Dr. Anuradha KAR

Associate Professor of AI & Robotics
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Dr. Anuradha KAR

Biography

Anuradha KAR, an Associate Professor of AI and Robotics at Aivancity, earned a Ph.D. in Electrical and Electronic Engineering from the University of Galway in Ireland.She then worked at ENS Lyon in collaboration with Inria and InraE on deep learning for the analysis of 3D biological images, before joining the Paris Brain Institute with Inria to work on deep learning for the analysis of data from patients with Alzheimer’s disease, and the Pasteur Institute in Paris on deep learning applications in drug discovery. She is particularly interested in deep learning applications in computer vision, computational biology, and healthcare, as well as human-machine interactions and intelligent systems.

 

Education & Degrees

YearUniversityDegree/Position
2015–2019    National University of Ireland, Galway    Ph.D. in Philosophy, Electrical and Electronic Engineering
 
2009–2011    University of Calcutta, India    Master of Technology, Specialization: Radio, Physics & Electronics
2005–2009    West Bengal University of Technology, India    Bachelor of Technology in Electronics and Communications

Professional experience

YearFunction
September 2024    Associate Professor of AI and Robotics at aivancity. Specializes in deep learning, computer vision, explainable AI, AI for healthcare, and human-machine interactions.
October 2021–August 2023    Brain Institute (Paris)/ Researcher
 
June 2019 – September 2021    École Normale Supérieure de Lyon / Researcher
May 2015 – May 2019    National University of Ireland, Galway / PhD Student
November 2013 – April 2015    German Aerospace Center / Research Assistant
 
March 2012–July 2013    Max Planck Institute for Solar System Research / Research Assistant

Projects

YearFunction
2024Transformers and Explainable AI for Computer Vision
 
2021Transfer Learning for DICOM Image Classification
 
2016    Emotion Recognition Using SVM Models

Publications

  • YF. Mareuil, A. Moine-Franel, A. Kar, M. Nilges, C.B. Ciambur, O. Sperandio, Protein Interaction Explorer (PIE): A Comprehensive Platform for Navigating Protein-Protein Interactions and Ligand Binding Pockets, Bioinformatics, 2024;, btae414,(Impact Factor 7.6)
  • L. Ingrassia, S. Boluda, M. C. Potier, S. Haïk, G. Jimenez, A. Kar, D. Racoceanu, B. Delatour, L. Stimmer, Automated deep learning segmentation of neuritic plaques and neurofibrillary tangles in Alzheimer's disease brain sections using proprietary software, Journal of Neuropathology & Experimental Neurology, 2024;, nlae048, (Impact Factor 3.2)
  • KarA, Petit M, Refahi Y, Cerutti G, Godin C, Traas J. Benchmarking of deep learning algorithms for 3D instance segmentation of confocal image datasets. PLoS Comput Biol. 2022 Apr 14;18(4):e1009879. (Impact factor 4.7)
  • A.Kar MLGaze: Machine Learning-Based Analysis of Gaze Error Patterns in Consumer Eye Tracking Systems. Vision 2020, 4, 25.. (Citescore 2.3)
  • A. Kar and P. Corcoran. “Development of Open-Source Software and Gaze Data Repositories for the Performance Evaluation of Eye-Tracking Systems.” *Vision*, October 2019, vol. 3, no. 55. (CiteScore 2.3)
  • A. Karand and P. Corcoran, "GazeVisual: A Practical Software Tool and Web Application for Performance Evaluation of Eye Tracking Systems," in IEEE Transactions on Consumer Electronics, vol. 65, no. 3, pp. 293–302, Aug. 2019. (Impact factor 4.3)
  • J. Lemley, A. Kar, A. Drimbarean, and P. Corcoran, "Convolutional Neural Network Implementation for Eye-Gaze Estimation on Low-Quality Consumer Imaging Systems," in IEEE Transactions on Consumer Electronics, vol. 65, no. 2, pp. 179–187, May 2019 (Impact Factor 4.3)
  • A. Kar, P. Corcoran, "Performance Evaluation Strategies for Eye Gaze Estimation Systems Using Quantitative Metrics and Visualizations." Sensors 2018, 18, 3151. (Impact Factor 3.7)
  • A. Kar and P. Corcoran, "A Review and Analysis of Eye-Gaze Estimation Systems, Algorithms, and Performance Evaluation Methods in Consumer Platforms," in IEEE Access, vol. 5, pp. 16495–16519, 2017. (Impact factor: 3.4)
  • S. Bazrafkan, A. Kar, and C. Costache, "Eye Gaze for Consumer Electronics: Controlling and Commanding Intelligent Systems," in IEEE Consumer Electronics Magazine, vol. 4, no. 4, pp. 65–71, Oct. 2015. (Impact factor 4.5).

See also