Author details

Radu B. Rusu

Also published under: Radu Bogdan Rusu, R. B. Rusu, Radu Rusu

Affiliation

Open Perception Inc., California, United States

Publication Topics

Biography

Radu Bogdan Rusu, Open Perception, California. E-mail: Rusu@openperception.org.(Based on document published on 20 June 2013).

Publications

Citations

9,332

Publications by Year

20062015

Co-Authors:

Show All Co-Authors (84)

Author's Published Works

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Data Augmentation's Effect on Machine Learning Models when Learning with Imbalanced Data

Damien A. Dablain;Nitesh V. Chawla

2024 IEEE 11th International Conference on Data Science and Advanced Analytics (DSAA)

Year: 2024 | Conference Paper |

Cited by: Papers (1)

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Data Augmentation's Effect on Machine Learning Models when Learning with Imbalanced Data

Damien A. Dablain;Nitesh V. Chawla

2024 IEEE 11th International Conference on Data Science and Advanced Analytics (DSAA)

Year: 2024 | Conference Paper |

SMOTE for gene regulatory network sampling

Gonzalo A. Ruz;Nitesh V. Chawla

2024 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)

Year: 2024 | Conference Paper |

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SMOTE for gene regulatory network sampling

Gonzalo A. Ruz;Nitesh V. Chawla

2024 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)

Year: 2024 | Conference Paper |

Representing Outcome-Driven Higher-Order Dependencies in Graphs of Disease Trajectories

Steven J. Krieg;Nitesh V. Chawla;Keith Feldman

2024 IEEE 12th International Conference on Healthcare Informatics (ICHI)

Year: 2024 | Conference Paper |

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Representing Outcome-Driven Higher-Order Dependencies in Graphs of Disease Trajectories

Steven J. Krieg;Nitesh V. Chawla;Keith Feldman

2024 IEEE 12th International Conference on Healthcare Informatics (ICHI)

Year: 2024 | Conference Paper |

Efficient Augmentation for Imbalanced Deep Learning

Damien A. Dablain;Colin Bellinger;Bartosz Krawczyk;Nitesh V. Chawla

2023 IEEE 39th International Conference on Data Engineering (ICDE)

Year: 2023 | Conference Paper |

Cited by: Papers (4)

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Efficient Augmentation for Imbalanced Deep Learning

Damien A. Dablain;Colin Bellinger;Bartosz Krawczyk;Nitesh V. Chawla

2023 IEEE 39th International Conference on Data Engineering (ICDE)

Year: 2023 | Conference Paper |

Detecting Anomalies in Small Unmanned Aerial Systems via Graphical Normalizing Flows

Yihong Ma;Md Nafee Al Islam;Jane Cleland-Huang;Nitesh V. Chawla

IEEE Intelligent Systems

Year: 2023 | Volume: 38, Issue: 2 | Magazine Article |

Cited by: Papers (5)

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Detecting Anomalies in Small Unmanned Aerial Systems via Graphical Normalizing Flows

Yihong Ma;Md Nafee Al Islam;Jane Cleland-Huang;Nitesh V. Chawla

IEEE Intelligent Systems

Year: 2023 | Volume: 38, Issue: 2 | Magazine Article |

Deep Multimodal Complementarity Learning

Daheng Wang;Tong Zhao;Wenhao Yu;Nitesh V. Chawla;Meng Jiang

IEEE Transactions on Neural Networks and Learning Systems

Year: 2023 | Volume: 34, Issue: 12 | Journal Article |

Cited by: Papers (11)

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Deep Multimodal Complementarity Learning

Daheng Wang;Tong Zhao;Wenhao Yu;Nitesh V. Chawla;Meng Jiang

IEEE Transactions on Neural Networks and Learning Systems

Year: 2023 | Volume: 34, Issue: 12 | Journal Article |

SD2: Slicing and Dicing Scholarly Data for Interactive Evaluation of Academic Performance

Zhichun Guo;Jun Tao;Siming Chen;Nitesh V. Chawla;Chaoli Wang

IEEE Transactions on Visualization and Computer Graphics

Year: 2023 | Volume: 29, Issue: 8 | Journal Article |

Cited by: Papers (3)

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SD2: Slicing and Dicing Scholarly Data for Interactive Evaluation of Academic Performance

Zhichun Guo;Jun Tao;Siming Chen;Nitesh V. Chawla;Chaoli Wang

IEEE Transactions on Visualization and Computer Graphics

Year: 2023 | Volume: 29, Issue: 8 | Journal Article |

DeepSMOTE: Fusing Deep Learning and SMOTE for Imbalanced Data

Damien Dablain;Bartosz Krawczyk;Nitesh V. Chawla

IEEE Transactions on Neural Networks and Learning Systems

Year: 2023 | Volume: 34, Issue: 9 | Journal Article |

Cited by: Papers (176)

