Anees Kazi



Dr. rer. nat. Anees Kazi

Informatics 16 - Chair of Computer Aided Medical Procedures (Prof. Navab)

Postal address

Postal:
Boltzmannstr. 3
85748 Garching b. München

Research Interests

  • Geometric Deep Learning
  • Machine Learning: Deep Learning, Image Retrieval
  • Modalities: OCT, Histology, X-Ray, MR

Curriculum Vitae

  • *Ph.D. in Graph Deep Learning for Healthcare Applications.
  • Masters of Technology - (2016) in Medical Imaging and Informatics, Indian Institute of Technology, Kharagpur, INDIA
  • Bachelor of Engineering - with honors (2013) in Electronics and Telecommunication, Dr.Babasaheb Ambedkar Technological University, Lonere, INDIA

Awards

  • MICCAI Student Board Incentive 2020 - Awarded by MICCAI 2020.
  • Graduate Student Travel Award 2019 - Awarded by MICCAI 2019.
  • TUM Global Incentive Award 2019 - Awarded to collaborate with Dept. of Computing at Imperial College of London.
  • Scholarship from Freunde und F{\"o}rderer der Augenklinik, M{\"u}nchen, Germany Feb. 2017- Feb. 2020 - Awarded to pursue Ph.D. jointly at Technical University of Munich and Augenklinik, M{\"u}nchen by
  • Elsevier Medical Image Analysis Best Paper Award, MICCAI 2016 for the paper on Metric Hashing Forests (Second Author).
  • Deutscher Akademischer Austauschdienst (DAAD) (Bonn, GERMANY) Scholarship, Sep. 2015 - Mar. 2016 - Awarded to pursue Master's Thesis at Chair for Computer Aided Medical Procedures & Augmented RealityFakultät für InformatikTechnische Universität München.
  • Ministry of Human Resources and Development, Government of India Scholarship for pursuing graduate studies in Medical Imaging and Informatics after qualifying Graduate Aptitude Test in Engineering. 2014-2016
  • Best student award - Awarded by Sojar English School Barshi for all round performance. 2007

Professional Associations and Memberships

  • MICCAI Student Board- President 2020
  • IEEE Student Member
  • MICCAI Student Board- Memeber 2019

Reviewer

  • NeurIPS? 2020
  • Medical Image Computing & Computer Assisted Intervention 2020
  • Neurocomputing
  • IEEE Transactions on Medical Imaging
  • Medical Image Computing & Computer Assisted Intervention 2019
  • Medical Image Computing & Computer Assisted Intervention 2018

Publications

Projects

  • Analysis of graph-based methods for deep learning - application of graph convolutional network to disease prediction in the multi-graph setting.
  • Automatic Classification of the femur and distal radius fracture - Developing deep learning based models for classification and detection of fracture. The main focus of this project is to explore the attention models to localize and classify the fractures in X-ray images.
  • Deep learning for Ophthalmology - Main focus of this project is developing deep learning method for retinal disease classification. We work on real data from Augen Klinik Munich.
  • Deep Learning for medical image analysis.