Kiran Vaidhya Venkadesh

Kiran Vaidhya Venkadesh

Postdoctoral researcher

Radboudumc

👋 I am Kiran. I am an entrepreneur in Radiology AI. I work as a postdoctoral fellow in the 2nd edition of the NWO Faculty of Impact, and I’m based out of Radboud University Medical Center. My interests revolve around the design and development of AI algorithms for radiology.

🧑🏽‍🎓 I completed my PhD research under the supervision of Colin Jacobs, Alessa Hering, Bram van Ginneken, and Mathias Prokop. I defended my PhD thesis on AI for lung cancer screening in May 2024. In my first publication, we demonstrated that deep learning algorithms can predict lung cancer risk as effectively as clinical experts. This work was also featured by the Telegraph. 😊 After my PhD, I briefly collaborated with Alessa Hering on the COMFORT project.

During my PhD, I dedicated 10% of my time to supporting users of grand-challenge.org. Additionally, I volunteered as an editor for The Gradient, where I managed outreach and ensured articles met publication standards.

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

💙 In my free time, I enjoy playing outdoor sports, reading books, and occasionally stargazing.

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

    IIT Madras

Experience

 
 
 
 
 
Radboudumc
Postdoctoral researcher
Jun 2024 – Present Nijmegen, Netherlands
Fellow at the Faculty of Impact
 
 
 
 
 
Radboudumc
Postdoctoral researcher
Nov 2023 – May 2024 Nijmegen, Netherlands
Improving urological cancer care with AI
 
 
 
 
 
Radboudumc
PhD candidate
Nov 2019 – Oct 2023 Nijmegen, Netherlands
AI for lung cancer screening
 
 
 
 
 
Predible
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
 
 
 
 
 
Predible
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.

PDF Cite DOI

(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