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 Reality, Fakultät für Informatik, Technische 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
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.