Saptakatha Adak

AI Researcher

Bengaluru, Karnataka, India8 yrs 10 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in Computer Vision and Deep Learning.
Published multiple papers in renowned conferences.
Developed AI models improving clinical workflow efficiency.

Stackforce AI infers this person is a Healthcare AI Specialist with expertise in Computer Vision and Deep Learning.

Contact

saptakatha2@gmail.com LinkedIn

Skills

Core Skills

Computer VisionDeep Learning

Other Skills

CC (Programming Language)Convolutional Neural Networks (CNN)Deep Neural Networks (DNN)GitHTMLImage ProcessingKerasLaTeXMachine LearningMathematicsMatlabMedical ImagingOral CommunicationPHP

About

-- Research Scientist responsible for working on Computer Vision and Natural Language Processing problems involving electronic health records in form of visual (medical images in form of MR/CT scans) as well as textual data. -- Computer Vision Researcher experienced in working on challenging and modern problems such as Video Object Segmentation, Semantic segmentation in adverse scenarios for Autonomous systems, etc. --Publication in several conferences in the fields of Computer Vision and Machine Learning. -- Skilled in Python, C++, PyTorch, Keras, Tensorflow, OpenCV, MATLAB, etc. -- Strong research professional with a Master's Degree (MS by research) focused on Computer Vision from Indian Institute of Technology Madras.

Experience

8 yrs 10 mos

Total Experience

2 yrs 11 mos

Average Tenure

4 yrs 1 mo

Current Experience

Philips

Research Engineer (Data Scientist)

May 2022 – Present · 4 yrs 1 mo · Bengaluru, Karnataka, India · On-site

Designed Deep Learning based algorithms to build a multi-vendor robust pipeline for segmentation and severity grading of prostate cancer lesions using pyradiomics features extracted from multi-parametric MR image sequences.
Developed AI-based models to set up an automated pipeline for liver and cancer tumour segmentation and characterization for severity prediction from multi-phase CT images.
Evaluated and analyzed both the qualitative and quantitative performance of the developed models as well as optimized them to decrease the inference time by maintaining the quality and reliability of the algorithms.
Deployed and integrated the machine learning models as AI-enabled features in the proprietary visualization software by collaborating with cross-functional teams. Reduced clinician’s diagnosis and report generation time by ∼20%.
Collaborated with the clinicians to understand their requirements and devise ways to increase product scope, quality and customer experience. Worked closely with the consortium hospitals to acquire raw data and collaborated with radiologists for data annotation and validation.
Participated in mentoring a group of software engineers within the organization in Machine learning and Medical Imaging to help them progress in their professional careers.

Computer VisionDeep Learning

Buddi ai

2 roles

Research Scientist

Promoted

Jul 2021 – May 2022 · 10 mos

Responsible for research on problems involving Electronic Health Records (EHRs) in the form of image and text data.
Developed and deployed deep learning based framework to detect the presence of COVID-19 infections in the lung CT scans and estimate severity of infections in COVID-19 positive cases (predicting CoRADS grading) jointly.
Designed OCR pipeline containing text detection and recognition models to localize and extract text contents from image-based EHR scans, to be used as input for other text-based downstream tasks.

Computer VisionDeep Learning

Junior Research Scientist

Jul 2020 – Jun 2021 · 11 mos

Worked on approaches for automatically segmenting medical codes across different domains to extract information in a structured manner leveraging graph-based techniques and methods like relation extraction with custom knowledge bases.
Worked on multiple cross-team projects involving Scientists, Software Development Engineers and Product Managers.

Computer VisionDeep Learning

Indian institute of technology, madras

Research Scholar

Jul 2016 – Jul 2019 · 3 yrs · Greater Chennai Area

Worked as an MS research scholar in Visualization and perception Lab, IIT Madras under Prof. Sukhendu Das on Video Object Segmentation and Scene segmentation in adverse scenarios problems.
Published research works in both national and internationally renowned conferences.
Thesis title: Video Object Segmentation using Adversarial Techniques
Achievements:
Best Student Paper Award @ ICONIP-2019
Top 10% paper @ ICIP-2019
IAPR Best Student Paper Award @ CVIP-2018

Computer VisionDeep Learning