Department of Microelectronics
Faculty of Electrical Engineering, Mathematics, and Computer Science

dr.ir. J. Dauwels

Associate Professor
Signal Processing Systems (SPS), Department of Microelectronics

Expertise: Machine learning, with applications to autonomous vehicles and biomedical signal processing

Themes: Autonomous sensor systems, Health and Wellbeing

Biography

Dr. Justin Dauwels is an Associate Professor at the TU Delft (Signals Processing Systems Group, Department of Microelectronics), and serves as co-Director of the Safety and Security Institute at the TU Delft. He was an Associate Professor of the School of Electrical and Electronic Engineering at the Nanyang Technological University (NTU) in Singapore till the end of 2020. At the TU Delft, he serves as scientific lead of the Model-Driven Decisions Lab (MoDDL), a first lab for the Knowledge Building program between the police and the TU Delft. He also serves as Chairperson of the EE Board of Studies at the TU Delft, and is a board member of the Co van Ledden Hulsebosch Center (Netherlands Center for Forensic Science and Medicine).

His research interests are in machine learning and generative AI with applications to autonomous systems, and analysis of human behavior and physiology.

He obtained his PhD degree in electrical engineering at the Swiss Polytechnical Institute of Technology (ETH) in Zurich in December 2005. Moreover, he was a postdoctoral fellow at the RIKEN Brain Science Institute (2006-2007) and a research scientist at the Massachusetts Institute of Technology (2008-2010).

He has been elected as IEEE SPS 2024 - 2025 Distinguished Lecturer. He served as Chairman of the IEEE CIS Chapter in Singapore from 2018 to 2020, and served as Associate Editor of the IEEE Transactions on Signal Processing (2018 - 2023), and serves currently as Associate Editor (2021-2023) and Subject Editor (since 2023) of the Elsevier journal Signal Processing, Area Editor C&F for the IEEE Signal Processing Magazine (since 2023), member of the Editorial Advisory Board of the International Journal of Neural Systems (since 2021), and organizer of IEEE conferences and special sessions. He was also Elected Member of the IEEE Signal Processing Theory and Methods Technical Committee and IEEE Biomedical Signal Processing Technical Committee (both in 2018-2023), and is currently Elected Member of the IEEE Machine Learning for Signal Processing Technical Committee and the IEEE Emerging Transportation Technology Testing (ET3) Technical Committee. He has been a JSPS postdoctoral fellow (2007), a BAEF fellow (2008), a Henri-Benedictus Fellow of the King Baudouin Foundation (2008), and a JSPS invited fellow (2010, 2011). His research team has won several best paper awards at international conferences and journals.

His research on intelligent transportation systems has been featured by the BBC, Channel 5, national newspapers (Straits Times, Lianhe Zaobao, and others), and numerous technology websites. Besides his academic efforts, the team of Dr. Justin Dauwels also collaborates intensely with local start-ups, SMEs, and agencies, in addition to MNCs, in the field of data-driven transportation, logistics, and medical data analytics. His academic lab has spawned four startups across a range of industries, ranging from AI for healthcare to autonomous vehicles.

EE2G1 Electrical Engineering for the Next Generation

BSc 2nd year project

EE4685 Bayesian machine learning

Mathematical foundation for machine learning algorithms, presented from a statistical (Bayesian) and optimization point of view.

EE4C12 Machine learning for Electrical Engineering

Introduction at MSc level

ET4386 Estimation and detection

Basics of detection and estimation theory, as used in statistical signal processing, adaptive beamforming, speech enhancement, radar, telecommunication, localization, system identification, and elsewhere.

Model-driven decision lab

Data and model-driven decision making for the Dutch police

Towards robust perception of radar images

Machine learning and Signal Processing for radar systems (digital radar, millimeter-wave radar), automotive sensors, and related applications

Atmospheric Turbulence Informed Machine Learning for Laser Satellite Communications

Physics-informed machine learning algorithms to formulate the optical link performance map

Reliable POwerDown for Industrial Drives

The pioneering EU research project R-PODID started on the 1st of September 2023. This KDT JU co-funded project aims to develop an automated, cloudless, short-term fault-prediction for electric drives, power modules, and power devices, that can be integrated into power converters.

