I defended my doctoral thesis!
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I successfully defended my thesis Mathematical Methods for Inverse Rigging in Realistic Blendshape Models and got awarded a doctoral diploma with distinction
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I successfully defended my thesis Mathematical Methods for Inverse Rigging in Realistic Blendshape Models and got awarded a doctoral diploma with distinction
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Paper Refined Inverse Rigging: A Balanced Approach to High-fidelity Blendshape Animation has been published in SIGGRAPH Asia, one of the most important conferences of the graphics and visualisation.
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Paper PeersimGym: An Environment for Solving the Task Offloading Problem with Reinforcement Learning has been published in Joint European Conference on Machine Learning and Knowledge Discovery in Databases.
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Our publication Distributed Solution of the Inverse Rig Problem in Blendshape Facial Animation is selected to appear in the Association for Computing Machinery (ACM) Showcase on Kudos!
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Paper Distributed Solution of the Inverse Rig Problem in Blendshape Facial Animation is accepted for publication in SIGGRAPH Asia, one of the most important conferences of the graphics and visualisation.
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Paper A majorization–minimization-based method for nonconvex inverse rig problems in facial animation: algorithm derivation has been published in the Optimization Letters journal.
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Paper A hybrid compartmental model with a case study of COVID-19 in Great Britain and Israel was published in the Journal of Mathematics in Industry. It was motivated by our participation in the ECMI 2021 Student Competition.
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With Filipa Valdeira (University of Milan) and Greta Malaspina (University of Novi Sad), we won the first place in the ECMI 2021 Student Competition.
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Our paper Clustering of the Blendshape Facial Model was published in the proceedings of EUSIPCO 2021.
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With two colleagues from the BIGMATH program, Filipa Valdeira (University of Milan) and Rongjiao Ji (University of Milan), we won third place in the e-Poster competition for the graduate students, with the title ‘Meet my Avatar’. This work merges ideas from our three research fields: inverse rig estimation, face reconstruction, and emotion recognition.
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In September 2018, I earned an MSc degree in Applied Mathematics - Data Science at the Faculty of Sciences UNS. This two-year master’s program focused on extracting knowledge from data, utilizing ML, DL, optimization, and signal processing tools. My master thesis, titled “Parallel Implementation of Machine Learning Algorithms using PyCOMPSs,” concerns the software developed by the I-BiDaaS project and was conducted under the supervision of professor Dušan Jakovetić.
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From April 2018, I started working as a Junior Researcher at the Faculty of Sciences UNS, within an international project I-BiDaaS — Industrial-Driven Big Data as a Self-Service Solution. My role is model for distributed implementation of the standard Machine Learning algorithms.