Deepak Saini

Assistant Professor, Business Analytics and Information System

Deepak Saini

Assistant Professor, Business Analytics and Information System

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    [name] => Deepak
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    [department] => Assistant Professor, Business Analytics and Information System
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    [created_on] => 2024-01-12 13:12:37
    [last_name] => Saini
    [email] => deepak.saini@thapar.edu
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Dr. Deepak Saini is an Assistant Professor in Business Analytics and Information System. He holds a PhD from Punjab University and has worked with prestigious organizations like Wipro InfoTech as a Software Engineer, and with GreyB Research Private Limited as a Patent Research Analyst. He has also taught at institutions like Baddi University of Emerging Sciences and Technologies (BUEST) and Chandigarh University. He has also undertaken projects with CSIR –CSIO and PGIMER.

His areas of expertise include Deep Learning, Computer Vision, Image Processing, Artificial Intelligence, Healthcare, Analytics, with prowess in MATLAB, Java, Oracle SQL, Python, HADOOP (Basics), Image Processing, Deep Learning, LabView, Neural Networks, and OpenCV.

Publications:


  • Saini, Deepak, Trilok Chand, Devendra K. Chouhan, and Mahesh Prakash. "A comparative analysis of automatic classification and grading methods for knee osteoarthritis focussing on X-Ray images." Biocybernetics and Biomedical Engineering 41, no. 2 (2021): 419-444.
  • Saini, Deepak, et al. "Automated knee osteoarthritis severity classification using three?stage preprocessing method and VGG16 architecture." International Journal of Imaging Systems and Technology (2023).
  • Saini, Deepak, Bansal, Dipti. "Analysis and Recognition of Emotions Using Zernike Moment Based Facial Expression System", International Journal of Innovative Research in Science, Engineering and Technology. Vol. 5, Issue 8, August 2016.
  • Paper titled “A Deep Learning Approach for Development of Web Application for Automated Knee OA Classification” is accepted for IEEE conference IC2E3-20

 

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Contact


deepak.saini@thapar.edu

Education


Ph.D. (Computer Science Engineering) from Punjab Engineering College, Chandigarh. Title: Machine Learning based Knee Osteoarthritis Classification.

M.Tech (Electronics and Communication Engineering), University College of Engineering, Punjabi University Patiala

B.Tech (Electronics and Communication Engineering), Institute of Engineering and Emerging Technologies (IEET), Baddi (Affiliated to Himachal Pradesh University)

Dr. Deepak Saini is an Assistant Professor in Business Analytics and Information System. He holds a PhD from Punjab University and has worked with prestigious organizations like Wipro InfoTech as a Software Engineer, and with GreyB Research Private Limited as a Patent Research Analyst. He has also taught at institutions like Baddi University of Emerging Sciences and Technologies (BUEST) and Chandigarh University. He has also undertaken projects with CSIR –CSIO and PGIMER.

His areas of expertise include Deep Learning, Computer Vision, Image Processing, Artificial Intelligence, Healthcare, Analytics, with prowess in MATLAB, Java, Oracle SQL, Python, HADOOP (Basics), Image Processing, Deep Learning, LabView, Neural Networks, and OpenCV.

Publications:


  • Saini, Deepak, Trilok Chand, Devendra K. Chouhan, and Mahesh Prakash. "A comparative analysis of automatic classification and grading methods for knee osteoarthritis focussing on X-Ray images." Biocybernetics and Biomedical Engineering 41, no. 2 (2021): 419-444.
  • Saini, Deepak, et al. "Automated knee osteoarthritis severity classification using three?stage preprocessing method and VGG16 architecture." International Journal of Imaging Systems and Technology (2023).
  • Saini, Deepak, Bansal, Dipti. "Analysis and Recognition of Emotions Using Zernike Moment Based Facial Expression System", International Journal of Innovative Research in Science, Engineering and Technology. Vol. 5, Issue 8, August 2016.
  • Paper titled “A Deep Learning Approach for Development of Web Application for Automated Knee OA Classification” is accepted for IEEE conference IC2E3-20

 

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