  1. A Discrete Wavelet Transform-Based Lightweight Transformer Model for Intelligent Fault Diagnosis
    Jiarui Zhou; Sinian Li; Justin Dauwels;
    In 2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
    pp. 1251-1255, 2026. DOI: 10.1109/ICASSP55912.2026.11464936

  2. Physics-Informed Intelligent Motor Fault Detection
    Sinian Li; Raj Thilak Rajan; Edmund Marth; Patrick Zorn; Wolfgang Gruber; Justin Dauwels;
    In 33rd European Signal Processing Conference (EUSIPCO),
    IEEE, pp. 1158--1162, 2025.
    document

  3. Compositional Scene Understanding through Inverse Generative Modeling
    Yanbo Wang; Justin Dauwels; Yilun Du;
    In Forty-second International Conference on Machine Learning, ICML 2025, Vancouver, BC, Canada, July 13-19, 2025,
    PMLR, 2025.
    document

  4. Surgical Workflow Analysis: An Explainable Approach
    Christos Spiliadis; Yiheng Chang; Justin Dauwels; Chavdar Bachvarov; John van Den Dobbelsteen; Benno H. W. Hendriks; Maarten van der Elst; Markku Eskola;
    In 2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC),
    pp. 1-7, 2025. DOI: 10.1109/EMBC58623.2025.11253978

  5. Uncertainty-Aware Gate-Lifetime Prediction of p-GaN Gate HEMTs Using Gaussian Processes
    Shuoyan Zhao; Raj Thilak Rajan; Andrea Tallarico; Maurizio Millesimo; Vladislav Volosov; Antonio Imbruglia; Justin Dauwels;
    In 2025 9th International Conference on System Reliability and Safety (ICSRS),
    pp. 152-156, 2025. DOI: 10.1109/ICSRS68021.2025.11422186

  6. NeuroDots: From Single-Target to Brain-Network Modulation: Why and What Is Needed?
    Dirk de Ridder; Muhammad Ali Siddiqi; Justin Dauwels; Wouter A. Serdijn; Christos Strydis;
    Neuromodulation,
    April 16, 2024. DOI: https://doi.org/10.1016/j.neurom.2024.01.003
    document

  7. PEM: Perception Error Model for Virtual Testing of Autonomous Vehicles
    Andrea Piazzoni; Jim Cherian; Justin Dauwels; Lap-Pui Chau;
    IEEE Trans. Intell. Transp. Syst.,
    Volume 25, Issue 1, pp. 670--681, 2024. DOI: 10.1109/TITS.2023.3311633
    document

  8. EAD-GAN: A Generative Adversarial Network for Disentangling Affine Transforms in Images
    Letao Liu; Xudong Jiang; Martin Saerbeck; Justin Dauwels;
    IEEE Trans. Neural Networks Learn. Syst.,
    Volume 35, Issue 3, pp. 3652--3662, 2024. DOI: 10.1109/TNNLS.2022.3195533
    document

  9. Machine Learning Algorithm to Estimate Cardiac Output Based On Less-Invasive Arterial Blood Pressure Measurements
    Alan Hamo; Niki Ottenhof; Jan-Wiebe H. Korstanje; Justin Dauwels;
    In 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024, Orlando, FL, USA, July 15-19, 2024,
    IEEE, pp. 1--4, 2024. DOI: 10.1109/EMBC53108.2024.10781760
    document

  10. Prediction of Postinduction Hypotension by Machine Learning
    Shuoyan Zhao; Alan Hamo; Niki Ottenhof; Jan-Wiebe H. Korstanje; Justin Dauwels;
    In 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024, Orlando, FL, USA, July 15-19, 2024,
    IEEE, pp. 1--4, 2024. DOI: 10.1109/EMBC53108.2024.10782974
    document

  11. MoReSo: A DNN Framework Expediting Content-Based Video Image Retrieval (CBVIR)
    Sinian Li; Doruk Barokas Profeta; Justin Dauwels;
    In 32nd European Signal Processing Conference, EUSIPCO 2024, Lyon, France, August 26-30, 2024,
    IEEE, pp. 551--555, 2024.
    document

  12. Precipitation Nowcasting Using Physics Informed Discriminator Generative Models
    Junzhe Yin; Cristian Meo; Ankush Roy; Zeineh Bou Cher; Mircea Lica; Yanbo Wang; Ruben Imhoff; Remko Uijlenhoet; Justin Dauwels;
    In 32nd European Signal Processing Conference, EUSIPCO 2024, Lyon, France, August 26-30, 2024,
    IEEE, pp. 967--971, 2024.
    document

  13. alphaTC-VAE: On the relationship between Disentanglement and Diversity
    Cristian Meo; Louis Mahon; Anirudh Goyal; Justin Dauwels;
    In The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024,
    OpenReview.net, 2024.
    document

