Dr. Prateek Keserwani

Dr. Prateek Keserwani


Research Area

  • Computer Vision
  • Machine Learning
  • Deep Learning

Contact Information

prateekeserwani@gmail.com

Profile

Prateek Keserwani is working as a Lead Engineer (Machine Learning) in a Samsung Research Institute Bangalore, India. He did Ph.D. in Dept. of CSE, IITR, advised by Dr. Partha Pratim Roy (IIT Roorkee).on the detection and concealment of text in natural images. He completed his M.Tech from the University of Allahabad, Allahabad (UP) in 2015. He has also served as a guest faculty in NIT Allahabad (from 2010 to 2012) and the University of Allahabad (2015 - one semester). He also acted as a reviewer in many journals, conferences, and Workshops, including IEEE Transactions on Circuits and Systems for Video Technology, IEEE Access, IET Image Processing, IET Biometrics, Multimedia Tools and Applications, IJDAR, The Visual Computer, SN Computer Science, ICPR, ICFHR, CVIP, and Workshop ECCV. 


Currently, he is working in the area of neural architecture search. The neural architecture search is a step toward Learn2Learn. The current deep learning method can learn automatic features but needs the handcrafted design of the architectures. But, the neural architecture search obtains the optimal neural network from the search space and eliminates the need to design the architectures manually.  

Fellowship

  • VVS-Fellowship for Ph.D. from the Ministry of Electronics and Information Technology (MeitY)
  • MHRD fellowship for M.Tech

Competitions

Update

  • Joined as a Lead Engineer (Machine Learning) in Samsung Research Institute Bangalore, India. 
  • Got an internship offer at Samsung Research Institute Bangalore.
  • Got one paper accepted in ICPR 2022, entitled " Cross-Session Motor Imagery EEG Classification using Self-Supervised Contrastive Learning."
  • Got one paper accepted in IEEE Transactions on Circuits and Systems for Video Technology, entitled "Robust Scene Text Detection for Partially Annotated Training Data."  [Visualization]  
  • Visualization of the Quadbox  [Visualization]