Pranjal Sahu
Email: psahu@cs.stonybrook.edu

"I am not young enough to know everything." -Oscar Wilde

I am a PhD candidate in Computer Science working under Dr. Hong Qin at Stony Brook University. My research focus is on Deep Learning applications in the field of Biomedical Imaging. Some of the problems which I work on include image classification, projection de-noising, volume reconstruction etc. Currently I am working on efficient Digital Breast Tomosynthesis reconstruction to reduce out of plane blur which can improve lesion detection in dense breast.

I did my Bachelors (Hons) in Computer Science from IIT Kharagpur in 2013 and later gained experience in software development working in startups for 3 years. I was fortunate to take Computer Vision and Computer Graphics courses under Dr. Rajiv Ranjan Sahay and Dr. Jayanta Mukhopadhyay at IIT Kharagpur which motivated me to pursue PhD in this field. I am active on Twitter where I regularly share interesting blog posts and resources related to Deep Learning, Computer Vision, Computer Graphics and Optimization.

CV | Google Scholar | Github | Twitter | LinkedIn | ResearchGate

Publications
sym

[NEW] Using virtual digital breast tomosynthesis for de-noising of low-dose projection images
Pranjal Sahu, Hailiang Huang, Wei Zhao and Hong Qin

abstract
IEEE International Symposium on Biomedical Imaging, ISBI, 2019

sym

[NEW] A Lightweight Multi-section CNN for Lung Nodule Classification and Malignancy Estimation
Pranjal Sahu, Dantong Yu, Mallesham Dasari, Fei Hou and Hong Qin

abstract | pdf
IEEE Journal of Biomedical and Health Informatics, J-BHI
, 2018

sym

Apply lightweight deep learning on internet of things for low-cost and easy-to-access skin cancer detection
Pranjal Sahu, Dantong Yu, Hong Qin

abstract | pdf | bibtex
Medical Imaging, SPIE, 2018 (Best Demo Award)

  @inproceedings{sahu2018apply,
  title={Apply lightweight deep learning 
  on internet 
  of things for low-cost and 
  easy-to-access 
  skin cancer detection},
  author={Sahu, Pranjal and Yu, 
  Dantong and Qin, Hong},
  booktitle={Medical Imaging 2018: 
  Imaging Informatics 
  for Healthcare, Research, and Applications},
  volume={10579},
  pages={1057912},
  year={2018},
  organization={International Society 
  for Optics and Photonics}
}
sym

In-Operando Tracking and Prediction of Transition in Material System using LSTM
Pranjal Sahu, Dantong Yu, Kevin Yager, Mallesham Dasari and Hong Qin

abstract | pdf | bibtex
Autonomous Infrastructure for Science, HPDC, 2018

@inproceedings{sahu2018operando,
  title={In-Operando Tracking and Prediction of 
  Transition in Material System using LSTM},
  author={Sahu, Pranjal and Yu, Dantong and 
  Yager, Kevin and Dasari, Mallesham 
  and Qin, Hong},
  booktitle={Proceedings of the 1st 
  International 
  Workshop on Autonomous 
  Infrastructure for Science},
  pages={6},
  year={2018},
  organization={ACM}
}
sym

SHREC'17 Track: Protein Shape Retrieval
Na Song, Daniela Craciun and others

abstract | pdf | bibtex
Eurographics Workshop on 3D Object Retrieval, 2017

@inproceedings{Song2017SHREC17TP,
  title={SHREC’17 Track: Protein Shape Retrieval},
  author={Na Song and Daniela Craciun and 
  Charles Christoffer and Xusi Han and 
  Daisuke Kihara and Guillaume Levieux 
  and Matthieu Montes and Hong Qin and 
  Pranjal Sahu and Genki Terashi and 
  Haiguang Liu},
  year={2017}
}
Teaching
pacman

CSE 328: Fundamentals of Computer Graphics
Instructor: Dr. Hong Qin

CSE 377: Medical Imaging
Instructor: Dr. Allen Tannenbaum

Awards
  • Computer Science Chairman Fellowship (2016-2017)
  • Best Demo Award in SPIE Medical Imaging, Houston (2018)
  • Represented (C.G.) state in National Children Science Congress, Guwahati (2005)