  14. Unveiling Hidden Anomalies: A Hybrid Approach for Surface Mounted Electronics
    Amir Ghorbani Ghezeljehmeidan; Willem Dirk van Driel; Justin Dauwels;
    In 22nd IEEE International Conference on Industrial Informatics, INDIN 2024, Beijing, China, August 18-20, 2024,
    IEEE, pp. 1--6, 2024. DOI: 10.1109/INDIN58382.2024.10774393
    document

  15. Towards Robust Object Detection in Unseen Catheterization Laboratories
    Zipeng Wang; Rick M. Butler; John van den Dobbelsteen; Benno H. W. Hendriks; Maarten Van der Elst; Justin Dauwels;
    In IEEE International Symposium on Medical Measurements and Applications, MeMeA 2024, Eindhoven, The Netherlands, June 26-28, 2024,
    IEEE, pp. 1--6, 2024. DOI: 10.1109/MEMEA60663.2024.10596906
    document

  16. Six-Center Assessment of CNN-Transformer with Belief Matching Loss for Patient-Independent Seizure Detection in EEG
    Wei Yan Peh; Thangavel Prasanth; Yuanyuan Yao; John Thomas; Yee-Leng Tan; Justin Dauwels;
    Int. J. Neural Syst.,
    Volume 33, Issue 3, pp. 2350012:1--2350, 2023. DOI: 10.1142/S0129065723500120
    document

  17. Efficient Variational Bayes Learning of Graphical Models With Smooth Structural Changes
    Hang Yu; Songwei Wu; Justin Dauwels;
    IEEE Trans. Pattern Anal. Mach. Intell.,
    Volume 45, Issue 1, pp. 475--488, 2023. DOI: 10.1109/TPAMI.2022.3140886
    document

  18. Data Science Education: The Signal Processing Perspective [SP Education]
    Sharon Gannot; Zheng-Hua Tan; Martin Haardt; Nancy F. Chen; Hoi-To Wai; Ivan Tashev; Walter Kellermann; Justin Dauwels;
    IEEE Signal Process. Mag.,
    Volume 40, Issue 7, pp. 89--93, 2023. DOI: 10.1109/MSP.2023.3294709
    document

  19. Learning to Solve Multiple-TSP With Time Window and Rejections via Deep Reinforcement Learning
    Rongkai Zhang; Cong Zhang; Zhiguang Cao; Wen Song; Puay Siew Tan; Jie Zhang; Bihan Wen; Justin Dauwels;
    IEEE Trans. Intell. Transp. Syst.,
    Volume 24, Issue 1, pp. 1325--1336, 2023. DOI: 10.1109/TITS.2022.3207011
    document

  20. Sensing and Machine Learning for Automotive Perception: A Review
    Ashish Pandharipande; Chih-Hong Cheng; Justin Dauwels; Sevgi Z. Gurbuz; Javier Ibanez-Guzman; Guofa Li; Andrea Piazzoni; Pu Wang; Avik Santra;
    IEEE Sensors Journal,
    Volume 23, Issue 11, pp. 11097-11115, 2023. DOI: 10.1109/JSEN.2023.3262134

  21. Modeling and Inference of Sparse Neural Dynamic Functional Connectivity Networks Underlying Functional Ultrasound Data
    Ruben Wijnands; Justin Dauwels; Ines Serra; Pieter Kruizinga; Aleksandra Badura; Borbála Hunyadi;
    In ICASSP Workshops,
    pp. 1-5, 2023. DOI: 10.1109/ICASSPW59220.2023.10193029
    document

  22. Nowcasting of Extreme Precipitation Using Deep Generative Models
    Haoran Bi; Maksym Kyryliuk; Zhiyi Wang; Cristian Meo; Yanbo Wang; Ruben Imhoff; Remko Uijlenhoet; Justin Dauwels;
    In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023, Rhodes Island, Greece, June 4-10, 2023,
    IEEE, pp. 1--5, 2023. DOI: 10.1109/ICASSP49357.2023.10094988
    document

  23. Automatic Camera Pose Estimation by Key-Point Matching of Reference Objects
    Jinchen Zeng; Rick M. Butler; John van den Dobbelsteen; Benno H. W. Hendriks; Maarten Van der Elst; Justin Dauwels;
    In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023, Rhodes Island, Greece, June 4-10, 2023,
    IEEE, pp. 1--5, 2023. DOI: 10.1109/ICASSP49357.2023.10095197
    document

  24. Slot-VAE: Object-Centric Scene Generation with Slot Attention
    Yanbo Wang; Letao Liu; Justin Dauwels;
    In International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA,
    PMLR, pp. 36020--36035, 2023.
    document

