Computer Laboratory

Aliaksei Mikhailiuk

I am a PhD student at the Computer Laboratory, working under the supervision of Dr. Rafal Mantiuk. I can be contacted at: am2442[at]cam[dot]ac[dot]uk.

Research

My current research is focused on applications of Machine Learning to a problem of modelling Human Visual System. I am particularly interested in Deep Learning and Bayesian Inference. However my general interest is not constrained by these.

Supervising

I have supervised or am supervising for:


In the past I have supervised Part IB/II students and have a few ideas for Part II/MPhil projects in machine learning, multimedia experience and computer vision. If you want to discuss possible supervision, please drop me an email.

Before

Before starting a PhD I did an MPhil in Scientific Computing at Cambridge. During this time I was working under the supervision of Dr. Anita Faul on the dissertation entitled “Deep Learning and Parallelisation Applied to Seismic Data”. Before joining Cambridge I did a BEng in Computer Science and Electronics at the University of Bristol.

Publications

Perez-Ortiz M., Mikhailiuk A., Zerman E., Hulusic V., Valenzise G. and Mantiuk R., 2018. "From pairwise comparisons and rating to a unified quality scale". In: Transactions on Image Processing (TIP) 2018. IEEE (Under review)

Mikhailiuk A., Perez-Ortiz M. and Mantiuk R., 2018. "Psychometric scaling of TID2013 dataset" . In: International Conference on Quality of Multimedia Experience (QoMEX) 2018. IEEE
github dataset bibtex

Mikhailiuk A. and Faul A., 2018. "Deep Learning Applied to Seismic Data Interpolation". In: European Association of Geoscientists and Engineers (EAGE) 2018. IEEE
github bibtex

Mikhailiuk A.. and Dahnoun N., 2016. "Real-time pothole detection on TMS320C6678 DSP" . International Conference on Imaging Systems and Techniques (IST), 2016. pp 123-128. IEEE
github bibtex

Blog posts and media coverage

Unsupervised deep learning for data interpolation

Usefull links

37 Reasons why your Neural Network is not working

28 Jupyter Notebook tips, tricks, and shortcuts

A Simple Guide to the Versions of the Inception Network

The hacker's guide to uncertainty estimates

Software to plot DNN's architectures

Address

SS04, William Gates Building, 15 J J Thomson Ave, Cambridge CB3 0FD

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