Dr Chang Wei Tan

Applied Scientist @ Oracle

I'm interested in

About

I am an Applied Scientist at Oracle, developing Large Language Model (LLM) applications for healthcare. My journey to Oracle builds on a strong academic foundation as a Research Fellow at the Department of Data Science and AI, Monash University, where I specialized in Time Series Analysis and Machine Learning applications. I completed my PhD at the Faculty of Information Technology, Monash University, under the supervision of Professor Geoff Webb, Dr François Petitjean, and Dr Paul Reichl. My doctoral thesis, “Time Series Classification at Scale”, advanced scalable time series classification techniques, resulting in efficient algorithms for large datasets.


During my doctoral studies, I was honored with a best paper award for "Efficient search of the best warping window for Dynamic Time Warping", introducing a novel algorithm for learning Dynamic Time Warping (DTW) parameters. My research excellence was further recognized with the prestigious Mollie Holman medal for the best doctoral thesis in the Faculty of Information Technology.


My expertise extends beyond academia. I have collaborated with the Institute of Railway Technology (IRT) at Monash University to enhance railway track maintenance using advanced time series analysis, and provided data science services to Stemly, developing autonomous supply chain demand forecasting solutions.


I have also contributed to research in Time Series Extrinsic Regression (TSER), focusing on predicting continuous values from time series data, and explored EEG-based applications such as epilepsy diagnosis and driver distraction detection.


I led efforts in the Computational Cultural Understanding (CCU) project, part of the Defense Advanced Research Projects Agency (DARPA) initiative, focusing on predicting changes in conversations to deepen cultural understanding.


My transition to Oracle marks a new chapter, where I leverage my academic and industry experience to create impactful LLM-driven healthcare solutions. My multidisciplinary background—spanning scalable time series classification, TSER, EEG analytics, cultural understanding, and supply chain forecasting—enables me to bridge research and real-world innovation, advancing both technology and its societal benefits.

Research Interest

  • Artificial Intelligence
  • Digital Health
  • Time Series Analysis
  • Machine Learning
  • EEG Research
  • Railway Engineering

Research

Working papers

  1. A. Fawaz, A. Dempster, C.W. Tan, M. Herrmann, L. Miller, D.F. Schmidt, S. Berretti, J. Weber, M. Devanne, G. Forestier, and G.I. Webb, "An Approach to Multiple Comparison Benchmark Evaluations that is Stable Under Manipulation of the Comparate Set"
  2. A. Dempster, N. Foumani, C.W. Tan, L. Miller, A. Mishra, M. Salehi, C. Pelletier, D. Schmidt and G.I. Webb, MONSTER: Monash Scalable Time Series Evaluation Repository