  25. MERLIon CCS Challenge: A English-Mandarin code-switching child-directed speech corpus for language identification and diarization
    Yi Han Victoria Chua; Hexin Liu; Leibny Paola Garcia; Fei Ting Woon; Jinyi Wong; Xiangyu Zhang; Sanjeev Khudanpur; Andy W. H. Khong; Justin Dauwels; Suzy J. Styles;
    In 24th Annual Conference of the International Speech Communication Association, Interspeech 2023, Dublin, Ireland, August 20-24, 2023,
    ISCA, pp. 4109--4113, 2023. DOI: 10.21437/INTERSPEECH.2023-1446
    document

  26. Investigating model performance in language identification: beyond simple error statistics
    Suzy J. Styles; Yi Han Victoria Chua; Fei Ting Woon; Hexin Liu; Leibny Paola Garcia; Sanjeev Khudanpur; Andy W. H. Khong; Justin Dauwels;
    In 24th Annual Conference of the International Speech Communication Association, Interspeech 2023, Dublin, Ireland, August 20-24, 2023,
    ISCA, pp. 4129--4133, 2023. DOI: 10.21437/INTERSPEECH.2023-1707
    document

  27. A Data-Driven Approach to Estimate and Predict the Traffic Incidents' Queue Length
    Banishree Ghosh; Justin Dauwels;
    In 26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023, Bilbao, Spain, September 24-28, 2023,
    IEEE, pp. 2517--2522, 2023. DOI: 10.1109/ITSC57777.2023.10422644
    document

  28. A Dynamic Object Removal and Reconstruction Algorithm for Point Clouds
    Sarat Chandra Nagavarapu; Anuj Abraham; Nithish Muthuchamy Selvaraj; Justin Dauwels;
    In IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2023, Singapore, December 11-13, 2023,
    IEEE, pp. 1--8, 2023. DOI: 10.1109/SOLI60636.2023.10425733
    document

  29. Recurrent Affine Transform Encoder for Image Representation
    Letao Liu; Xudong Jiang; Martin Saerbeck; Justin Dauwels;
    IEEE Access,
    Volume 10, pp. 18653--18666, 2022. DOI: 10.1109/ACCESS.2022.3150340
    document

  30. Comparison of different Bayesian methods for estimating error bars with incident duration prediction
    Banishree Ghosh; Justin Dauwels;
    J. Intell. Transp. Syst.,
    Volume 26, Issue 4, pp. 420--431, 2022. DOI: 10.1080/15472450.2021.1894936
    document

  31. Disentangling cortical functional connectivity strength and topography reveals divergent roles of genes and environment
    Bianca Burger; Karl{-}Heinz Nenning; Ernst Schwartz; Daniel S. Margulies; Alexandros Goulas; Hesheng Liu; Simon Neubauer; Justin Dauwels; Daniela Prayer; Georg Langs;
    NeuroImage,
    Volume 247, pp. 118770, 2022. DOI: 10.1016/J.NEUROIMAGE.2021.118770
    document

  32. Factored Latent-Dynamic Conditional Random Fields for single and multi-label sequence modeling
    Satyajit Neogi; Justin Dauwels;
    Pattern Recognit.,
    Volume 122, pp. 108236, 2022. DOI: 10.1016/J.PATCOG.2021.108236
    document

  33. Transformer Convolutional Neural Networks for Automated Artifact Detection in Scalp EEG
    Wei Yan Peh; Yuanyuan Yao; Justin Dauwels;
    In 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022, Glasgow, Scotland, United Kingdom, July 11-15, 2022,
    IEEE, pp. 3599--3602, 2022. DOI: 10.1109/EMBC48229.2022.9871916
    document

  34. Challenges in Virtual Testing of Autonomous Vehicles
    Andrea Piazzoni; Roshan Vijay; Jim Cherian; Lyu Chen; Justin Dauwels;
    In 17th International Conference on Control, Automation, Robotics and Vision, ICARCV 2022, Singapore, Singapore, December 11-13, 2022,
    IEEE, pp. 416--421, 2022. DOI: 10.1109/ICARCV57592.2022.10004249
    document

  35. CoPEM: Cooperative Perception Error Models for Autonomous Driving
    Andrea Piazzoni; Jim Cherian; Roshan Vijay; Lap-Pui Chau; Justin Dauwels;
    In 25th IEEE International Conference on Intelligent Transportation Systems, ITSC 2022, Macau, China, October 8-12, 2022,
    IEEE, pp. 3934--3939, 2022. DOI: 10.1109/ITSC55140.2022.9921807
    document

