Daniel Andrade

Last Updated :2025/11/07

Affiliations, Positions
Education and Research Center for Artificial Intelligence and Data Innovation, Associate Professor
Web Site
https://sites.google.com/view/andrade-stats
E-mail
andradehiroshima-u.ac.jp
Self-introduction
My research covers a broad field in applied machine learning ranging from classification, natural language processing, clustering/outlier detection and uncertainty quantification in various domains (e.g. text, medical and security). My current research interests are especially in Text/Numerical Data Analysis, Model Selection, Bayesian Inference and Bayesian Statistics in general.

Basic Information

Major Professional Backgrounds

  • 2011/10/01, 2021/01/31, NEC, Central Research Laboratories, Researcher
  • 2020/04/01, 2025/03/31, Rikkyo University, Graduate School of Artificial Intelligence and Science, Visiting Associate Professor
  • 2021/02/01, Hiroshima University, Education and Research Center for Artificial Intelligence and Data Innovation, Associate Professor

Educational Backgrounds

  • University of Passau, Department of Informatics and Mathematics, Informatics, Germany, 2001/10, 2007/10
  • The University of Tokyo, Graduate School of Information Science and Technology, Computer Science, Japan, 2008/10, 2011/09
  • The Graduate University for Advanced Studies (SOKENDAI), School of Multidisciplinary Sciences, Department of Statistical Science, Statistics, 2016/04, 2019/09

Academic Degrees

  • PhD (Statistics), The Graduate University for Advanced Studies (SOKENDAI)
  • PhD (Computer Science), The University of Tokyo
  • Diploma (Informatics), University of Passau

Research Fields

  • Informatics;Principles of Informatics;Statistical science

Research Keywords

  • Computational Statistics, Machine Learning, Bayesian Statistics, Natural Language Processing

Affiliated Academic Societies

  • International Society for Bayesian Analysis

Educational Activity

Course in Charge

  1. 2025, Liberal Arts Education Program1, 2Term, Computer Programming
  2. 2025, Undergraduate Education, 2Term, Linear Regression Model
  3. 2025, Undergraduate Education, 4Term, Informatics and Data Science Exercise IV
  4. 2025, Undergraduate Education, 1Term, Intelligence Science Seminar I
  5. 2025, Undergraduate Education, 2Term, Intelligence Science Seminar II
  6. 2025, Undergraduate Education, Second Semester, Graduation Thesis
  7. 2025, Graduate Education (Master's Program) , 1Term, Special Exercises on Informatics and Data Science A
  8. 2025, Graduate Education (Master's Program) , 2Term, Special Exercises on Informatics and Data Science A
  9. 2025, Graduate Education (Master's Program) , 3Term, Special Exercises on Informatics and Data Science B
  10. 2025, Graduate Education (Master's Program) , 4Term, Special Exercises on Informatics and Data Science B
  11. 2025, Graduate Education (Master's Program) , Year, Special Study on Informatics and Data Science

