Assistant Professor

Dr Isunuri Bala Venkateswarlu

Department of Computer Science and Engineering

Interests

  • Deep Learning
  • Medical Image Analysis
  • Artificial Intelligence and Machine Learning

Faculty Details

Education

2005

Koneru Lakshmaiah College of Engineering, ANU, Guntur
BTech

2010

School of Information Technology, JNTU,
Hyderabad
MTech

2023

IIITDM Kancheepuram
PhD

Experience

  • Feb 2024 to May 2024 – Assistant Professor – GITAM (Deemed to be) University, Hyderabad
  • July 2023 to Dec 2023 – Assistant Professor – Anurag University, Hyderabad
  • June 2017 to Dec 2018 – Assistant Professor – St. Ann’s College of Engineering and Technology, Chirala
  • July 2015 to May 2016 – Assistant Professor – Vignan’s Lara Institute of Technology and Science, Vadlamudi
  • Jan 2011 to Oct 2014 – Associate Professor – St. Ann’s College of Engineering and Technology, Chirala
  • Apr 2006 to Dec 2010 – Assistant Professor – St. Ann’s College of Engineering and Technology, Chirala
  • Aug 2005 to Mar 2006 – Assistant Professor – Chirala Engineering College, Chirala

Research Interest

  • Optimization of deep neural networks for medical and satellite image analysis.
  • Design of large language models with optimized parameters.

Awards & Fellowships

  • 2019 to 2021 - JRF - IIITDM Kancheepuram
  • 2022 to 2023 - SRF - IIITDM Kancheepuram

Memberships

  • CSI, ISTE, ACM, IEEE

Publications

JOURNALS
  • Venkateswarlu Isunuri and Jagadeesh Kakarla. “Ensemble coupled convolution network for three-class brain tumor grade classification“. Multimedia Tools and Applications. 2023.
  • Venkateswarlu Isunuri and Jagadeesh Kakarla. “EfficientNet and Multi-path Convolution with Multi-head Attention network for brain tumor grade classification“. Computers and Electrical Engineering. Elsevier, Vol. 108, pp. 108700, 2023.
  • Venkateswarlu Isunuri and Jagadeesh Kakarla. ”Three-class brain tumor classification from magnetic resonance images using separable convolution based neural network”. Concurrency and Computation Practice and Experience. Wiely, Vol. 34(1), 2022.
  • Jagadeesh Kakarla, Venkateswarlu Isunuri, K. S. Doppalapudi, and K. S. R., Bylapudi. ”Three-class classification of brain magnetic resonance images using average-pooling convolutional neural network”. International Journal of Imaging Systems and Technology. Wiely, Vol. 31(3), 2021.
  • Kokkalla S., Jagadeesh Kakarla, and Venkateswarlu Isunuri. ”Three-class brain tumor classification using deep dense inception residual network”. Soft Computing. Springer, Vol. 25, 2021.
  • Kumar R.L., Jagadeesh Kakarla, and Venkateswarlu Isunuri. ”Multi-class brain tumor classification using residual network and global average pooling”. Multimedia Tools and Applications. Springer, Vol. 80, 2021.
  • Venkateswarlu Isunuri. ”Fast Medical Image Security Using Color Channel Encryption”. Brazilian Archives of Biology and Technology. Vol. 63, 2020.
  • Venkateswarlu Isunuri, and Jagadeesh Kakarla. ”Fast brain tumour segmentation using optimized U-Net and adaptive thresholding”. Automatika. Vol. 61(3), 2020.
  • Venkateswarlu Isunuri and Jagadeesh Kakarla. ”Password security by encryption using an extended ADFGVX cipher”. International Journal of Information and Computer Security. Inderscience, Vol. 11, 2019.
CONFERENCES
  • Venkateswarlu Isunuri and Jagadeesh Kakarla. ”Alzheimer’s severity classification using Transfer Learning and Residual Separable Convolution Network”. ACM 13th Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP). 2022.
  • Venkateswarlu Isunuri and Jagadeesh Kakarla, ”Brain tumor grade detection using Transfer learning and Residual Multi-head Attention Network”. 7th International Conference on Computer Vision & Image Processing (CVIP). 2022.
  • Venkateswarlu Isunuri, Jagadeesh Kakarla and S. Prakash. ”Face mask detection using MobileNet and Global Pooling Block”. IEEE 4th Conference on Information & Communication Technology (CICT). 2020.

Contact Details

  • E-mail id: bala.v@srmap.edu.in
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