Dr. Sanju Kumari Singh

Assistant Professor (Contractual -II)

Specialization

Artificial Intelligence, Machine Learning and Big Data

Email

sanju.singh@thapar.edu

Specialization

Artificial Intelligence, Machine Learning and Big Data

Email

sanju.singh@thapar.edu

 

EDUCATION

1.    Ph.D. (Year of Completion: 2023), Punjab Engineering College (Deemed to be University), Sector 12 Chandigarh. (Computer Science Department)
Title: Machine Learning based Knee Osteoarthritis Classification.
2.    NTA/UGC NET qualified in 2019 (Assistant Professorship).
3.    M.Tech    ELECTRONICS    AND    COMMUNICATION    ENGINEERING    from
University College of Engineering, Punjabi University Patiala.
4.    B.Tech  in  ELECTRONICS  AND  COMMUNICATION  ENGINEERING  from
Himachal Pradesh University.
5.    12th from G.A.V. Public School Kangra (CBSE Board Delhi).
6.    10th from G.A.V. Public School Kangra (CBSE Board Delhi).

EMPLOYMENT
Education
1.    PhD in Computer Science and Engineering from Thapar Institute of Engineering and Technology
o    Title – Big Data Analytics of Demand Response Management in Smart Grid
2.    M. Tech. in Information technology from Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal (M.P)
3.    B. Tech. in Computer Science and Engineering from SVERI Pandharpur (Maharashtra). 
4.    Schooling from K.D. Girls High School Purnia (Bihar).

Experience
1.    Assistant Professor (Research Faculty), Computer Science and Engineering Department, Thapar University Patiala, India (Feb 2025 - present)
2.    Assistant Professor, Computer Science and Engineering Department, SSGDCOE, BHUSAWAL, Maharashtra (July 2013 – April 2014) 
3.    Teaching Assistant in Computer Science and Engineering Department, (January 2022– December 2022)


Journal publications
1.    Sanju Kumari, Neeraj Kumar, and Prashant Singh Rana. "Big Data Analytics for Energy Consumption Prediction in Smart Grid Using Genetic Algorithm and Long Short-Term Memory." Computing & Informatics 40.1 (2021).
2.    Sanju Kumari, Neeraj Kumar, and Prashant Singh Rana. "Comparative performance study of different filtering techniques with LSTM for the prediction of power consumption in smart grid." IETE Journal of Research 70.4 (2024): 3646-3663.
3.    Sanju Kumari, Neeraj Kumar, and Prashant Singh Rana. "A Big Data Approach for Demand Response Management in Smart Grid using the Prophet model." Electronics 11.14 (2022): 2179.

Peer reviewer for Journals
●    Cluster Computing Journal

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