Kiran Vaidhya Venkadesh

Kiran Vaidhya Venkadesh

Postdoctoral researcher

Diagnostic Image Analysis Group


👋 Hi! I am a postdoctoral researcher at Radboud University Medical Center. I work within the Diagnostic Image Analysis Group (DIAG), and my research interests revolve around the design and development of AI algorithms in radiology. I currently work with Alessa Hering in the COMFORT project.

🧑🏽‍🎓 For my PhD research, I was supervised by Colin Jacobs, Bram van Ginneken, and Mathias Prokop. My thesis is on AI for lung cancer screening, with a focus on early lung cancer detection from chest CT scans. In my first publication, we showed that deep learning algorithms are comparable to clinical experts at predicting lung cancer risk. This story was also covered by the Telegraph. 😊

👥 As part of my PhD research, I spent 10% of my time providing support for users of I also volunteered as an editor for The Gradient. I was responsible for outreach, and I edited articles to make sure they met the publication standards.

🛠️ 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.

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

  • Artificial intelligence
  • Radiology
  • Medical image analysis
  • Lung cancer screening
  • B.Tech & M.Tech in Engineering Design (Specialization in Biomedical Design), 2016

    IIT Madras


Postdoctoral researcher
Nov 2023 – Present Nijmegen, Netherlands
Improving urological cancer care with AI
PhD candidate
Nov 2019 – Oct 2023 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

(2023). Prior CT Improves Deep Learning for Malignancy Risk Estimation of Screening-detected Pulmonary Nodules. In Radiology.

Cite DOI

(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