{"id":2452,"date":"2025-10-18T13:26:55","date_gmt":"2025-10-18T16:26:55","guid":{"rendered":"https:\/\/eic.cefet-rj.br\/~eogasawara\/?page_id=2452"},"modified":"2025-12-02T14:02:06","modified_gmt":"2025-12-02T17:02:06","slug":"lectures","status":"publish","type":"page","link":"https:\/\/eic.cefet-rj.br\/~eogasawara\/en\/lectures\/","title":{"rendered":"Talks"},"content":{"rendered":"

Lectures presented at conferences and seminars<\/p><\/blockquote>\n

    \n
  1. Harbinger: A Unified Framework for Event Detection in Time Series<\/a> (Arcahub 2025, CEFET\/RJ 2025, 3W Workshop 2025)<\/li>\n
  2. Data Science: Challenges and Opportunities<\/a> (IFRJ 2024)<\/li>\n
  3. Use of LLM to Support Writing and Reviewing Articles<\/a> (SEPEX 2024)<\/li>\n
  4. Opportunities in Computer Science: A Perspective from Data Science<\/a> (Technische Universit\u00e4t Berlin 2024)<\/li>\n
  5. Concept Drift<\/a> (Technische Universit\u00e4t Berlin 2024)<\/li>\n
  6. Career in Computing<\/a> (Marista S\u00e3o Jos\u00e9 2024)<\/li>\n
  7. REMD: A New Hybrid Method for Anomaly Detection in Time Series<\/a> (IJCNN 2024)<\/li>\n
  8. Data-Centric AI Approaches for Time Series Event Detection<\/a> (DAL Lives 2024)<\/li>\n
  9. Data-Centric AI Approaches for Time Series Event Detection<\/a> (INRIA 2024)<\/li>\n
  10. Event Detection in Time Series<\/a> (UFRRJ 2024)<\/li>\n
  11. Data, Models, and Configuration Management in the Context of Artificial Intelligence<\/a> (SEPEX 2023)<\/li>\n
  12. Challenges in Predicting Global Pesticide Consumption Using Machine Learning<\/a> (BreSci 2023)<\/li>\n
  13. Outbreak Detection<\/a> (Fiocruz 2023)<\/li>\n
  14. Time Series Event Detection<\/a> (CENPES 2023)<\/li>\n
  15. Concept Drift<\/a> (Shape Time Series Day 2022)<\/li>\n
  16. Data Science in the Axes of Science, Business, and Government<\/a> (SEPEX 2022 and ERBD 2022)<\/li>\n
  17. Generalization of Restricted Sequence Mining in Space and Time<\/a> (SBBD 2021) (video)<\/li>\n
  18. Panel: High Performance Data Science (WEIC 2021) (video<\/a>)<\/li>\n
  19. Panel: Research & Extension Initiatives at EIC: Where Did We Come From? What Are We? Where Are We Going? (WEIC 2021) (video<\/a>)<\/li>\n
  20. Time Series Prediction<\/a> (SEIC 2021) (video<\/a>)<\/li>\n
  21. Where to Submit Articles? And Qualis?<\/a> (SEIC 2020) (video<\/a>)<\/li>\n
  22. Autoregressive Model of Adaptive Integration<\/a> (SBBD 2019) (video<\/a>)<\/li>\n
  23. Frequent Anomaly Detection in Urban Road Transport<\/a> (SBBD 2018)<\/li>\n
  24. Towards the Integration of Workflow Algebra with Relational Query Processing<\/a> (SBBD 2018)<\/li>\n
  25. Evaluating Data Preprocessing Methods for Machine Learning Models for Flight Delays<\/a> (IJCNN 2018)<\/li>\n
  26. Evaluating the Complementarity of Communication Tools for Learning Platforms<\/a> (CSEDU 2018)<\/li>\n
  27. Orthographic Educational Game for Portuguese-Speaking Countries<\/a> (CSEDU 2018)<\/li>\n
  28. Management and Analysis of Spatio-Temporal Series<\/a> (LNCC-INRIA 2017)<\/li>\n
  29. Anomaly Detection in Urban Road Transport<\/a> (SBBD 2017)<\/li>\n
  30. PPCIC and Its Connection with Data Science Challenges<\/a> (WEIC 2016)<\/li>\n
  31. Analysis of Research Practice and Research Methodology Courses<\/a> (SEIC 2016)<\/li>\n
  32. Opening Presentation of the Graduate Program in Computer Science at CEFET\/RJ<\/a> (CEFET\/RJ 2016)<\/li>\n
  33. Research Report<\/a> (LNCC-INRIA 2016)<\/li>\n
  34. Identification of Motifs in Spatio-Temporal Series<\/a> (WCD @ LNCC 2016)<\/li>\n
  35. Exploring Multiple Clusters in Attributed Graphs<\/a> (SAC 2015)<\/li>\n
  36. Am\u00ea: An Environment to Learn and Analyze Adversarial Search Algorithms Using Stochastic Card Games<\/a> (SAC 2015)<\/li>\n
  37. Big Data & IoT<\/a> (WEIC 2015)<\/li>\n
  38. Innovative Projects, Revolutionary Ideas<\/a> (WEIC 2014)<\/li>\n
  39. How to Prepare Good Final Projects?<\/a> (SEIC 2014)<\/li>\n
  40. Algorithms and Applications of Data Mining<\/a> (LNCC-INRIA 2014)<\/li>\n
  41. Towards a Reference Model for ODL: A Case Study in the Tourism Undergraduate Course<\/a> (ICBL 2013)<\/li>\n
  42. Building an Environment for Developing Educational Games Based on Gestural Interface<\/a> (SENID 2013)<\/li>\n
  43. Using Provenance Analyzers to Improve the Performance of Scientific Workflows in Cloud Environments<\/a> (SBBD 2012)<\/li>\n
  44. Using Domain-Specific Data to Enhance Scientific Workflow Steering Queries<\/a> (IPAW 2012)<\/li>\n
  45. An Algebraic Approach for Data-Centric Scientific Workflows<\/a> (VLDB 2011)<\/li>\n
  46. Evaluation of the Distribution of Static and Dynamic Activities in Parallel Environments Using Hydra<\/a> (BreSci 2011 @ CSBC)<\/li>\n
  47. Data Parallelism in Bioinformatics Workflows Using Hydra<\/a> (ECMLS 2010 @ HPDC)<\/li>\n
  48. GExpLine: A Tool for Supporting Experiment Composition<\/a> (IPAW 2010)<\/li>\n
  49. Estimates of Consumption and Production of Agro-Minerals for the Next 20 Years<\/a> (CETEM 2010)<\/li>\n
  50. A Conception Process for Abstract Workflows: An Example in the Deep Water Oil Exploitation Domain<\/a> (eScience 2009)<\/li>\n
  51. Parallelization of Data Mining Tasks Using Scientific Workflows<\/a> (WAAMD 2009 @SBBD)<\/li>\n
  52. Exploring Many Task Computing in Scientific Workflows<\/a> (MTAGS 2009 @ SC)<\/li>\n
  53. Autoregressive Model for Fertilizer Forecasting Based on Neural Networks<\/a> (Rochagem 2009)<\/li>\n
  54. Neural Networks Cartridges for Data Mining on Time Series<\/a> (IJCNN 2009)<\/li>\n
  55. Experiment Line: Software Reuse in Scientific Workflows<\/a> (SSDBM 2009)<\/li>\n
  56. Comparison and Versioning of Scientific Workflows<\/a> (CVSM 2009 @ ICSE)<\/li>\n
  57. Experience Lines: Management of Reuse and Configuration in Scientific Workflows<\/a> (BreSci 2009)<\/li>\n
  58. Experimental Evaluation of Indexing Techniques in Object-Oriented Databases<\/a> (SBBD 1999)<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