Publications

  1. C.W. Tan, M. Herrmann, M. Salehi, and G.I. Webb, "Proximity Forest 2.0: A new effective and scalable similarity-based classifier for time series" in Data Mining and Knowledge Discovery, 2025 doi
  2. G. Ho, C.W. Tan, Z. Darban, M. Salehi, G. Haffari, and W. Buntine MTP: A Dataset for Multi-Modal Turning Points in Casual Conversations in The 62nd Annual Meeting of the Association for Computational Linguistics, 2024
  3. N. Foumani, C.W. Tan, G.I Webb, H. Rezatofighi, and M Salehi Series2vec: similarity-based self-supervised representation learning for time series classification in Data Mining and Knowledge Discovery, 2024 doi
  4. N. Foumani, L. Miller, C.W. Tan, G.I. Webb, G. Forestier, and M. Salehi, "Deep Learning for Time Series Classification and Extrinsic Regression: A Current Survey" in ACM Computing Surveys, 2024
  5. M. Janmohamed, D. Nhu, L. Shakathreh, O. Gonen, L. Kuhlman, A. Gilligan, C.W Tan, P. Perucca, T.J. O’Brien, and P. Kwan "Comparison of automated spike detection software in detecting epileptiform abnormalities on scalp-EEG of genetic generalized epilepsy patients" in Journal of Clinical Neurophysiology, 2023
  6. C. Nguyen, C.W. Tan, E. Daly and V. Pauwel Efficient analysis of hydrological connectivity using 1D and 2D Convolutional Neural Networks in Advances in Water Resources, 2023
  7. C. Nguyen, C.W. Tan, E. Daly and V. Pauwel "Applications of convolutional neural networks and remote sensing data to predict flood extents" in The 25th International Congress on Modelling and Simulation (MODSIM2023), 2023
  8. N. Foumani, C.W. Tan, G.I. Webb, and M. Salehi, "Improving Position Encoding of Transformers for Multivariate Time Series Classification" in Data Mining and Knowledge Discovery, 2023
  9. M. Herrmann, C.W. Tan, and G.I. Webb, "Parameterizing the cost function of Dynamic Time Warping with application to time series classification" in Data Mining and Knowledge Discovery, 2023 doi
  10. C.W. Tan, M. Herrmann, and G.I. Webb, "Ultra-fast meta-parameter optimization for time series similarity measures with application to nearest neighbour classification" in Knowledge and Information Systems, 2023 doi
  11. D. Nhu, M. Janmohamed, L. Shakhatreh, O. Gonen, P. Perucca, A. Gilligan, P. Kwan, T.J. O'Brien, C.W. Tan, and L. Kuhlmann, "Automated Interictal Epileptiform Discharge Detection from Scalp EEG Using Scalable Time-series Classification Approaches" in International Journal of Neural System, 2023 doi
  12. D. Nhu, M. Janmohamed, A. Antonic-Baker, P. Perucca, T.J. O'Brien, A. Gilligan, P. Kwan, C.W. Tan, and L. Kuhlmann, "Deep learning for automated epileptiform discharge detection from scalp EEG: a systematic review" in Journal of Neural Engineering, 2022 doi
  13. C.W. Tan, A. Dempster, C. Bergmeir, and G.I. Webb, "MultiRocket: Multiple pooling operators and transformations for fast and effective time series classification" in Data Mining and Knowledge Discovery, 2022 doi
  14. M. Janmohamed, D. Nhu, L. Kuhlmann, A. Gilligan, C.W. Tan, P. Perucca, T.J. O'Brien, and P. Kwan, "Moving the field forward: detection of epileptiform abnormalities on scalp electroencephalography using deep learning—clinical application perspectives" in Brains Communications, 2022 doi
  15. C.W. Tan, M. Herrmann, and G.I. Webb, "Ultra fast warping window optimization for Dynamic Time Warping" in IEEE International Conference on Data Mining (ICDM 2021), IEEE, 2021
  16. N. Foumani, C.W. Tan, and M. Salehi, "Disjoint-CNN for Multivariate Time Series Classification" in IEEE International Conference on Data Mining Workshops (ICDMW 2021), IEEE, 2021 doi
  17. D. Nhu, M. Janmohamed, P. Perucca, A. Gilligan, P. Kwan, T.J. O'Brien, C.W. Tan, and L. Kuhlmann, "Graph Convolutional Network For Generalized Epileptiform Abnormality Detection On EEG" in IEEE Signal Processing in Medicine and Biology Symposium (SPMB 2021), IEEE, 2021
  18. C.W. Tan, C. Bergmeir, F. Petitjean, and G.I. Webb, "Time Series Extrinsic Regression: Predicting numeric values from time series data" in Data Mining and Knowledge Discovery, 2021 doi
  19. D. Nhu, M. Janmohamed, L. Shakhatreh, O. Gonen, P. Kwan, A. Gilligan, C.W. Tan, and L. Kuhlmann, "Automated Inter-ictal Epileptiform Discharge Detection From Routine EEG" in Studies in Health Technology and Informatics, 2021 doi
  20. C.W. Tan, F. Petitjean, and G.I. Webb, "FastEE: Fast Ensembles of Elastic Distances for time series classification" in Data Mining and Knowledge Discovery 2020 doi
  21. C.W. Tan, F. Petitjean, and G.I. Webb, "Elastic bands across the path: A new framework and method to lower bound DTW" in 2019 SIAM International Conference on Data Mining (SDM19), SIAM, 2019 doi
  22. C.W. Tan, M. Herrmann, G. Forestier, G.I. Webb, and F. Petitjean, "Efficient search of the best warping window for Dynamic Time Warping" in 2018 SIAM International Conference on Data Mining (SDM18), SIAM, 2018 Best Research Paper Award doi
  23. C.W. Tan, G.I. Webb, F. Petitjean and P. Reichl, "Machine learning approaches for tamping effectiveness prediction" in 11th International Heavy Haul Association Conference (IHHA), IHHA, 2017
  24. C.W. Tan, G.I. Webb, F. Petitjean and P. Reichl, "Tamping Effectiveness Prediction Using Supervised Machine Learning Techniques" in First International Conference on Rail Transportation (ICRT), Southwest Jiaotong University, 2017 doi
  25. F. Wu, C.W. Tan, M. Sarvi, C. Rudiger and M. Yuce, "Design and Implementation of a Low-Power Wireless Sensor Network Platform Based on XBee" in 2017 IEEE 85th Vehicular Technology Conference (VTC2017), IEEE Vehicular Technology Society, 2017 doi
  26. C.W. Tan, G.I. Webb, and F. Petitjean, "Indexing and classifying gigabytes of time series under time warping" in 2017 SIAM International Conference on Data Mining (SDM17), SIAM, 2017 doi

