• 2019 - 2021: Postdoc at the University of New Mexico (UNM), USA (Supervisor: Abdullah Mueen)

• 2018 - 2019: Postdoc at the University of São Paulo (ICMC/USP), Brazil (Supervisor: Gustavo Batista)

• 2014: Six-month PhD internship abroad (March to September) at the University of Porto (LIAAD-INESC TEC), Portugal (Supervisor: João Gama)

• 2011 - 2016: PhD in Computer Science from the University of Sao Paulo (ICMC/USP), Brazil (Advisor: Gustavo Batista)

• 2009 - 2011: MSc in Computer Science from State University of Maringá (UEM), Brazil (Advisor: Valéria Feltrim)

• 2004 - 2008: BSc in Informatics from State University of Maringá (UEM), Brazil

• [2024] Being a researcher and professor is tough. It is even worse in Brazil (e.g., 150 students and no TA, lack of resources, etc). Once again, my name appears in the Stanford/Elsevier Top 2% Scientists Ranking in 2023 (single year). Out of 223,000 researchers, 1,340 Brazilians and not a half dozen from my university. Maybe I'll be gifted a plastic cup or a weird candle at the end of semester.

• [2024] Some conference papers accepted this year: IJCNN, ICANN, and ICMLA.

• [2024] The undergraduate students under my supervision Lucas and Henrique published their final course work Time-Series Mining Approaches for Malaria Vector Prediction On Mid-Infrared Spectroscopy Data in the Data Science Journal.

• [2023] I am delighted to have the paper A Large Comparison of Normalization Methods on Time Series published in the Big Data Research journal. This article can be an interesting reference for the time series community in which we discuss the impact of 10 normalization methods on distance-based and deep learning algorithms for time series classification. More information available on the supporting website.

• [2023] The paper Online Few-Shot Time Series Classification for Aftershock Detection was accepted at KDD 2023.

• [2022] For the first time, my name was mentioned in the Elsevier ranking (based on Scopus data) as a top-cited scientist worldwide. The selection is based on the top 100,000 scientists during the calendar year 2021. I have a lot of criticisms regarding the biases of these rankings, but being on the same list as dozens of ML researchers whom I admire made me happy. You can check it out in Table 2 (single year) here.

• [2022] Providing contributions besides the Computer Science field, our paper Hierarchical classification of pollinating flying insects under changing environments was published in the Ecological Informatics (IF: 4.498) journal.

• [2022] Trying higher visibility in an open-access journal for the first time with the paper Time Series Prediction via Similarity Search: Exploring Invariances, Distance Measures and Ensemble Functions. 

• [2022] Since my PhD I have been pursuing a goal in my career to have published at least one paper at the three top-tier and competitive conferences in my field: KDD, ICDM, and SDM. Finally, I got a paper accepted at KDD, and now I can unlock this achievement (✓). Septor: Seismic Depth Estimation using Hierarchical Neural Network is a joint work with Ashraf Siddiquee and Abdullah Mueen from UNM and Eli Baker from Air Force Research Laboratory. 

• [2022] The paper TS-DENSE: Time Series Data Augmentation by Subclass Clustering was accepted at ICPR 2022. It is my first paper with undergraduate students (Rodrigo and Lucas) under my supervision. 

• [2022] An extended version of FilCorr paper published at ICDM 2020 was accepted in the journal ACM Transactions on Knowledge Discovery from Data (TKDD) (IF: 2.713). See the paper: Combining Filtering and Cross-correlation Efficiently for Streaming Time Series.

• [2022] A new article from the collaboration with Lucas Tsutsui (ICMC/USP) and Gustavo Batista (UNSW) is now online in the IEEE Sensors Journal (Impact Factor: 3.301). See the paper: An Open-Source Tool for Classification Models in Resource-Constrained Hardware

• [2021] At least a good news during hard times of questions and regrets. Our paper Multi-way Time Series Join on Multi-length Patterns with Md Parvez and Abdullah Mueen was accepted as a regular paper at IEEE ICDM. Out of 990 submissions, only 98 regular papers were accepted. This corresponds to an acceptance rate of 9.9%. Particularly, ICDM is my favorite conference, and it is a pleasure to have a third paper in it.

• [2021] As a computer science researcher, I think it is essential to contribute to different fields when possible. I hope our new paper Changes in the wing-beat frequency of bees and wasps depending on environmental conditions: a study with optical sensors, published in Apidologie journal (Impact Factor: 2.318), could provide helpful information and discussion for biologists and entomologists.

• [2021] My paper Efficient unsupervised drift detector for fast and high-dimensional data streams has just been published in the top-tier data mining journal Knowledge and Information Systems (Impact Factor: 2.936).

• [2021] I'm glad about my new position as an Assistant Professor with the Graduate Program in Informatics (PPGIa) of PUCPR, Brazil. Currently, I'm recruiting three undergraduate and two Master's (filled) students interested in working with real-world problems using machine learning and data mining solutions on time series or/and streaming data. Please feel free to contact me!

• [2020] My paper Unsupervised Drift Detection on High-speed Data Streams was accepted as a regular paper in the conference IEEE BigData (acceptance rate of 15.5% over 535 submissions).

• [2020] It is a pleasure to have a paper accepted in the top-tier conference IEEE ICDM (overall acceptance rate of 19.7% - regular/short papers - over 930 submissions). I am co-author of FilCorr: Filtered and Lagged Correlation on Streaming Time Series with Sheng Zhong and Abdullah Mueen. 

• [2020] I am glad to have a new article published in the top-tier journal Data Mining and Knowledge Discovery (Impact Factor: 2.879). The paper entitled Challenges in Benchmarking Stream Learning Algorithms with Real-world Data is available here.