    Lectures presented at conferences and seminars Harbinger: A Unified Framework for Event Detection in Time Series (Arcahub 2025, CEFET\/RJ 2025, 3W Workshop 2025) Data Science: Challenges and Opportunities (IFRJ 2024) Use of LLM to Support Writing and Reviewing Articles (SEPEX 2024) Opportunities in Computer Science: A Perspective from Data Science (Technische Universit\u00e4t Berlin 2024) Concept […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"class_list":["post-2452","page","type-page","status-publish","hentry","entry"],"_links":{"self":[{"href":"https:\/\/eic.cefet-rj.br\/~eogasawara\/wp-json\/wp\/v2\/pages\/2452","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/eic.cefet-rj.br\/~eogasawara\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/eic.cefet-rj.br\/~eogasawara\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/eic.cefet-rj.br\/~eogasawara\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/eic.cefet-rj.br\/~eogasawara\/wp-json\/wp\/v2\/comments?post=2452"}],"version-history":[{"count":4,"href":"https:\/\/eic.cefet-rj.br\/~eogasawara\/wp-json\/wp\/v2\/pages\/2452\/revisions"}],"predecessor-version":[{"id":2599,"href":"https:\/\/eic.cefet-rj.br\/~eogasawara\/wp-json\/wp\/v2\/pages\/2452\/revisions\/2599"}],"wp:attachment":[{"href":"https:\/\/eic.cefet-rj.br\/~eogasawara\/wp-json\/wp\/v2\/media?parent=2452"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}