Specialization

Deep Learning, Computer Vision, and Artificial Intelligence for Medical Diagnosis

Email

Sandeep.mandia@thapar.edu

Contact No.: +91-9799790044

Education:

• PhD from Malaviya National Institute of Technology Jaipur, India
  • Thesis Title: “Towards Leveraging Deep Learning and Computer Vision for Student Engagement Analysis”
• M. Tech from National Institute of Technology Silchar, Assam, in Microelectronics and VLSI Design
• B. Tech from Rajasthan Technical University, Rajasthan, in Electronics and Communication Engineering

Experience:

Publications

Journal (SCI/SCIE)

1. S. Mandia, K. Singh, R. Mitharwal, “Recognition of Student Engagement in Classroom from Affective States” International Journal of Multimedia Information Retrieval, 12, 18 (2023), DOI: 10.1007/s13735-023-00284-7 [SCIE/Q1/IF-5.6]
2. S. Mandia, R. Mitharwal, K. Singh, “Automatic Student Engagement Measurement using Machine Learning Techniques: A Literature Study of Data and Methods” Multimedia Tools and Application (2023), DOI: 10.1007/s11042-023-17534-9 [SCIE/Q1/IF-3.6]
3. D. Janu, K. Singh, S. Kaushik, S. Mandia, “Hierarchical Cooperative LSTM-based Spectrum Sensing,” IEEE Communications Letters, 27 (3) (2023), 866-870, DOI: 10.1109/LCOMM.2023241664 [SCIE/Q1/IF-4.1]

International Conferences

1. S. Bohra, M. Kumari, S. Mandia, K. Singh “Neoteric Advancements in Neural Automatic Text Summarization: A Comprehensive Survey,” 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), DOI: 10.1109/ICCCNT56998.2023.10307105
2. S. Mandia, F. Mushtaq, K. Singh, R. Mitharwal, A. Panthakkam, “YOLO-v5 Based Single Step Student Affect State Detection System”, 2023 second International Conference on the Paradigm shifts in Communication, Embedded Systems, Machine Learning and Signal Processing, DOI: 10.1109/PCEMS58491.2023.10136090
3. S. Mandia, K. Singh, R. Mitharwal, “Vision Transformer for Automatic Student Engagement Estimation,” 2022 Fifth IEEE International Conference on Image Processing, Applications and Systems, DOI: 10.1109/IPAS55744.2022.10052945
4. S. Mandia, A. Kumar, J. K. Deegwal, K. Verma, “3D Convolution for Driver Yawning Detection”, 2022 International Conference on Intelligent Systems and Smart Infrastructure, DOI: 10.1201/9781003357346-64
5. S. Mandia, A. Kumar, K. Verma, J. K. Deegwal, “Vision-Based Assistive Systems for Visually Impaired People: A Review,” 2021 International Conference on Optical & Wireless Technologies, DOI: 10.1007/978-981-19-1645-8_17
6. S.Mandia, R.Rabidas, A. Roy, and R.H.Laskar, “Fundamentals of Image compression and comparative study of JPEG and Hybrid (DWT+DCT) Model,” International Journal of Innovative Research In Science, Engineering, and Technology, 3, 3, (2014).

Patent

1. K. Singh, F. Mushtaq, S. S. Chouhan, S. Mandia, R. Kumar, P. Harjule, “An AI-Based Portable Computer-Aided Diagnostic System for Silicosis Disease” Published, App. No. 202311063986 (13/10/2023). (Published)

Membership of Professional Bodies

• Member IEEE

Academic Projects

• Developed proof of concept for AI-enabled Cardiac Valvular Heart Disease Detection (Speaking Stethoscope), 2023.
• A project titled “A deep learning based standalone assistive device for visually impaired persons” implemented a vision solution using a YOLO-based deep learning model on Raspberry Pi for visually impaired persons, 2021.
• A project titled “Facial Landmark Detection using ResNet” trained a deep learning model Residual Network on Facial Landmark Detection dataset from Kaggle on Google Colaboratory, 2020.
• A project titled “Facial Expression Recognition” trained a Convolutional Neural Network (CNN) based deep learning model on the Facial Emotion Recognition (FER-13) dataset on Google Colaboratory, 2020.
• A project titled “SVM Based Face Recognition” trained an SVM model on the ORL database for faces using MATLAB and customized it for the faculty members of the department, 2019.