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DeepSMOTE: Fusing Deep Learning and SMOTE for Imbalanced Data

Damien Dablain;Bartosz Krawczyk;Nitesh V. Chawla

IEEE Transactions on Neural Networks and Learning Systems

Year: 2023 | Volume: 34, Issue: 9 | Journal Article |

Modeling Co-Evolution of Attributed and Structural Information in Graph Sequence

Daheng Wang;Zhihan Zhang;Yihong Ma;Tong Zhao;Tianwen Jiang;Nitesh V. Chawla;Meng Jiang

IEEE Transactions on Knowledge and Data Engineering

Year: 2023 | Volume: 35, Issue: 2 | Journal Article |

Cited by: Papers (6)

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Modeling Co-Evolution of Attributed and Structural Information in Graph Sequence

Daheng Wang;Zhihan Zhang;Yihong Ma;Tong Zhao;Tianwen Jiang;Nitesh V. Chawla;Meng Jiang

IEEE Transactions on Knowledge and Data Engineering

Year: 2023 | Volume: 35, Issue: 2 | Journal Article |

RESAM: Requirements Elicitation and Specification for Deep-Learning Anomaly Models with Applications to UAV Flight Controllers

Md Nafee Al Islam;Yihong Ma;Pedro Alarcon;Nitesh Chawla;Jane Cleland-Huang

2022 IEEE 30th International Requirements Engineering Conference (RE)

Year: 2022 | Conference Paper |

Cited by: Papers (10)

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RESAM: Requirements Elicitation and Specification for Deep-Learning Anomaly Models with Applications to UAV Flight Controllers

Md Nafee Al Islam;Yihong Ma;Pedro Alarcon;Nitesh Chawla;Jane Cleland-Huang

2022 IEEE 30th International Requirements Engineering Conference (RE)

Year: 2022 | Conference Paper |

Dynamic Attributed Graph Prediction with Conditional Normalizing Flows

Daheng Wang;Tong Zhao;Nitesh V. Chawla;Meng Jiang

2021 IEEE International Conference on Data Mining (ICDM)

Year: 2021 | Conference Paper |

Cited by: Papers (2)

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Dynamic Attributed Graph Prediction with Conditional Normalizing Flows

Daheng Wang;Tong Zhao;Nitesh V. Chawla;Meng Jiang

2021 IEEE International Conference on Data Mining (ICDM)

Year: 2021 | Conference Paper |

Predicting Job Performance Using Mobile Sensing

Shayan Mirjafari;Hessam Bagherinezhad;Subigya Nepal;Gonzalo J. Martinez;Koustuv Saha;Mikio Obuchi;Pino G. Audia;Nitesh V. Chawla;Anind K. Dey;Aaron Striegel;Andrew T. Campbell

IEEE Pervasive Computing

Year: 2021 | Volume: 20, Issue: 4 | Magazine Article |

Cited by: Papers (3)

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Predicting Job Performance Using Mobile Sensing

Shayan Mirjafari;Hessam Bagherinezhad;Subigya Nepal;Gonzalo J. Martinez;Koustuv Saha;Mikio Obuchi;Pino G. Audia;Nitesh V. Chawla;Anind K. Dey;Aaron Striegel;Andrew T. Campbell

IEEE Pervasive Computing

Year: 2021 | Volume: 20, Issue: 4 | Magazine Article |

motif2vec: Semantic-aware Representation Learning for Wearables' Time Series Data

Suwen Lin;Xian Wu;Nitesh V. Chawla

2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA)

Year: 2021 | Conference Paper |

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motif2vec: Semantic-aware Representation Learning for Wearables' Time Series Data

Suwen Lin;Xian Wu;Nitesh V. Chawla

2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA)

Year: 2021 | Conference Paper |

Lan: Learning to Augment Noise Tolerance for Self-report Survey Labels

Suwen Lin;Louis Faust;Nitesh V. Chawla

2021 IEEE International Conference on Pervasive Computing and Communications (PerCom)

Year: 2021 | Conference Paper |

Cited by: Papers (1)

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Lan: Learning to Augment Noise Tolerance for Self-report Survey Labels

Suwen Lin;Louis Faust;Nitesh V. Chawla

2021 IEEE International Conference on Pervasive Computing and Communications (PerCom)

Year: 2021 | Conference Paper |

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Biomedical Knowledge Graphs Construction From Conditional Statements

Tianwen Jiang;Qingkai Zeng;Tong Zhao;Bing Qin;Ting Liu;Nitesh V. Chawla;Meng Jiang

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Year: 2021 | Volume: 18, Issue: 3 | Journal Article |

Cited by: Papers (9)

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Biomedical Knowledge Graphs Construction From Conditional Statements

Tianwen Jiang;Qingkai Zeng;Tong Zhao;Bing Qin;Ting Liu;Nitesh V. Chawla;Meng Jiang

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Year: 2021 | Volume: 18, Issue: 3 | Journal Article |