This thesis shows how NLP Deep Learning methods, trained on user interactions sequences at H&M website, can be used to model user behavior and create personalized recommendations. We performed multiple experiments to prove how an ordered user history helps the model learn. Both item and user representations proved themselves to play an important role in our model's performance. New models won at performance but also saw different patterns on recommended items, recommending less popular items, and more expensive than our baseline model. We believe it is the powerful representation learning and the ability to capture order within sequences that are responsible for the performance improvements.

This blog post describes the TRIC model -- an architecture for Relative Image Captioning task that was created as a part of my Master Thesis. All of them are described in my thesis in a pretty concise way so I highly recommend it -- you can find a link right below. But if you want to check them from another source it is also covered. To each of the topics listed above, I have attached a link to my personal favorite resource concerning this particular subject. Earlier this month I defended my master's thesis in Computer Science at the Warsaw University of Technology.

Cooperation and collaboration robots, co-robots or cobots for short, are an integral part of factories. For example, they work closely with the fitters in the automotive sector, and everyone does what they do best. However, the novel robots are not only relevant in production and logistics, but also in the service sector, especially where proximity between them and the users is desired or unavoidable. For decades, individual solutions of a very different kind have been developed in care. Now experts are increasingly relying on co-robots and teaching them the special tasks that are involved in care or therapy. This article presents the advantages, but also the disadvantages of co-robots in care and support, and provides information with regard to human-robot interaction and communication. The article is based on a model that has already been tested in various nursing and retirement homes, namely Lio from F&P Robotics, and uses results from accompanying studies. The authors can show that co-robots are ideal for care and support in many ways. Of course, it is also important to consider a few points in order to guarantee functionality and acceptance.

Here I will be posting some of the data science and machine learning projects that I have been working on. The main motivation for making this blog is that I will soon be starting the Fast AI Deep Learning course. Blogging along with the lectures seemed like a great opportunity for me to be really hands-on with the material and get acquainted with other students. Let me first start by giving you a quick background of my journey into data science. About a year ago I started writing my master thesis for the study Business Administration.

Every year our HCI research group defines a number of Master thesis topics for Computer Science and Engineering students. Our topics include data visualisation, recommender systems, augmented reality, learning analytics, and e-health. As my expertise is data visualisation, and video games have always held a special place in my heart, it only made sense to merge the two. That's why this year we have two Master students working on "Designing live data visualisations for the new spectator sport: video games". The general idea is to use live (interactive) visualisations during a game to help a specific audience get a better understanding of and new insights in what is going on.

Interested in the research on machine learning and time-series analysis algorithms able to process big data in an efficient, adaptive, and robust way. Currently focused on their application to Cognitive Stimulation and Rehabilitation (see Innobrain and Cognitio projects) and Autism Spectrum Disorders (see AMATE project). Another topic of my interest is the use of Machine Learning techniques to reason and learn about musical processes like expressive music generation. Currently focused on the study of musical expressivity in Nylon Guitars (see guitarLab) and social tools for music education (see PRAISE). We have studied the issue of expressiveness in the context of tenor saxophon interpretations (see Saxex and TempoExpress systems) in collaboration with the Music Technology Group (UPF).