Seminars take place at UPF, Campus Poblenou, Roc Boronat, 138, Barcelona and will only be streamed/recorded if the speaker has granted permission. Rooms 55.309 / 55.410 streaming / Auditorium streaming
EiTIC members: If you are interested in giving a Research Seminar or you would like to invite a speaker, please fill in the following form RSDetails Form.
Upcoming Invited and PhD seminars 2020
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February, 17
11.00
55.309 |
Invited Research Seminar By Dr. Mehran Ebrahimi, Ontario Tech University, Canada Inverse Problems in Image Processing Abstract: In many practical problems in the field of applied sciences, the features of most interest cannot be observed directly, but have to be inferred from other, observable quantities. The problem of solving an unknown object from the observed quantities is called an inverse problem. Many classical problems in imaging can be modelled as inverse problems. Many real-world inverse problems are ill-posed, mainly due to the lack of existence of a unique solution. The procedure of providing an acceptable unique solution to such problems is known as regularization. Indeed, much of the progress in image processing in the past few decades has been due to advances in the formulation and practice of regularization. This, coupled with the progress in the areas of optimization and numerical analysis, has yielded much improvement in computational methods of solving inverse imaging problems. In this talk, we will revisit a number of inverse problems including image registration (alignment), image inpainting (completion), super-resolution (resolution enhancement), and present some recent research ideas mainly aimed at medical imaging applications. Furthermore, we present an approach based on deep convolutional neural networks to address two image restoration problems, image inpainting and super-resolution. The method applies our so-called “Edge-Connect”, a two-stage adversarial model that contains an edge generator followed by an image completion network. We evaluate the model and observe that it outperforms current state-of-the-art techniques quantitatively and qualitatively. Bio: Dr. Mehran Ebrahimi is an Associate Professor in the Faculty of Science at Ontario Tech University in Canada, where he is directing the Imaging Lab. He received his PhD in Applied Mathematics in the area of inverse problems in imaging from the University of Waterloo, Canada, in 2008. He was an NSERC postdoctoral fellow at Sunnybrook Hospital and Dept. of Medical Biophysics at the University of Toronto during 2008-2012. Since 2013, he has been a faculty member of Modelling and Computational Science at Ontario Tech. His research interests include medical image analysis, inverse problems, computer-assisted surgery and computer vision. Host: Miguel Ángel González Ballester |
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February, 17
15.30
55.309 |
Invited Research Seminar By Rafael Caro Repetto, Institute of Ethnomusicology, Kunstuniversität Graz, Austria. Technology for aiding understanding of music cultures: The Musical Bridges project Abstract: We live in an increasingly connected world. People, objects, customs, behaviors, ideas, and also sounds, travel with ever growing speed and scope. As a result, multiculturality is an unavoidable condition of contemporary societies. However, the cohabitation in a particular local community of elements from external origins do not necessarily imply their mutual understanding, and even acceptance. In this project we aim at using technology for building Musical Bridges between cultures. A musical tradition is deeply rooted in the thought systems, religious ideas, aesthetic principles, social structures and economic trends of the communities that developed it. Therefore, unraveling the elements of a musical system can aid the understanding of its originating culture. Furthermore, being able to experience them in musical performance allows the embodiment of their underlying cultural phenomena. Existing materials for approaching alien musical cultures are mostly addressed to students or scholars, and in their vast majority consist in written explanations illustrated with accompanying audio or video recordings. Thus, a gap remains between aural perception and intellectual comprehension, generally only addressed via music scores. In Musical Bridges we design interactive, online tools which offer as intuitive as possible visualizations of selected musical aspects from audio recordings with the aim of guiding the user’s listening attention, and her/his bodily engagement with the listening experience. To this aim, we draw on the audio recordings corpora gathered in the previous CompMusic project for the computational study of North Indian and South Indian classical music, Turkish makam music, Chinese jingju music and Moroccan Andalusian music. The visualizations offered by the Musical Bridges tools, tailored to the specific characteristics of each of these music traditions, are based on automatically extracted features using audio signal processing methods, as well as manual annotations by experts. Adopting an approach that could be framed as applied computational musicology, the Musical Bridges project also organizes public educational activities to put these tools, and the project’s philosophy, in action, and bring these music traditions, and their corresponding cultures, closer to the Barcelona audience. In this presentation, I report about, and demonstrate, the current state of the research carried out in the Musical Bridges project. Bio: Rafael Caro Repetto is an ethnomusicologist specialized in Chinese traditional music. After several years of research in Beijing and Shanghai, he obtained a master’s degree in ethnomusicology at Soas (University of London). In 2013 he joined the CompMusic project at the Music Technology Group from Universitat Pompeu Fabra, focusing on jingju music research. In 2018 he received his Ph.D. degree with a thesis on computer aided analysis of the jingju’s melodic system. Currently, Rafael Caro is a senior scientist at the Institute of Ethnomusicology from Kunstuniversität Graz (Austria), and member of the Musical Bridges project, extending his research scope to Indian classical music and Moroccan Andalusian music. Host: Xavier Serra |
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February, 20
15.30
55.309 |