Research Activities

Academic Papers

  1. A Comparative Study of Bayesian Variable Selection with Missing Data: BAS and BART for Healthcare Data Analysis, International Conference on Mathematical Applications in Engineering, 2025
  2. SSAT: Sensor-Satellite Auto-Correlation Transformer for Enhanced Aerosol Optical Depth Prediction, IEEE ACCESS, 13, 130832-130845, 2025
    Link to Paper Search Results by DOI
  3. On the effectiveness of partially deterministic Bayesian neural networks, COMPUTATIONAL STATISTICS, 40(5), 2491-2518, 202506
    Link to Paper Search Results by DOI
  4. Improved Variance Estimation From Trimmed Samples, STAT, 13(4), 202412
    Link to Paper Search Results by DOI
  5. Stabilizing training of affine coupling layers for high-dimensional variational inference, MACHINE LEARNING-SCIENCE AND TECHNOLOGY, 5(4), 20241201
    Link to Paper Search Results by DOI
  6. On the effectiveness of partially deterministic Bayesian neural networks, Computational Statistics, 2024
  7. LOFT - Stable Training of Normalizing Flows for Variational Inference, Workshop on Tractable Probabilistic Modeling (TPM), 2023
  8. Robust Gaussian Process Regression with the Trimmed Marginal Likelihood, Proceedings of Conference on Uncertainty in Artificial Intelligence (UAI), 2023
  9. Knowledge Fusion Using Dempster-Shafer Theory and the Imprecise Dirichlet Model, Proceedings of IEEE Soft Computing in Industrial Applications (SMCia), 142-148, 2008
  10. Lower bound Bayesian networks: an efficient inference of lower bounds on probability distributions in Bayesian networks, Proceedings of Conference on Uncertainty in Artificial Intelligence (UAI), 10-18, 2009
  11. Robust Measurement and Comparison of Context Similarity for Finding Translation Pairs, Proceedings of International Conference on Computational Linguistics (COLING), 19-27, 2010
  12. Effective use of Dependency Structure for Bilingual Lexicon Creation, Proceedings of International Conference on Computational Linguistics and Intelligent Text Processing (CiCling), 80-92, 2011
  13. Learning the Optimal use of Dependency-parsing Information for Finding Translations with Comparable Corpora, Proceedings of ACL Workshop on Building and Using Comparable Corpora, 10-18, 2011
  14. Translation Acquisition Using Synonym Sets, Proceedings of Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (HLT-NAACL), 655-660, 2013
  15. Synonym Acquisition Using Bilingual Comparable Corpora, Proceedings of International Joint Conference on Natural Language Processing (IJCNLP), 1077-1081, 2013
  16. Chinese Informal Word Normalization: an Experimental Study, Proceedings of International Joint Conference on Natural Language Processing (IJCNLP), 127-135, 2013
  17. Cross-lingual Text Classification Using Topic-Dependent Word Probabilities, Proceedings of Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (HLT-NAACL), 1466-1471, 2015
  18. Analogy-based Reasoning with Memory Networks for Future Prediction, Workshop on Cognitive Computation: Integrating Neural and Symbolic Approaches (CoCo), CEUR Workshop Proceedings, 1-9, 2016
  19. Efficient Bayes Risk Estimation for Cost-Sensitive Classification, International Conference on Artificial Intelligence and Statistics (AISTATS), Proceedings of Machine Learning Research (PMLR), 3372-3381, 2019
  20. POSTER: Detecting Suspicious Processes from Log-Data via a Bayesian Block Model, Proceedings of the ACM Asia Conference on Computer and Communications Security, 922-924, 2020
  21. Statistical Extraction and Comparison of Pivot Words for Bilingual Lexicon Extension, ACM Transactions on Asian Language Information Processing (TALIP), 11(2), 1-31, 2012
  22. Analysis of the Use of Background Distribution for Naive Bayes Classifiers, Journal of Intelligent Systems, 28(2), 1-15, 2017
  23. Leveraging knowledge bases for future prediction with memory comparison networks, AI Communications, 31(6), 465-483, 2018
  24. ★, Exploiting Covariate Embeddings for Classification Using Gaussian Processes, Pattern Recognition Letters, 104(1), 8-14, 2018
  25. ★, Robust Bayesian model selection for variable clustering with the Gaussian graphical model, Statistics and Computing, 30(2), 351-376, 2020
  26. Disjunct Support Spike and Slab Priors for Variable Selection in Regression under Quasi- sparseness, Stat, 1-19, 2020
  27. Adaptive covariate acquisition for minimizing total cost of classification, MACHINE LEARNING, 110(5), 1067-1104, 202105
    Link to Paper Search Results by DOI
  28. Convex covariate clustering for classification, PATTERN RECOGNITION LETTERS, 151, 193-199, 202111
    Link to Paper Search Results by DOI

Invited Lecture, Oral Presentation, Poster Presentation

  1. Stabilizing training of affine coupling layers for high-dimensional variational inference, 2025, With Invitation, English, BIRS Workshop, "Efficient Approximate Bayesian Inference", Canada
  2. Implementing Recent VI Methods (Interactive Tutorial), 2025, With Invitation, English, BIRS Workshop, "Efficient Approximate Bayesian Inference", Canada
  3. Stable Training of Normalizing Flows for Variational Inference, 2023, With Invitation, English, Arizona State University
  4. Robust Methods for Gaussian Process Regression and the Trimmed Marginal Likelihood Approach, 2022, With Invitation, Japanese, Kanto Gakuin University
  5. Introduction to Statistics and Machine Learning for AI, 2017, Japanese, Public Lecture, Iida
  6. Special Seminar on Artificial Intelligence (Probabilistic Modeling), Visiting Associate Professor, 2020, Japanese, Rikkyo University
  7. Introduction to Informatics (AI Systems, ICT, Computational Theory), Visiting Associate Professor, 2020, Japanese, Rikkyo University
  8. The Basics of Feature selection in Regression Models, 2021, With Invitation, Japanese, Organization for AI Data Innovation Education and Research Initiatives, Hiroshima University
  9. Introduction to Informatics (AI Systems, ICT, Computational Theory), Visiting Associate Professor, 2021, Japanese, Rikkyo University
  10. Special Seminar on Artificial Intelligence (Probabilistic Modeling), Visiting Associate Professor, 2021, Japanese, Rikkyo University

