Masters Presentation May 2021

Masters Presentation May 2021

www.upc.edu www.upc.edu Master in Artificial Intelligence (MAI) Master in Informatics Engineering (MEI) Master in Informatics Engineering – Industrial Modality Master in Innovation and Research in Informatics (MIRI) Master in Data Science (MDS) Màster per al Professorat de Secundària, Master in Cybersecurity Erasmus Mundus Master in Big Data Management and Analytics More Master Information [email protected] Daniel Jiménez-González Vice-dean of Postgraduates Studies FIB: graduate curricula www.upc.edu Coordinated by FIB: ● Màster en Enginyeria Informàtica (Spanish/Catalan) → MEI ● (NEW) Màster en Enginyeria Informàtica Modalitat Empresa ● Master in Innovation and Research in Informatics (English) → MIRI ● Master in Data Science (English) → MDS ● Interuniversity Master in Artificial Intelligence (English) → MAI Màster de Formació per al Professorat de Secundària (Català/Castellà) Participate: Master’s degree in Cybersecurity (2020/21 - English) Interuniversity Master in Pure and Applied Logics Interuniversity Master in Atomistic and Multiscale Computational Modelling in Physics, Chemistry and Biochemistry ERASMUS MUNDUS: 3 Master Erasmus Mundus in Big Data Management and Analytics Summary Knowledge Areas – www.upc.edu MAI/MIRI/MEI/MDS Computer Networks, MDS: Distributed Data Science, Systems, Big Data Advanced Security Computing, Analytics Management Algorithms Business Artificial Intelligence Computer Graphics, Supercomputing, Virtual and MEI Parallelism, Augmented Reality MAI Microprocessor Design MIRI 4 www.upc.edu I could start with the institutional part... … but the important is what you would like to achieve/do/be… 5 www.upc.edu All Achievements Begin as Dreams … and our students make them real here! 6 www.upc.edu Social and Technological Dreams HardwareHardware DesignDesign and and Acceleration Acceleration HealthHealth Goals Goals Artifitial Intelligence Artifitial Intelligence 3D3D Gaming Gaming Applied Applied RenderingRendering in in Real Real Time Time DataData Science/ Science/ ProgrammingProgramming Models Models BigBig Data Data Analytics Analytics ParallelParallel Exploitation/ Exploitation/ ProcessorProcessor Design Design TECHNOLOGY TRANSFER RESEARCH + DEVELOPMENT + INNOVATION 7 www.upc.edu Social and Technological Dreams HealthHealth GoalsGoals Hardware DesignDesign andandHardware AccelerationAcceleration ArtifitialArtifitial IntelligenceIntelligence AppliedApplied DataData Science/Science/ BigBig DataData AnalyticsAnalytics 3D Gaming RenderingRendering3D Gaminginin RealReal TimeTime ProgrammingProgramming ModelsModels ParallelParallel Exploitation/Exploitation/ ProcessorProcessor DesignDesign RESEARCHTECHNOLOGY + DEVELOPMENT TRANSFER + INNOVATION And of course! Any of your dream! 8 www.upc.edu Master Thesis Examples • MIRI: • (CGVR) Plausible reconstruction and rendering of semi-procedural landscapes. Oscar Argudo • (CNDS) Critical Analysis and Comparison of Data Protection Techniques for Genomics Data Sets. Daniel Naro • (HPC) Asynchronous runtime for task-based dataflow programming models. Jaume Bosch Pons • (AC) Machine Learning Techniques for resource prediction in nanoelectronic circuit design. Narcís Ricard • MEI : Study of Deep Learning Algorithms Scalability in High Performance Computer Infrastructures. Francesc Sastre Cabot. • MAI: Applying deep-learning techniques to detect freezing of gait episodes in Parkinson's disease patients. Julià Camps Sereix • MDS: Computing and visualizing informative trajectories in temporally annotated data. Martí Zamora Casals (Under MIRI-DS) 9 MIRI-CGVR: Rendering for 3D www.upc.edu Real Time – Games and Health! • Plausible reconstruction and rendering of semi-procedural landscapes. Author: Oscar Argudo. Grade: 10(MH) • Detail usually involves scanning again the • The acquisition process is area of interest with more accurate expensive because it involves a equipment or taking more samples per substantial amount of time, area. human resources and expensive equipment. • 3D real time reconstruction is possible using real information guidance 10 Video … Núria www.upc.edu MIRI-CGVR: Rendering for 3D Real Time – Games and Health! • Plausible reconstruction and rendering of semi-procedural landscapes. • Author: Oscar Argudo Detail usually involves scanning again the area of interest with more accurate equipment or taking more samples per . Grade: 10(MH) area . Game Companies are really powerful! • The acquisitionHea lprocessth is a isls o expensive becausea t aitr involvesget! a substantial amount of time, human resources and expensive equipment. • 3D real time reconstruction is possible Video … Núria using real information guidance 11 MIRI-CNDS: Security/Genomics www.upc.edu • Critical Analysis and Comparison of Data Protection Techniques for Genomics