Dixon Vimalajeewa

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Dixon Vimalajeewa

Asst Professor Statistics University of Nebraska-Lincoln

Contact

Address
HARH 343F
Lincoln NE 68583-0963,
Phone
402-472-2084 On-campus 2-2084
Email
hvimalajeewa2@unl.edu

Areas of Expertise: Wavelets-based Signal Processing, Distributed Computing, Machine Learning, Mathematical Modelling, Internet of Things

Dr. Dixon Vimalajeewa earned his PhD in Computer Science from Southeast Technological University (SETU) in Ireland in 2020. He has been a part of the UNL statistics department since August 2023. Prior to joining UNL, he held the position of a postdoctoral research associate at the Department of Statistics, Texas A&M University, under the guidance of Dr. Brani Vidakovic, during the period of 2021 to 2023. Additionally, he also contributed as a postdoctoral researcher at the Walton Institute, Ireland, under the supervision of Dr. Sasitharan Balasubramaniam, from 2020 to 2021.

Dr. Vimalajeewa engages in interdisciplinary research at the nexus of various data-science domains, including wavelets, fractality, multifractality, scalable machine learning, statistical signal and image processing, and statistical inference in multiscale domains. The overarching objective is to integrate statistical learning methods with contemporary data science frameworks to address the challenges of processing large-scale and complex datasets effectively.

Education

PhD in Computer Science, South East Technological University (SETU), 2020.

  • Dissertation: Distributed Learning and Data Processing for Smart Farming.
  • Advisors: Prof. Sasitharan Balasubramaniam and Prof. Donagh P. Berry.
  • Courses: Big Data Analytics and Deep Neural Network in Python.

 MSc (Technology) in Computational Engineering, Lappeenranta University of Technology (LUT), Finland,

2015.

  •  Dissertation: Parameter Identification in Time Series Models.- Supervisors: Prof. Marko Linen and Prof. Heikki Haario.
  • Courses: Statistical Analysis in Modeling, Design of Experiments, Stochastic Theory and Models, Membrane Technology, Modeling Methodology in Process Engineering, Fuzzy Engineering and Data Analysis.

BSc ( First Class Honours) in Mathematics and Statistics, University of Ruhuna, Sri Lanka, 2012.

  •  Dissertation: Non-parametric Kennel Smoothing Technique with Boundary Correction Methods for Regression Analysis.
  • Courses: Mathematics, Statistics, & Computer Science.

Peer-Reviewed Articles

  1. Dixon Vimalajeewa, R. J. Hinton, F. Rugeri, B. Vidakovic, An Advanced Self-similarity measure: Average of Level-pairwise Hurst Exponent Estimates, IEEE Transactions in Biomedical Engineering, vol. 72, no. 8, pp. 2567-2579, 2025 (involves PhD student supervision).
  2. Dixon Vimalajeewa, C. Lee, B. Vidakovic, A Method for Detecting Murmurous Heart Sounds based on Self-similar Properties, Nature Scientific Reports, vol. 15, no. 1, 2025.
  3. D. Maywald and Dixon Vimalajeewa, Utilizing Wavelet Transform in the Analysis of Scaling Dynamics for Milk Quality Evaluation, Time Series and Wavelet Analysis, pp. 261-279, 2024 (involves PhD student supervision).
  4. R.J. Hinton, Jr., J. Byun, and Dixon Vimalajeewa, B. Vidakovic, Ovarian Cancer Diagnostics using Wavelet Packet Scaling Descriptors, Biomedical Signal Processing, vol. 102, 2024 (involves student supervision).
  5. Dixon Vimalajeewa, Anirban Das Gupta, Fabrizio Ruggeri, Brani Vidakovic, Gamma-Minimax Wavelet Shrinkage for Signals with Low SNR , The New England Journal of Statistics in Data Science, 2023.
  6. Jongphil Kim, Dixon Vimalajeewa, and Brani Vidakovic, Analysis and Classification of 1H-NMR Spectra by Multifractal Analysis, PLOS One, 2023.
  7. Dixon Vimalajeewa, Ethan McDonald, Magan Tung, Brani Vidakovic, Parkinson’s Disease Diagnosis With Gait Characteristics Extracted Using Wavelet Transforms, IEEE Journal of Translational Engineering in Health and Medicine, vol. 11, pp. 271-281, 2023 (involves MSc and undergraduate student supervision).
  8. Dixon Vimalajeewa, Scott Alan Bruce, Brani Vidakovic, Early Detection of Ovarian Cancer by Wavelet Analysis of Protein Mass Spectra. Statistics in Medicine, 2023.
  9. Dixon Vimalajeewa, Ethan McDonald, Scott Alan Bruce, Brani Vidakovic, Wavelets-based approach for diagnosing Attention Deficit Hyperactivity Disorder (ADHD), Nature Scientific Reports, 2022 (involves undergraduate student supervision).
  10. Dixon Vimalajeewa, Sasitharan Balasubramaniam, Donagh. P Berry, Gerald Barry, Virus particle propagation and infectivity along the respiratory tract and a case study for SARS-CoV-2, Nature Scientific Reports, vol. 12, 2022.
  11. Dixon Vimalajeewa, Sasitharan Balasubramaniam, Donagh P Berry, Chamil Kulatunga, A Service-based Joint Model Used for Distributed Learning: Application for Smart Agriculture, IEEE Transactions on Emerging Topics in Computing, vol. 10, no. 2, pp. 838-854, 2022.
  12. Dixon Vimalajeewa, Chamil Kulatunga, Brendatte O’Brien, Donagh P Berry, Leveraging Social Network Analysis for Evaluating Animal Cohesion. IEEE Transactions on Computational Social Systems, vol. 6, no. 2, pp. 323-337, 2019.
  13. Dixon Vimalajeewa, Chamil Kulatunga, Donagh P. Berry, Learning in the compressed data domain: Application to milk quality prediction, Elsevier Journal of Information Sciences, vol. 459, pp. 149-167, 2018.

