Dr Anuradha KAR

Associate Professor of AI & Robotics
Dr. Anuradha KAR

Biography

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

Education & Qualifications

YearUniversityQualification/Position
2015–2019 National University of Ireland, Galway Doctor of Philosophy, Electrical and Electronic Engineering
2009–2011 University of Calcutta, India Master of Technology, Specialisation: Radio, Physics & Electronics
2005–2009 West Bengal University of Technology, India Bachelor of Technology, Electronics and Communications

Work experience

YearPosition
September 2024 Associate Professor in AI and Robotics at aivancity. Specialising in deep learning, computer vision, explainable AI, AI for healthcare and human-machine interactions.
October 2021–August 2023 Institut du Cerveau (Paris)/ Researcher
June 2019 – September 2021 École Normale SupĂ©rieure de Lyon / Researcher
May 2015 – May 2019 National University of Ireland, Galway / PhD student
November 2013 – April 2015 German Aerospace Centre / Research Assistant
March 2012–July 2013 Max Planck Institute for Solar System Research / Research Assistant

Projects

YearRole
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. HaĂŻk, 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)
  • Kar A, 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. 14 April 2022;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 Performance Evaluation of Eye-Tracking Systems. Vision, October 2019, 3, 55. (CiteScore 2.3)
  • A. Kar 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 with Quantitative Metrics and Visualisations’. *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).

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