Sindhura C

Senior Engineer (ML), Qualcomm

I am Sindhura.

Currently, I'm working as senior Engineer in Qualcomm, Hyderabad. Here we as a R&D team, we are trying to develop a Continuous blood pressure monitoring device and interesting that it is going to be a wearable strap kind of device. We use "photo-acoustic plethysmography" signals acquired from wrist and then do lot of data analysis, extract important features and then use machine learning to predict the BP.

I did my PhD in the field of Medical Image Analysis under the guidance of Prof. Subrahmanyam Gorthi in the Department of Electrical Engineering at the Indian Institute of Technology (IIT) Tirupati. I developed novel frameworks for "Diagnosis of Intracranial Hemorrhages in head CT scans" using deep learning methods.

I completed my M.Tech from the Department of Electrical Engineering at the Indian Institute of Technology, Design & Manufacturing in Jabalpur (IITDM Jabalpur).

Prior to my M.Tech, I worked as a systems engineer in the domain of software quality assurance in Tata Consultancy Services, Bangalore, after my Bachelors.

PhD (Aug 2018 - Dec 2023 ) IIT Tirupati

MTech (Aug 2016 - Jul 2018 ) IIITDM Jabalpur

Research Interests:

Medical Image Analysis, Deep learning, Segmentation and classification tasks, Machine learning

Publications:

2024

C. Sindhura, S. Gorthi, "Clinical knowledge aware synthesized CT image-based framework for improved detection and segmentation of hemorrhages." Pattern Recognition Letters, 2024. doi: https://doi.org/10.1016/j.patrec.2024.11.028

2023

C. Sindhura, M.Al. Fahim, PK. Yalavarthy and S. Gorthi., “Sinogram-based Deep Learning Method with Intensity Transformation Module for Detection of Intracranial Hemorrhages”, Journal of Medical Physics, 2023. https://doi.org/10.1002/mp.16714
J. Li, D. G. Ellis, ..., S. Pathak, C. Sindhura, RKS Gorthi, D. V. Kiran, S. Gorthi et al., “Towards clinical applicability and computational efficiency in automatic cranial implant design: An overview of the AutoImplant 2021 cranial implant design challenge”, in Medical Image Analysis, vol. 88, num. p. 1-15, Aug. 2023. https://doi.org/10.1016/j.media.2023.102865

2022

C. Sindhura, H. V. R. Vengama, and S. Gorthi., “Efficient-PSP-Net: A Lightweight Model for the Segmentation of Liver and Tumor in CT Scans”, 13th Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP 2022), Gandhinagar, India, Dec 2022. https://doi.org/10.1145/3571600.3571642
P. Lankireddy, C. Sindhura, and S. Gorthi., “A New Lightweight Architecture and a Class Imbalance Aware Loss Function for Multi-label Classification of Intracranial Hemorrhages”, 13th MICCAI Workshop on Machine Learning in Medical Imaging (MLMI), Singapore, Sep 2022. https://doi.org/10.1007/978-3-031-21014-3_41

2021

S. Pathak, C. Sindhura, R. K. S. Gorthi, V. K. Degala, and S. Gorthi., “Cranial Implant Design Using V-Net Based Region of Interest Reconstruction”, Second MICCAI challenge on cranial implant design (AutoImplant2021), Lecture Notes in Computer Science, vol 13123, 116-128, 2021. http://dx.doi.org/10.1007/978-3-030-92652-6_10

2019 and before

C. Sindhura, Prateeksha Sharma, Dinesh Kumar V, "Stub Filter based on Hybrid Metal Insulator Metal Plasmonic Waveguide," Workshop on Recent Advances in Photonics (WRAP), Hyderabad, Dec-2017.
C. Sindhura, Sharma, P. and Vishwakarma, D.K. (2018), Sinusoidal Bragg grating based on hybrid metal insulator metal plasmonic waveguide. Micro Nano Lett., 13: 1633-1637. https://doi.org/10.1049/mnl.2018.5107
Srivastava, K., C. Sindhura, Sharma, P. and Vishwakarma, D.K., Investigation of Bragg gratings in planar hybrid metal–insulator–metal plasmonic waveguide using a graded profile. Micro Nano Lett., 14: 1117-1120. https://doi.org/10.1049/mnl.2019.0201

Awards/Funding:

Received “Honorable Mention Award” for participating in the challenge INSTANCE 2022 organized by Medical Image Computing and Computer-Assisted Intervention (MICCAI 2022), September 2022.
Received MICCAI Society Main Conference Participation grant to attend the MICCAI conference in Singapore (September 2022).

Teaching Activities:

Basic Electrical Engineering Course (BEE1100, ES1210) in 2018, 2019
Medical imaging (EE5029) in 2019, 2020, 2021
Computer Vision (EE5113) in 2020, 2021
Machine Learning for Image Processing and Lab (EE5204, EE5294) - 2022
Advanced Signal Analysis and Processing, Course (EE527P), Lab (EE527L) - 2022
Signals and Systems (EE205L) - 2023

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