Kiran Vaidhya Venkadesh

Kiran Vaidhya Venkadesh

PhD candidate

Diagnostic Image Analysis Group


👋 Hi! I am a PhD candidate at Radboud University Medical Center. I work within the Diagnostic Image Analysis Group (DIAG), and my research interests revolve around the use of deep learning algorithms for medical image analysis.

🧑🏽‍🎓 I am supervised by Colin Jacobs, Bram van Ginneken, and Mathias Prokop. My PhD thesis is on AI for lung cancer screening, with a focus on early lung cancer detection from low-dose chest CT images. As part of my work at DIAG, I also spend 10% of my time providing support for users of

🛠️ Prior to my PhD, I worked at an early-stage startup called Predible (acquired by nference) for three years, where we developed deep learning algorithms for wrist x-ray, chest CT, and abdomen CT analysis.

✍️ I also volunteer as an editor for The Gradient. I am responsible for outreach, and I help edit articles to make sure they meet the publication standards.

💙 During my free time, I love to play outdoor sports, read books and, occasionally, stargaze.

  • Medical Image Analysis
  • Lung Cancer Screening
  • Computer Vision
  • Deep Learning
  • B.Tech & M.Tech in Engineering Design (Specialization in Biomedical Design), 2016

    IIT Madras


PhD candidate
Nov 2019 – Present Nijmegen, Netherlands
AI for lung cancer screening
VP Engineering
Jun 2017 – Jul 2019 Bangalore, India
Responsible for the development, validation, and deployment of deep learning algorithms for tri-phasic abdomen CT analysis and chest CT analysis
Algorithms Researcher
Jun 2016 – May 2017 Bangalore, India
Developed deep learning algorithms for fracture detection in wrist x-rays, radiology reports, and liver segmentation from abdomen CT images
Department of Engineering Design, IIT Madras
Dual Degree Thesis
Jun 2015 – Apr 2016 Chennai, India
Worked on stacked denoising autoencoders for brain tumor segmentation from MRI
Philips Healthcare
Research Intern
Dec 2014 – May 2015 Pune, India
Developed an image registration tool to align pre-operative and post-operative fluoroscopic images of the spine from mobile C-Arm systems

Recent Publications

(2021). Automated COVID-19 Grading With Convolutional Neural Networks in Computed Tomography Scans: A Systematic Comparison. In IEEE TAI.


(2021). Deep Learning for Malignancy Risk Estimation of Pulmonary Nodules Detected at Low-Dose Screening CT. In Radiology.

Cite DOI

(2020). Automated Assessment of COVID-19 Reporting and Data System and Chest CT Severity Scores in Patients Suspected of Having COVID-19 Using Artificial Intelligence. In Radiology.

Cite DOI

Recent & Upcoming Talks