Specialization

Deep Learning, Computer Vision and Image Processing

Email

Nitigya.sambyal@thapar.edu

Education
•    PhD in Computer Science and Engineering, from Punjab Engineering College (Deemed to be University), Chandigarh, India. 
•    M. Tech in Computer Science from University of Jammu, Jammu, India.  
•    B. Tech in Computer Engineering from University of Jammu, Jammu, India.
Trainings
•    Certifications in various FDPs from organizations like NITTTR Chandigarh, IIT Roorkee, IIT Kanpur etc.
Experience
1.    Assistant Professor, Computer Science and Engineering Department, Thapar Institute of Engineering and Technology, Patiala, India (August 2021 - Present)
2.    Assistant Professor, Department of Computer Engineering, Government College of Engineering and Technology, Jammu, India (December 2020- August 2021)
Journal publications
SCI/SCIE indexed
1.    Nitigya Sambyal, Poonam Saini, Rupali Syal, Varun Gupta “Modified U-Net Architecture for Semantic Segmentation of Diabetic Retinopathy Images”, Biocybernetics and Biomedical Engineering, Elsevier, 40(2020), pp 1094-1109. https://doi.org/10.1016/j.bbe.2020.05.006. 
2.    Nitigya Sambyal, Poonam Saini, Rupali Syal, Varun Gupta “Modified Residual Networks for Severity Stage Classification of Diabetic Retinopathy” Evolving Systems, Springer, 2022, https://doi.org/10.1007/s12530-022-09427-3
3.    Nitigya Sambyal, Poonam Saini, Rupali Syal, “Microvascular Complications in Type-2 Diabetes: A Review of Statistical and Machine Learning Models, Wireless Personal Communications, Springer, June 2020. https://doi.org/10.1007/s11277-020-07552-3.

4.    Nitigya Sambyal, Poonam Saini, Rupali Syal, Varun Gupta, “Aggregated Residual Transformation Network for Multistage classification in Diabetic Retinopathy”, International Journal of Imaging Systems and Technology, Wiley, 2020, pp 1-12. https://doi.org/10.1002/ima.22513
5.    Varun Gupta, Nitigya Sambyal, Akhil Sharma, Praveen Kumar, “Restoration of Artwork using Deep Neural Networks”, Evolving Systems, Springer, 2019, https://doi.org/10.1007/s12530-019-09303-7.
6.    Megha Vasudev, Varun Gupta, Amit Doeger, Nitigya Sambyal, “Breast Cancer Detection from Histopathology Images Using Modified  Residual Neural Networks”, Biocybernetics and Biomedical Engineering, Elsevier, 41(2021), pp. 1272– 1287.   https://doi.org/10.1016/j.bbe.2021.08.011.
7.    Gagandeep Mangat, Divya, Varun Gupta, Nitigya Sambyal, “Power Theft Detection using Deep Neural Networks”, Electric Power Components and Systems, Taylor and Francis, 49(2021), pp. 458-473.  https://doi.org/10.1080/15325008.2021.1970055
8.    Saksham Gupta, Paras Sharma, Dakshraj Sharma, Varun Gupta, Nitigya Sambyal, “Detection and Localization of potholes in Thermal Images using Deep Neural Networks”, Multimedia Tools and Applications, Springer, 79(2020), pp 26265–26284. https://doi.org/10.1007/s11042-020-09293-8.

    Scopus indexed 
1.    Nitigya Sambyal, Poonam Saini, Rupali Syal, “A Review of Statistical and Machine Learning Techniques for Microvascular Complications in Type 2 Diabetes”, Current Diabetes Reviews, Bentham Science, 16(2020). DOI: 10.2174/1573399816666200511003357. 
2.    Nitigya Sambyal, Poonam Saini, Rupali Syal, “Big Data Analytics: Applications, Trends,   Tools and Future Research Directions”, Handbook of Research on Cloud Computing, Big Data in IoT, IGI Global, pp 67-81, April 2019. (Book Chapter) 

    Conferences 
1.    Nitigya Sambyal, Poonam Saini, Rupali Syal, “A Discriminative Learning-based Deep Learning Approach for Diabetic Retinopathy Classification, International Conference on Artificial Intelligence and Sustainable Engineering, NIT Goa, India, 18-20 January, 2021, Published in  Lecture Notes in Electrical Engineering, Springer.
2.    Nitigya Sambyal, Pawanesh Abrol, “Character Segmentation using Connected Component Approach”, Proceedings of National Conference on Recent Trends and Technologies in Data Sciences and Artificial Intelligence, University of Jammu, Jammu, 26-27 August, 2016. 

Other activities
    Qualified National Eligibility Test (UGC NET, 2018)  and Graduate Aptitude Test (GATE, 2015 and 2016).
    Member of coordination team of Experiential Learning Activity (ELC) on "ROBOTIC ARM--The Soul of Industrial Automation" for B,Tech at Thapar Institute of Engineering and Technology, Patiala.
    Member of Project semester coordination team at Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala.
    Invited for expert lecture on “Neural Networks and Deep Learning” at AcSIR-Central Scientific Instruments Organisation, Chandigarh during the "statistical analysis and machine learning" course, 2022
    Delivered an expert lecture on “Free Tools for Artificial Intelligence and Deep Learning” in the Short Term Course on “Free Software and Resources for Technical Education” organized by Department of Computer Science and Engineering, National Institute of Technical Teachers
Training & Research, Chandigarh, 2022.
    Invited for expert talk on Deep Learning for Medical Image Analysis at Dr. BR Ambedkar, National Institute of Technology, Jalandhar in December 2021.

    Delivered an expert talk on Artificial Intelligence at GCET, Jammu in December 2021
    Member of organizing committee in AICTE Induction Program for B.E batch 2020 at GCET Jammu, J&K (UT), India.