  14. Chamil Kulatunga, Kriti Bhargava, Dixon Vimalajeewa, Stephan Ivanov, Cooperative In-network Computation in Energy Harvesting Device Clouds, Sustainable Computing: Informatics and Systems, vol. 16, pp. 106-116, 2017.

     

Conference Proceedings

  1.  Dixon Vimalajeewa, Sasitharan Balasubramaniam, Digestive system dynamics in molecular communication perspectives, In: Nakano, T. (eds) Bio-Inspired Information and Communications Technologies. BICT 2021, Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol. 403, pp. 117-133, 2021, Japan, 2021, doi: 10.1007/978-3-030-92163-710.
  2. Caio Fonseca, Dixon Vimalajeewa, Daniel P Martins, Deep Learning-based Voting System Model for Blind Bit Detection in Bacteria-based Molecular Communications Systems, Data Competition - ACM NanoCom, 2021 (involves MSc student supervision).
  3. Dixon Vimalajeewa, Eric Robson, Donagh P Berry, Chamil Kulatunga, Evaluation of Non-linearity in MIR Spectroscopic data for Compressed Learning , High Dimensional Data Mining (HDM) Workshop, IEEE Conference on Data Mining , New Orleans, USA, (ICDM 2017), pp. 545-553, 2017, doi: 10.1109/ICDMW.2017.77.

 Articles Under Review

  1. Dixon Vimalajeewa, U. Muller, B Vidakovic, A Multiscale Approach for Enhancing Weak Signal Detection, Submitted to IEEE Transactions in Signal Processing, 2025.
  2. M. Premathilaka, F. Rugeri, Dixon Vimalajeewa, A Noise Resilient Approach for Robust Hurst Exponent Estimation, Submitted to Journal Statistical Computing and Graphical Statistics, 2025.
  3. EA Onugha, A Banerjee, Dixon Vimalajeewa, KJ Nobleza, DT Nguyen, Dietary sodium and potassium patterns in adults with food insecurity in the context of hypertension risk, Journal of Hypertension, 2025 (involves PhD student supervision).

Articles Under Preparation

  1. Dixon Vimalajeewa, B. Vidakovic, F. Rugeri, Review on Recent Developments in Hurst Exponent Estimation Methods Using Wavelets (an invited article),
  2. V. Rathnayeka, Dixon Vimalajeewa, B. Vidakovic, Machine Learning-based Wavelet Thresholding (a corroboration with Texas A&M University).
  3. Dixon Vimalajeewa, B. Vidakovic, F. Ruggeri, Wavelets in Cryptography: Concepts and Applications.
  4. Dixon Vimalajeewa, E. Loyed, A. Keenen, B. Vidakovic, Leveraging Intrinsic Fluctuations in Neural Dynamics for Characterizing Blindfish Brain Evolution.