• [2019] I was hired as Postdoc Researcher in the CS Department of the University of New Mexico (UNM), USA. I'll start my work under the supervision of Professor Abdullah Mueen in October 2019.

• [2019] A new paper from the collaboration with the PhD candidate Antonio Parmezan is now online in the Information Sciences journal (Impact Factor: 5.524), see: Evaluation of statistical and machine learning models for time series prediction: Identifying the state-of-the-art and the best conditions for the use of each model

• [2018] We had two accepted papers in the conference CIARP from the collaborations with Gustavo Batista´s PhD students Antonio Parmezan (Towards Hierarchical Classification of Data Streams) and Tiago Pinho (A Fuzzy Classifier for Data Streams with Infinitely Delayed Labels).

• [2018] My new article with Rafael Giusti and Antônio Lima entitled Asfault: A low-cost system to evaluate pavement conditions in real-time using smartphones and machine learning was published in the journal Pervasive and Mobile Computing (Impact Factor: 2.769). 

• [2018] My article Asphalt pavement classification using smartphone accelerometer and Complexity Invariant Distance was accepted in the journal Engineering Applications of Artificial Intelligence (Impact Factor: 3.526), and it is now online available. 

• [2018] My website is now online!

CURRENT

PhD:

• Rodrigo Krüger (co-advisor) (2024-2028)

Master's degree:

• André Gustavo da Rosa Ribeiro (2024)

• Lucas Gabriel Mendes de Castro (2024)

Undergraduate final project:

• Open positions

Scientific initiation (undergraduate):

• Bruno Assis Miglioretto (2024-2025)

• Alexandre Faisst (2024-2025)

• Alexandre Beiruth (2024-2025)

PostDoc supervision:

• Jonas Krause (2024-2025)

Former

Master´s degree:

• Rodrigo Krüger (2023)

Scientific initiation (undergraduate):

• Patrickerson Veiga (2023-2024)

• André Gustavo da Rosa Ribeiro (2022-2023)

• Henrique Vieira da Costa (2022-2023)

Undergraduate final project:

• André Gustavo da Rosa Ribeiro (2023)

• Henrique Vieira da Costa and Lucas Castro (2023)

• Felipe Tomazelli and Mateus Pimenta (2022)

• Lucas Castro and Rodrigo Zanella (2021)

• Juan Carlos Santos Silva (2017) (co-advisor with Professor Rafael Rossi, UFMS).

• Research Excellence Award received by PUCPR in 2023

• Teaching Excellence Award received by PUCPR in 2022, referring to the 2021 academic year (official document).

• 1st place (PhD) in the X Thesis and Dissertation Contest in Artificial and Computational Intelligence (CTDIAC 2016) promoted by the 5th Brazilian Conference on Intelligent System (BRACIS) (Paper) (official document)

• SIAM SDM Student Travel Award (2015)

• ICPR Student Travel Award (2014) - one of the 50 (out of 247)

• Best paper of VIII Brazilian Symposium in Information and Human Language Technology (STIL 2011)

• Mar 2017 - Nov 2017: Evaluation and collaborative monitoring of streets and roads conditions by means of smartphone sensors - PIPE-FAPESP (Phase 1 - Grant of 200,000 BRL or around 65,000 USD )

• Jun 2016 - Feb 2017: Intelligent Tools to Vector Control and Population Orientation against Dengue Fever - PIPE-FAPESP (Phase 1 - Grant of 200,000 BRL or around 65,000 USD)

I have been Assistant Professor at PUCPR since 2021, teaching different graduate/undergraduate CS disciplines. If you are interested in my teaching material (slides and videos) for the disciplines below, please download the compacted files and send me an e-mail requesting the password*. I will be glad to share the material with you.

* Such a procedure is only for my personal control of the material access

• Artificial Intelligence (slides of 1/2023) 

• Big Data (slides of 2/2023)

• Problem-solving with Graphs (slides of 2/2022)

• Graph Mining (videos of 2021)

• Fundamentals of Computational Mathematics (videos of 2021)

• USP Data Stream Benchmark Repository

• Visemble 

• Image-Based Drift Detector - IBDD (IEEE BigData & KAIS)

• Asfault datasets v.2 (streets/roads - ARFF files), PMC publication - DOWNLOAD

• Asfault datasets v.1 (Regularity, PavType, Obstacles - MAT-Files), EAAI publication - DOWNLOAD

• Data Stream Classification Guided by Clustering on Nonstationary Environments and Extreme Verification Latency (SDM 2015)

• Automatic Classification of Drum Sounds with Indefinite Pitch (IJCNN 2015)

• Music Shapelets for Fast Cover Song Recognition (ISMIR 2015)

• Extracting Texture Features for Time Series Classification (ICPR 2014)

• Time Series Classification Using Compression Distance of Recurrence Plots (ICDM 2013)

• Applying Machine Learning and Audio Analysis Techniques to Insect Recognition in Intelligent Traps (ICMLA 2013)

• Journal (reviewer)

  • ACM Computing Surveys

  • Machine Learning

  • Applied Soft Computing

  • Pattern Recognition Letters

  • Big Data Research

  • IEEE Transactions on Audio Speech and Language Processing

• Conference

  • PC Member of ACM CIKM since 2024

  • PC Member of SIGKDD since 2022

  • PC Member of IJCAI since 2021

  • PC Member of DSAA 2017

  • PC Member of IOTStreams (ECML Workshop) 2020

Reviewer:

• • SIGKDD (2012, 2014, 2020, 2021)

  • ICDM (2020)

  • SDM (2021)

  • BIGDATA (2014, 2015, 2018, 2019, 2020)

  • ICPR (2018, 2022)

  • WWW (2021)

  • CIKM (2013, 2014)

  • AAAI (2015, 2019)

Newspaper:

• Revista EXAME

• Agência FAPESP