  36. Enhancing Language Identification Using Dual-Mode Model with Knowledge Distillation
    Hexin Liu; Leibny Paola Garcia-Perera; Andy W. H. Khong; Justin Dauwels; Suzy J. Styles; Sanjeev Khudanpur;
    In Odyssey 2022: The Speaker and Language Recognition Workshop, 28 June - 1 July 2022, Beijing, China,
    ISCA, pp. 248--254, 2022. DOI: 10.21437/ODYSSEY.2022-35
    document

  37. Automated Adult Epilepsy Diagnostic Tool Based on Interictal Scalp Electroencephalogram Characteristics: A Six-Center Study
    John Thomas; Thangavel Prasanth; Wei Yan Peh; Jin Jing; Yuvaraj Rajamanickam; Sydney S. Cash; Rima Chaudhari; Sagar Karia; Rahul Rathakrishnan; Vinay Saini; Nilesh Shah; Rohit Srivastava; Yee{-}Leng Tan; M. Brandon Westover; Justin Dauwels;
    Int. J. Neural Syst.,
    Volume 31, Issue 5, pp. 2050074:1--2050, 2021. DOI: 10.1142/S0129065720500744
    document

  38. Multi-Center Validation Study of Automated Classification of Pathological Slowing in Adult Scalp Electroencephalograms Via Frequency Features
    Wei Yan Peh; John Thomas; Elham Bagheri; Rima Chaudhari; Sagar Karia; Rahul Rathakrishnan; Vinay Saini; Nilesh Shah; Rohit Srivastava; Yee-Leng Tan; Justin Dauwels;
    Int. J. Neural Syst.,
    Volume 31, Issue 6, pp. 2150016:1--2150, 2021. DOI: 10.1142/S0129065721500167
    document

  39. Time-Frequency Decomposition of Scalp Electroencephalograms Improves Deep Learning-Based Epilepsy Diagnosis
    Thangavel Prasanth; John Thomas; Wei Yan Peh; Jin Jing; Yuvaraj Rajamanickam; Sydney S. Cash; Rima Chaudhari; Sagar Karia; Rahul Rathakrishnan; Vinay Saini; Nilesh Shah; Rohit Srivastava; Yee-Leng Tan; M. Brandon Westover; Justin Dauwels;
    Int. J. Neural Syst.,
    Volume 31, Issue 8, pp. 2150032:1--2150, 2021. DOI: 10.1142/S0129065721500325
    document

  40. Editorial: Celebration of the 30th Anniversary of IJNS
    Justin Dauwels;
    Int. J. Neural Syst.,
    Volume 31, Issue 12, pp. 2103013:1--2103, 2021. DOI: 10.1142/S0129065721030131
    document

  41. A Generic GPU-Accelerated Framework for the Dial-A-Ride Problem
    Ramesh Ramasamy Pandi; Songguang Ho; Sarat Chandra Nagavarapu; Justin Dauwels;
    IEEE Trans. Intell. Transp. Syst.,
    Volume 22, Issue 10, pp. 6473--6488, 2021. DOI: 10.1109/TITS.2020.2992560
    document

  42. Context Model for Pedestrian Intention Prediction Using Factored Latent-Dynamic Conditional Random Fields
    Satyajit Neogi; Michael Hoy; Kang Dang; Hang Yu; Justin Dauwels;
    IEEE Trans. Intell. Transp. Syst.,
    Volume 22, Issue 11, pp. 6821--6832, 2021. DOI: 10.1109/TITS.2020.2995166
    document

  43. R3L: Connecting Deep Reinforcement Learning To Recurrent Neural Networks For Image Denoising Via Residual Recovery
    Rongkai Zhang; Jiang Zhu; Zhiyuan Zha; Justin Dauwels; Bihan Wen;
    In 2021 IEEE International Conference on Image Processing, ICIP 2021, Anchorage, AK, USA, September 19-22, 2021,
    IEEE, pp. 1624--1628, 2021. DOI: 10.1109/ICIP42928.2021.9506323
    document

  44. End-to-End Language Diarization for Bilingual Code-Switching Speech
    Hexin Liu; Leibny Paola Garcia-Perera; Xinyi Zhang; Justin Dauwels; Andy W. H. Khong; Sanjeev Khudanpur; Suzy J. Styles;
    In 22nd Annual Conference of the International Speech Communication Association, Interspeech 2021, Brno, Czechia, August 30 - September 3, 2021,
    ISCA, pp. 1489--1493, 2021. DOI: 10.21437/INTERSPEECH.2021-82
    document

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Last updated: 6 Sep 2025

Justin Dauwels

PhD students

MSc students

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