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New Professor in computational interaction

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Published on Monday, 29 March 2021

Luis Leiva recenlty joined the Department of Computer Science at the University of Luxembourg as Associate Professor in the fields of machine learning and human-computer interaction.

Luis Leiva shares his background, former experience and explains his future challenges.

1) Could you introduce yourself?

"I do multidisciplinary research at the intersection of Human-Computer Interaction and Machine Learning. I combine computational thinking with data-driven models and methods to enable, explain, and support user interaction. I hold two undergraduate degrees (Industrial Design and Industrial Engineering), an MSc in Electrical Engineering, an MAS in Pattern Recognition and Artificial Intelligence, and a PhD in Computer Science. I am also the co-founder and former director of technology of Sciling, an SME agency specialised in B2B Machine Learning solutions. Previously I was a postdoctoral scholar at Aalto University (Finland) and even before I was a research fellow of the PRHLT Research Center at the Technical University of Valencia (Spain)."

2) Why did you join the University of Luxembourg?

"There are several reasons. First of all, the University of Luxembourg provides an excellent research environment, which will help me build my own team. Second, most of the national research priorities for Luxembourg are very well aligned to my own research, including for example fundamental tools and data-driven modeling and simulation, cyber-physical systems, and personalised healthcare. Third, there is a great team of research facilitators and many opportunities to apply for funding at the Fonds National de la Recherche (FNR). Finally, interdisciplinarity and cross-institutional cooperation is highly encouraged, which is further facilitated by the fact that Luxembourg is strategically situated in the middle of Europe. Taken together, these aspects put the University of Luxembourg in an interesting position as a modern, multilingual, and multidisciplinary institution." 

3) What will be your main activities?

"My mission is to train the next generation of industry practitioners and researchers in computational interaction. I plan to accomplish that mission via the usual duties of a university professor: research, teaching at bachelor and master's programmes, international project collaborations, dissemination of knowledge, technology transfer, and management. These activities will keep attracting talented students and researchers, which in turn will promote the excellence of the University of Luxembourg. 

My current research agenda is focused on artificial data generation, as a practical way to lower the costs of collecting and labeling large amounts of human data. For example, I have been using kinematic motor control models of aimed movements to synthesise stroke gestures that possess human-like characteristics and that can generalise across user populations. Another research topic I am actively pursuing is the decoding of biological signals from implicit interactions. For example, I have developed computational models of mouse movements to predict user engagement, attention to advertisements, and demographics. There are plenty of practical applications that can be developed with these models, from self-adapting user interfaces to novel biometric measures." 

4) What will be your key challenges? 

"My main challenge at present is building my research team, for which I plan to recruit talented and motivated students as well as postdoctoral researchers. Another key challenge is related to teaching: I have completed several courses on pedagogical training, so I plan to put into practice many ideas about modern education for bachelor and master's students. 

Looking forward into the future, I am very interested in a host of computational problems involving Human-Computer Interaction and Machine Learning. I plan to investigate deep generative models of human movements, which have potential to enable higher learning capacity and to generalize better. The ultimate goal is to support realistic simulation of individual-level movement styles, which will hopefully result in fruitful research collaborations and joint publications."