My research lies at the intersection of computational mathematics and machine learning for applications to large-scale real world problems. My central research is to develop new data-driven algorithmic techniques that allow computers to gain high-level understanding from vast amounts of data, this, with the aim of aiding the decisions of users. These methods are based on mathematical modelling and machine learning methods.
Keywords: 
Publications
Sliding to predict: vision-based beating heart motion estimation by modeling temporal interactions.
– International journal of computer assisted radiology and surgery
(2018)
13,
353
(doi: 10.1007/s11548-018-1702-1)
Peekaboo-Where are the Objects? Structure Adjusting Superpixels
– Proceedings - International Conference on Image Processing, ICIP
(2018)
00,
3693
(doi: 10.1109/icip.2018.8451822)
Robust cardiac motion estimation using ultrafast ultrasound data: a low-rank topology-preserving approach.
– Phys Med Biol
(2017)
62,
4831
(doi: 10.1088/1361-6560/aa6914)
Towards Retrieving Force Feedback in Robotic-Assisted Surgery: A Supervised Neuro-Recurrent-Vision Approach.
– IEEE Trans Haptics
(2016)
10,
431
(doi: 10.1109/TOH.2016.2640289)
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