Ismail Elezi


New: From February 2020, I am joining NVIDIA as a Deep Learning Software Intern. I will be interning with Jose M. Alvarez in Santa Clara.

I am a third-year Ph.D. Student of Deep Learning, supervised by professor Marcello Pelillo at Ca' Foscari, University of Venice. While my master thesis was in Graph Theory, like most of the other young machine learning scientists, I switched to the Deep Learning side. My first year was spent mostly on studying deep learning and doing some lite research in semi-supervised deep learning. 

In the second year of my Ph.D., I did a one year exchange period at ZHAW Datalab (Switzerland) working with professor Thilo Stadelmann. Together with Lukas Tuggener, we significantly improved state-of-the-art results in musical object detection. Our ISMIR paper (in collaboration with Jurgen Schmidhuber) presents a new algorithm designed for musical object detection.

In the third year of my Ph.D., I changed countries again. From January 2018, I am a visiting Ph.D. student in the lab of professor Laura Leal-Taixe at the Technical University of Munich (TUM). I must say that I am having the best time of the Ph.D. here in Munich and with Laura (and her other students/visitors) I am working in different problems like deep metric learning, active learning, and generative adversarial networks.

I did my master's degree at Ca' Foscari, University of Venice, with my master thesis being supervised by professor Marcello Pelillo.  And at the beginning, I did my bachelor studies at the University of Prishtina, Kosovo.

I am proficient in developing and using Deep Neural Networks on both industrial and research applications, on traditional machine learning, algorithms, and mathematics.

I have developed a hands-on MOOC about Deep Learning with PyTorch for DataCamp. The course can be found here.


Elsewhere


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