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Dr. Sakshi Ahuja

Assistant Professor, School of Artificial Intelligence, Amrita Vishwa Vidyapeetham, Faridabad

Qualification: Ph.D
sakshi.ahuja@dl.amrita.edu
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Google Scholar Profile
Research Interest: Medical image analysis, IoT based devices, Computational neuroscience,Deep Learning, Machine Learning

Bio

Dr. Sakshi Ahuja is a dedicated AI and Machine Learning expert with a strong academic foundation and extensive experience in developing innovative AI solutions. Holding a Ph.D. in Electrical Engineering from the prestigious Indian Institute of Technology Delhi (IITD), she has specialized in multi-modal radiographic image analysis using deep learning, focusing on critical applications like brain tumor detection and COVID-19 diagnosis. Driven by the transformative potential of AI in industry and healthcare, she is passionate about advancing research, solving complex problems, and contributing to cutting-edge technologies. She actively seeks collaborations with researchers and industry professionals to push the frontiers of AI and Machine Learning.

Professional Experience : 3 years of teaching and 6 years of regular PhD with TA duty in IIT Delhi
Professional Achievements :Organized IEEE conference in 2018 in LPU (ICICS-2018)

Publications

Book Chapter

Year : 2023

COVID-19 Lung Patch Segmentation Using COVSeg-NET

Cite this Research Publication : Vivek Noel Soren, Sakshi Ahuja, B. K. Panigrahi, Tapan K. Gandhi, COVID-19 Lung Patch Segmentation Using COVSeg-NET, Lecture Notes in Networks and Systems, Springer Nature Singapore, 2023, https://doi.org/10.1007/978-981-99-4284-8_24

Publisher : Springer Nature Singapore

Journal Article

Year : 2022

McS-Net: Multi-class Siamese network for severity of COVID-19 infection classification from lung CT scan slices

Cite this Research Publication : Sakshi Ahuja, B.K. Panigrahi, Nilanjan Dey, Dr. Arpit Taneja, and T.K. Gandhi, "McS- Net: Multi-class Siamese network for the severity of COVID-19 infection classification from lung CT scan slices", Applied Soft Computing, Elsevier, 2022.

Publisher : Elsevier

Year : 2022

Enhanced performance of Dark-Nets for brain tumor classification and segmentation using colormap-based superpixel techniques

Cite this Research Publication : Sakshi Ahuja, B.K. Panigrahi, and T.K. Gandhi, "Enhanced performance of Dark-Nets for brain tumor classification and segmentation using colormap-based superpixel techniques", Machine Learning with Applications, Elsevier, Volume 7, 15 March 2022

Publisher : Elsevier

Year : 2021

Transfer learning–based ensemble support vector machine model for automated COVID-19 detection using lung computerized tomography scan data

Cite this Research Publication : Singh, M., Bansal, S., Ahuja, S. et al., “Transfer learning–based ensemble support vector machine model for automated COVID-19 detection using lung computerized tomography scan data”, Medical & Biological Engineering & Computing, Springer, 2021.

Publisher : Springer

Year : 2020

Deep transfer learning-based automated detection of COVID-19 from lung CT scan slices

Cite this Research Publication : Sakshi Ahuja, B.K. Panigrahi, and T.K. Gandhi, "Deep transfer learning-based automated detection of COVID-19 from lung CT scan slices", Applied Intelligence, Springer, 2020.

Publisher : Springer

Conference Paper

Year : 2021

Deep learning-based computer-aided diagnosis tool for brain tumor classification

Cite this Research Publication : Sakshi Ahuja, B.K. Panigrahi, Tapan Gandhi, Utkarsh Gautam, Deep learning-based computer-aided diagnosis tool for brain tumor classification, 2021 11th International Conference on Cloud Computing, Data Science & Engineering (Confluence), IEEE, 2021, https://doi.org/10.1109/confluence51648.2021.9377171

Publisher : IEEE

Year : 2021

Fully automatic brain tumor segmentation using DeepLabv3+ with variable loss functions

Cite this Research Publication : Sakshi Ahuja, B.K. Panigrahi, Tapan K. Gandhi, Fully automatic brain tumor segmentation using DeepLabv3+ with variable loss functions, 2021 8th International Conference on Signal Processing and Integrated Networks (SPIN), IEEE, 2021, https://doi.org/10.1109/spin52536.2021.9566128

Publisher : IEEE

Year : 2020

Transfer Learning Based Brain Tumor Detection and Segmentation using Superpixel Technique

Cite this Research Publication : Sakshi Ahuja, B.K. Panigrahi, Tapan Gandhi, Transfer Learning Based Brain Tumor Detection and Segmentation using Superpixel Technique, 2020 International Conference on Contemporary Computing and Applications (IC3A), IEEE, 2020, https://doi.org/10.1109/ic3a48958.2020.233306

Publisher : IEEE

Year : 2019

Human Iris Recognition Based on Statistically Matched Wavelet

Cite this Research Publication : Sakshi Ahuja, Utkarsh Gautam, Human Iris Recognition Based on Statistically Matched Wavelet, 2019 9th International Conference on Advances in Computing and Communication (ICACC), IEEE, 2019, https://doi.org/10.1109/icacc48162.2019.8986190

Publisher : IEEE

Year : 2018

Design of Orthogonal Wavelet for Human Palmprint Recognition

Cite this Research Publication : Sakshi Ahuja, Akhil Mehan, Design of Orthogonal Wavelet for Human Palmprint Recognition, 2018 International Conference on Intelligent Circuits and Systems (ICICS), IEEE, 2018, https://doi.org/10.1109/icics.2018.00061

Publisher : IEEE

Year : 2017

Design of semi-orthogonal wavelet for human ear recognition

Cite this Research Publication : Sakshi Ahuja, “Design of semi-orthogonal wavelet for human ear recognition”, International Conference on Trends in Electronics and Informatics (ICEI 2017, IEEE)

Year : 2016

Comprehensive analysis of ear recognition techniques

Cite this Research Publication : Manish K. Saini, J.S. Saini, and Sakshi Ahuja, “Comprehensive analysis of ear recognition techniques”, 2016 Sixth International Conference on Advanced Computing & Communication Technologies

Year : 2016

Design of wavelet using ring- projection technique for the ear

Cite this Research Publication : Manish K. Saini, J.S. Saini, and Sakshi Ahuja, “Design of wavelet using ring- projection technique for the ear”. Sixth International Conference on Advanced Computing & Communication Technologies, Rohtak (2016).   

Talks Delivered

Research Talks Delivered

  • School of Computing and Information Technology REVA UNIVERSITY Bangalore is organizing a Faculty Development Program (FDP) on 26TH July, 2024

Invited Talks

  • Role of AI in industry at JMIT Radaur, Haryana on 20 May, 2020.
Awards

Gold medalist in B.Tech from Kurukshetra University

Ph. D. Guidance/ Co-Guidance
  • Ms. Priyanka- Brain Tumor Diagnosis using AI Tools
  • Mr. Nighil – Respiratory Diseases Analysis using Chest CT Scan
Courses Taught for UG/ PG/ Ph. D.

UG

  • Introduction to Electronics
  • Introduction to Electrical Engineering

PG

  • Machine learning and Deep learning based biomedical data management
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