Program committees / Refereeing

Journals

Conferences and Workshops

Achievements

Awards

  1. 2019 - Mollie Holman Medal awarded by Monash University for the best doctoral thesis in the Faculty of Information Technology
  2. 2018 – Best Research Paper Award awarded by the Society for Industrial and Applied Math (SIAM) International Conference on Data Mining 2018 (SDM18).
  3. 2018 – SIAM Student Travel Award awarded by the Society for Industrial and Applied Math (SIAM) International Conference on Data Mining 2018 (SDM18) to selected students traveling to a SIAM conferences.
  4. 2017 – SIAM Student Travel Award awarded by the Society for Industrial and Applied Math (SIAM) International Conference on Data Mining 2018 (SDM17) to selected students traveling to a SIAM conferences.
  5. 2015 – Faculty of Engineering Dean’s Honour List 2014 awarded by Monash University to students in recognition of attaining an average of 80% or above in 2014 academic year.
  6. 2014 – Third Prize in Final Year Project Poster Competition, Academic Award awarded by Monash University ECSE Department to the student with the best final year project poster voted by academic staffs at the ECSE poster night. During this event, ECSE final year students showcase their project to academic staffs, and industry partners.
  7. 2014 – Jack Wilson Prize Award awarded by Wilson Transformer to level 3 Electrical Engineering student who shows the greatest proficiency and initiative in Electrical Power Engineering.
  8. 2013 – Faculty of Engineering Dean’s Honour List 2012 awarded by Monash University to students in recognition of attaining an average of 80% or above in 2012 academic year
  9. 2012 – Faculty of Engineering Dean’s Honour List 2011 awarded by Monash University to students in recognition of attaining an average of 80% or above in 2014 academic year
  10. 2012 – Golden Key International Honor Society Award. This is a life-long award for the top 15% based on academic achievement.

Scholarships

  1. 2018 – Monash University Postgraduate Publications Award (PPA). The PPA provides support for high-achieving students who, having submitted their thesis, wish to write up some of their research for publication while they await the result of their examination.
  2. 2015 – Australian Postgraduate Award (APA) Scholarship. APA scholarships are awarded to students of exceptional research potential undertaking a HDR in Australia. It is currently known as Research Training Program (RTP) scheme.
  3. 2015 – Monash University Faculty of Engineering Summer Research Scholarship 2014/2015. Summer research program for high achieving students to assist lecturers in researches during the summer.
  4. 2014 – Monash University Faculty of Engineering Summer Research Scholarship 2013/2014.Summer research program for high achieving students to assist lecturers in researches during the summer.

Experiences

Work

  1. 2025 Apr – Current – Senior Applied Scientist – Oracle Health and AI
  2. 2024 Oct – 2025 Feb – Senior Data Scientist – Stemly AI
  3. 2019 Aug – 2024 Aug – Research Fellow – Department of Data Science and AI, Monash University
  4. 2018 Apr – 2018 Dec – Teaching Associate (ENG1002) – Department of Electrical and Computer Systems Engineering (ECSE), Monash University
  5. 2018 Jan – 2018 Apr – Data Research Associate (Intern) – DataSpark Singapore
  6. 2015 Jun – 2017 Nov – Teaching Associate (ENG1002, ECE4058) – Department of Electrical and Computer Systems Engineering (ECSE), Monash University
  7. 2014 Jun – 2015 Dec – Research Assistant – Biomedical Integrated Circuits and Sensors Laboratory (BICS), Monash University
  8. 2012 Dec – 2013 Feb – Electrical Engineer (Intern) – Sarawak Energy
  9. 2012 Jan – 2012 Feb – Electrical Consultant (Intern) – Perunding ElecMec

Volunteering

  1. 2016 Jan – 2017 Apr – Assistant Secretary, Monash IEEE Student Branch
  2. 2016 Jun – Year 8 ChallENGe – Faculty of Engineering, Monash University
  3. 2012 Jun – MUISS Winter Swoop – Monash University International Student Society (MUISS)

Competitions

  1. 2018 May – 3 Minute Thesis (3MT) – Faculty of Information Technology, Monash University
  2. 2017 May – 3 Minute Thesis (3MT) – Faculty of Information Technology, Monash University

Lab Visits

  1. 2019 December – Visiting Researcher to Professor Tony Bagnall's Group at School of Computing Sciences, University of East Anglia (UEA) – Norwich
  2. 2018 May – Visiting PhD Student to Professor Eamonn Keogh‘s Lab at Computer Science & Engineering Department, University of California (UCR) – Riverside

Contact

I am available on LinkedIn, ResearchGate, Twitter as well as Github. Otherwise, feel free to drop me an email at the email address below.

Location:

Oracle Melbourne, 417 St Kilda Rd, Melbourne VIC 3004