PhD Research Seminar By Alastair Porter Software development best practices for research reproduceability Abstract: In software development it is considered a best practice to test code, include documentation, use source code management tools, and make frequent backups. A lot of the time technical research tends to eschew these best practices, resulting in missing data, hard to reproduce results, and wasted time. For researchers who haven't worked in or studied software engineering roles, it can often be confusing to know where to start, or how these best practices improve code quality and save time. In this talk I will show some examples why software engineering best practices are a valuable part of technical research and how to start applying them if you do not know what tools and resources are available. Bio: I'm a developer in the Music Technology Group at the Universitat Pompeu Fabra in Barcelona, Spain. I specialise in developing bespoke software in collaboration with academic researchers to help complete and promote their research, and providing technical and development support to the department. I received my MA at McGill University working in the Distributed Digital Music Archives and Libraries lab |
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February, 27
15.30
55.309 |
PhD Research Seminar By Simone Tassani Statistical course and Design of Experiments - course composed on 6 2-hour sessions The course of statistics aims to introduce a number of tools for master/Ph.D. students and post docs. The presented tools will play a role in planning many kind of studies, properly analyse the results and understand if data analysed by other researchers are or not reliable. Bio: Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group. |
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March, 3
15.30
55.309 |
PhD Research Seminar By Simone Tassani Statistical course and Design of Experiments - course composed on 6 2-hour sessions The course of statistics aims to introduce a number of tools for master/Ph.D. students and post docs. The presented tools will play a role in planning many kind of studies, properly analyse the results and understand if data analysed by other researchers are or not reliable. Bio: Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group. |
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March, 5
15.30
55.309 |
PhD Research Seminar By Simone Tassani Statistical course and Design of Experiments - course composed on 6 2-hour sessions The course of statistics aims to introduce a number of tools for master/Ph.D. students and post docs. The presented tools will play a role in planning many kind of studies, properly analyse the results and understand if data analysed by other researchers are or not reliable. Bio: Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group. |
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March, 12
15.30
55.003 |
PhD Research Seminar By Simone Tassani Statistical course and Design of Experiments - course composed on 6 2-hour sessions The course of statistics aims to introduce a number of tools for master/Ph.D. students and post docs. The presented tools will play a role in planning many kind of studies, properly analyse the results and understand if data analysed by other researchers are or not reliable. Bio: Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group. |
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March, 19
12.00
55.309 |
Invited Research Seminar By Petri Toiviainen, Finnish Centre for Interdisciplinary Music Research, University of Jyväskylä fMRI meets MIR: studying neural correlates of music listening with a naturalistic paradigm Abstract: The past two decades have witnessed a surge of neuroimaging studies that have attempted at identify brain structures involved in the perception of music-related perceptual features, such as pitch, sensory dissonance, rhythm, timbre, and key, typically in controlled conditions wherein the feature of interest has been presented in isolation and manipulated artificially. Such studies have inspected phenomena relatively distinct from the actual music listening situation where listeners continuously and subconsciously extract several musical features that are changing and integrate them into coherent percepts. To alleviate this shortcoming, our team has introduced and employed a naturalistic paradigm, wherein neural correlates of music processing are investigated using brain imaging data collected during continuous listening of music recordings and modelled using features computationally extracted from the presented music. I will give an overview of this work, including approaches of both encoding neural activation from music and decoding musical content and listener characteristics from neural activation. I will also present our ongoing work in which we aim to switch from feature engineering to feature learning in order to model the neural correlates of implicit music learning and enculturation. To this end, we will employ unsupervised deep neural networks to learn style-specific musical features at a range of abstraction levels and compare the thus learned representations with neural representations to investigate how music is processed in the brain at different hierarchical levels and how this depends on previous musical exposure. Host: Xavier Serra Casals |
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March, 19
15.30
55.309 |
PhD Research Seminar By Simone Tassani Statistical course and Design of Experiments - course composed on 6 2-hour sessions The course of statistics aims to introduce a number of tools for master/Ph.D. students and post docs. The presented tools will play a role in planning many kind of studies, properly analyse the results and understand if data analysed by other researchers are or not reliable. Bio: Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group. |
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March, 26
15.30
55.309 |
PhD Research Seminar By Simone Tassani Statistical course and Design of Experiments - course composed on 6 2-hour sessions The course of statistics aims to introduce a number of tools for master/Ph.D. students and post docs. The presented tools will play a role in planning many kind of studies, properly analyse the results and understand if data analysed by other researchers are or not reliable. Bio: Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group. |
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