revised from 60 to 240

Professional Society

Professional Society 2024-2025

Professional Society 2023-2024

Club Activities

Club Activities 2024-2025

Club Activities 2023-2024

Newsletter

Newsletter

Magazine

Magazine

Survey Forms

Question Bank – Academic Year 2025-26 (Even Semester)

YR/SEM SUBJECT CODE SUBJECT TITLE LINKS
II / IV
23MA1406
Probabilistic Methods and Optimization Techniques for Machine Learning
23CS1401
Computer Networks
23IT1404
Operating Systems With Linux Administration
23AD1401
Machine Learning
23CB1402
Introduction to Innovation
and Entrepreneurship
23AD1403
Software Development and Practices
III / VI
23ML1601
Reinforcement and
Ensemble Learning
23ML1602
Swarm Intelligence
23AD1601
Deep Learning
23AD1602
Computer Vision
23ME1944
Supply Chain Management
23CS1910
Digital Marketing
Honors
23ML1903
Speech and Language Processing using Deep Learning
23IT1904
UI and UX Design

Minor - for ECE, EEE
23ML4003
Machine Learning II
23ML4004
Reinforcement Learning
IV / VIII
21AD1924
Optimization Techniques in Machine Learning
21IT1906
DevOps

AIML Department Library Details

Item Details
Area 166 Sq.m.
No. of  Volumes 803
No. of  Titles 288
No. of Total Technical Journals(Scopus-National) 15 (Access to Central Library-II)
No. of Reprints(International Journals) 09 (Access to Central Library-II)
No. of Computers 01
No. of E-Journals 05(IEEE-ASPP/IEEE-POP/ELSIVIER-SCOPUS/ DELNET/EBSCOHOST
No. of  E-BookS 01 (MGH)

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