Awards

  1. 2008/06, Best Paper Award, IEEE Soft Computing in Industrial Applications (SMCia)
  2. 2009/05, IBM Ph.D. Scholarship Award
  3. 2011/02, Best Paper Award (3rd Place), Conference on Computational Linguistics and Intelligent Text Processing (CiCling)
  4. 2016/06, IPSJ Kiyasu Special Industrial Achievement Award)
  5. 2016/06, Best Reviewer Award, Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT)
  6. 2019/09, Dean's Award, School of Multidisciplinary Sciences, SOKENDAI
  7. 2020/09, Best Reviewer Award (Top 33%), International Conference on Machine Learning (ICML)

Patented

  1. Patent, 11201404678R (SG), 2015/05, Term Synonym Acquisition Method and Term Synonym Acquisition Apparatus
  2. Patent, 11201404225W (SG), 2016/05, Term Translation Acquisition Method and Term Translation Acquisition Apparatus
  3. Patent, 11201604193Q (SG), 2016/09, Document Classification Method
  4. Patent, 09542386 (US), 2017/01, Entailment Evaluation Device, Entailment Evaluation Method and Recording Medium
  5. Patent, 06090531, 2017/02, Word Translation Acquisition Method
  6. Patent, 6281491, 2018/02, Text Mining System
  7. Patent, 10409848 (US), 2018/04, Text Mining System
  8. Patent, 6455068, 2018/12, Keyword Extraction System
  9. Patent, 6467893, 2019/01, Information Enrichment of Existing Word Embeddings
  10. Patent, 20190164072 (US), 2019/05, Inference System, Information Processing System, Inference Method, and Recording Medium
  11. Patent, 20190180192 (US), 2019/06, An Information Processing System, An Information Processing Method and a Computer Readable Storage Medium
  12. Patent, 10324971, 2019/06, Feature Weighting for Naïve Bayes Classifiers Using a Generative Model
  13. Patent, 10354010 (US), 2019/07, Incorporating Word Similarity in Bag-of-words Representations
  14. Patent, 6690713, 2020/05, Inference System

External Funds

Acceptance Results of Competitive Funds

  1. KAKENHI-C (Basic Research Funding), Computationally Feasible Confidence Regions for Bayes Factors with Iteratively Refined Normalizing Flows

Social Activities

History as Committee Members

  1. Annual Conference of the Japanese Society for Artificial Intelligence, 2021/01, 2021/06

History as Peer Reviews of Academic Papers

  1. 2025, Journal of the American Statistical Association (JASA)
  2. 2025, Computational Statistics
  3. 2025, NeurIPS 2025 (Neural Information Processing Systems)
  4. 2025, ICML 2025 (International Conference on Machine Learning)
  5. 2024, Statistics and Computing
  6. 2024, ICML 2024 (International Conference on Machine Learning)
  7. 2023, Scientific Reports
  8. 2023, ICML 2023 (International Conference on Machine Learning)
  9. 2022, AISTATS 2022 (Artificial Intelligence and Statistics)
  10. 2022, BMC Medical Research Methodology
  11. 2021, NeurIPS 2021 (Conference on Neural Information Processing Systems)
  12. 2021, ICML 2021 (International Conference on Machine Learning)
  13. 2020, ICLR 2021 (International Conference on Learning Representations)
  14. 2020, Computational Statistics & Data Analysis
  15. 2020, ICML 2020 (International Conference on Machine Learning)
  16. 2020, IEEE Transactions on Neural Networks and Learning Systems
  17. 2018, Knowledge-Based Systems
  18. 2018, ACL 2018 (Annual Conference of the Association for Computational Linguistics) Program Committee Member
  19. 2016, NAACL HLT 2016 (Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies)
  20. 2014, IEICE Transactions on Information and Systems