Data Sets. Author: Daniel Naro. Grade: 10 (MH) • Genomic data is extremely sensitive by nature: it has intrinsic properties for individual identification, ancestry discovery, and disease prediction among others. • Protection is needed for individual: DNA encrypted, access control, etc. • File Format with encrypted portions of the DNA, by using different keys 12 www.upc.edu MIRI-CNDS: Security/Genomics • Critical Analysis and Comparison of Data Protection Techniques for Genomics Data Sets. Author: Daniel Naro. • Genomic data is extremely sensitive by nature: it has intrinsic properties for individual identification, ancestry Grade: 10 (MH) discovery, and disease prediction among others.Network Security • Protection is needed for individual: DNA encrypted,and A I are target of access control, etc. this specialization And Distributed and Cloud System! • File Format with encrypted portions of the DNA, by using different keys 13 MIRI-HPC: How to improve an www.upc.edu Application? HW vs Software • Asynchronous runtime for task-based dataflow programming models. Author: Jaume Bosch Pons. Grade: 10 (MH) • Task-based parallel programming model • There is a library follows a natural way to parallelize (runtime) that takes care of all the “hard” work of parallelize the tasks • Hardware and Parallel Knowledge helps to speedup applications: Bioinformatics, Earth Science (weather simulatios), etc. 14 MIRI-HPC: How to improve an www.upc.edu Application? HW vs Software • Asynchronous runtime for task-based dataflow programming models. Author: Jaume Bosch Pons. Grade: 10 (MH) • Task-based parallel programming model • There is a library follows a natural way to parallelize (runtime) that takes care of all the “hard” work of parallelize the tasks • Hardware and Parallel Knowledge helps to speedup applications: Bioinformatics, Earth Science (weather simulatios), etc. 15 MIRI-AC: Circuit (Chip) Design www.upc.edu using Machine Learning • Machine Learning Techniques for resource prediction in nanoelectronic circuit design. Author: Narcís Ricard. Grade: 9 • Company’s needed resources estimation • Problems in the beforehand organization due to unknown timing process • Highly accurate machine learning models for IT metrics (runtime, CPU time and memory) 16 www.upc.edu MEI: HPC for Deep Learning! • Study of Deep Learning Algorithms Scalability in High Performance Computer Infrastructures. Author: Francesc Sastre Cabot. Grade: 10 (MH) • High Performance Computing and Parallel Techniques speedup Deep Learning • Image classification • Object Detection, etc. • From 106 hours of training to 12 hours... 17 MAI: Particular Diseases can www.upc.edu be target like Parkinson • Applying deep-learning techniques to detect freezing of gait episodes in Parkinson's disease patients. Author: Julià Camps Sereix Grade: 10 (MH) • Accurate ambulatory FOG • Funded by FP7 European assessment would enable Projects and TV3 Marató non-pharmacologic support based on cues and would provide relevant information to neurologists on the disease evolution. • Automatic detection with 90% accuracy (stat-of-the- art) 18 MDS: Health Guidance! www.upc.edu • Computing and visualizing informative trajectories in temporally annotated data. Author: Martí Zamora Casals – Grade: 10 • A trajectory in the medical world is the • Trajectory of a patient is sequence of events that occur during the life of formed by states, each a patient. state is formed by a central event, normally a diagnostic and a set of secondary events • Trajectory graph combines the trajectory of different patients, providing a probability of the next event for a patient with a disease 19 www.upc.edu MDS: Health Guidance! • Computing and visualizing informative trajectories in temporally annotated data. • A trajectory inAuthor: the medical Martí worldZamora is the Casals sequence of events that occur during the life of a patient. – Grade: 10 Nowadays, Data • Analy Trajectory of a patienttics i sis important! formed by states, each state is formed by a central event, normally a diagnostic and a set of secondary events • Trajectory graph combines the trajectory of different patients, providing a probability of the next event for a patient with a disease 20 www.upc.edu How can you do it? 21 www.upc.edu How can you do it? Creating networking! 22 How can you do it? www.upc.edu You can create networking! • Acquiring the knowledge of OUR master subjects and going further on them… • Our professors are also researchers ➢ Belong to different departments and research groups ➢ Contact them… at class… or directly to the research group/center • Under Industrial Agreements, acquiring even more knowledge and experience! • Under International Mobility 23 You have several www.upc.edu research groups and centers • Mathematics

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