Birla Institute of Technology, Mesra
Faculty Image

Anusha Vupputuri

Joined Institute on : 7-Jun-2024

  • Assistant Professor
  • Electronics and Communication Engg
  • PhD
Contact Address

TA 18 BIT Campus Mesra, Ranchi, Jharkhand

Visakhapatnam, Andhra Pradesh

  • Phone Office - 8987848258
  • Phone Residence - 8987848258
  • Email - anusha@bitmesra.ac.in
Work Experience

Teaching : 7 Years

Research : 10 Years

Individual: 1 Years
Professional Background
  • Lead Engineer, AIRA Matrix Pvt. Ltd, Mumbai
  • Senior Engineering Technical Writer, Deep Learning and Computer Vision, MathWorks India
Research Areas
  • Image processing and Computer Vision
  • Machine Learning
  • Medical Image Analysis
Award and Honours

  • Augmented Writing Skills for Articulating Research (AWSAR) Award- 2020 (PHD category) (1 in 100) from DST -Govt. of India

  • Gandhian Young Technological Innovation (GYTI) APPRECIATION AWARD- 2021 (1 in 15), from SRISTI, GIAN and Ministry of
    Science and Technology, Govt. of India

  • Infosys Travel grant for Women for presenting research paper at  IEEE EMBC- 2017 held in Jeju, South Korea

  • Institute Best Conference Travel Grant for for presenting research paper at  IEEE EMBC- 2019 held in Berlin, Germany
Publications
Publication Year

Journals:

  • A Vupputuri, A. Gupta, N Ghosh; MCA-DN: Multi-path Convolution leveraged Attention Deep Network for Salvageable Tissue Detection in Ischemic Stroke from Multi-parametric MRI;  Computers in Biology and Medicine; 104724; 136; 2021  https://doi.org/10.1016/j.compbiomed.2021.104724

  • A Vupputuri, N Ghosh; Multi-view Iterative Random Walker for Automated Salvageable Tissue Delineation in Ischemic Stroke from Multi-Sequence MRI;  Journal of Neuroscience Methods; 2; 360; 2021  https://doi.org/10.1016/j.jneumeth.2021.109260

  • Vupputuri, A, Ashwal, S, Tsao, N. Ghosh, Ischemic stroke segmentation in multi-sequence MRI by symmetry determined superpixel based hierarchical clustering;  Computers in Biology and Medicine; 116; 103536; 2020.  https://doi.org/10.1016/j.compbiomed.2019.103536

Conferences:

  • A Gupta, A Vupputuri, N Ghosh; Delineation of Ischemic Core and Penumbra Volumes from MRI using MSNet Architecture;  Annual International Conference of the IEEE Engineering in Medicine and Biology Society; pp. 6730-6733; Berlin; 2019 ( 10.1109/ EMBC.2019. 8857708)
  • R Sathish, R Rajan, A Vupputuri, N Ghosh, D Sheet; Adversarially Trained Convolutional Neural Networks for Semantic Segmentation of Ischaemic Stroke Lesion using Multisequence Magnetic Resonance Imaging;  Annual International Conference of the IEEE Engineering in Medicine and Biology Society; pp. 6730-6733; Berlin; 2019 ( 10.1109/ EMBC.2019. 8857527)
  • A Vupputuri, S Dighade, PS Prasanth, N Ghosh; Symmetry determined superpixels for efficient lesion segmentation of ischemic stroke from MRI.  Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC); pp. 742-745, Hawaii, USA; 2018 ( 10.1109/EMB C.2018. 8512283)
  • MK Nag, A Vupputuri, S Chatterjee, AK Sadhu, J Chatterjee, N Ghosh; Delineation of Hemorrhagic Mass from CT Volume;  International Conference on Applied Human Factors and Ergonomics; pp. 130-138; Orlando, USA; 2018 ( 10.1007/978- 3-319-94373- 2_14)
  • A Vupputuri, S Ashwal, B Tsao, E Haddad, N Ghosh; MRI based objective ischemic core-penumbra quantification in adult clinical stroke;  39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC); pp. 3012-3015; Jeju-South Korea; 2017, ( 10.1109/EMB C.2017.80374 91)
  • A Vupputuri; S. Meher; Facial expression recognition using local binary patterns and kullback leibler divergence:  International Conference on Communications and Signal Processing (ICCSP), pp 0349-0353; India; 2015 ( 10.1109/ICCSP.2015.7322904)