The Electronic and Telecommunication Engineering Department of the University of Moratuwa, in collaboration with the UBC Quantum Club, IEEE Sri Lanka Section, and Skill Surf, organized a one-day workshop on “Introduction to Quantum Computing” on January 21, 2023. The workshop aimed to introduce participants to the basics of quantum computing, its applications, and its future potential. The workshop featured key resource personnel who are experts in the field of quantum computing. Dr. Harini Hapuarachchi from RMIT University, Australia, Mr. Kithmin Wickremasinghe from the University of British Colombia, Canada, Mr. Ravi Tharaka from Monash University, Australia, and Theshani Nuradha from Cornell University, USA, were the keynote speakers for the workshop.
The one-day workshop attracted a significant number of participants, including students, academics, and industry professionals. The workshop offered a comprehensive introduction to the basics of quantum computing, including quantum mechanics, qubits, quantum gates, quantum circuits, and quantum algorithms. Participants also had the opportunity to learn about quantum computing applications in various fields, including cryptography, machine learning, and optimization. The workshop included interactive sessions, demonstrations, and hands-on exercises to provide a practical understanding of the concepts covered in the lectures. The resource personnel also provided valuable insights into the future of quantum computing and the opportunities it presents.
The workshop was a great success, with participants expressing their satisfaction with the content and delivery of the program. The participants also had the opportunity to network and exchange ideas with the experts in the field. The organizers of the workshop thanked the resource personnel, participants, and sponsors for making the event a success. They also encouraged participants to continue to explore the world of quantum computing and stay updated with the latest developments in the field.
Overall, the “Introduction to Quantum Computing” workshop was a great initiative by the Electronic and Telecommunication Engineering Department of the University of Moratuwa, together with its partners. The department has a thrust area in quantum computing. The workshop was an excellent opportunity for participants to expand their knowledge and skills in quantum computing and explore the exciting potential of this emerging field.Read More
SPARK project aims to drive projects that solve crucial problems that mankind faces such as climate change, food scarcity, and inequality in education though the application of engineering principles. All these are important aspects of the 17 Sustainable Development Goals (https://sdgs.un.org/goals). Approximately 35 student teams worked on developing solutions to problems that address one or more such goals. Ten groups were able to propose fully-developed ideas and make prototypes. This was possible after a long-term training provided by SAPRK with the involvement of foreign trainers.
As the culmination of this year-long process, the ten groups pitched their projects to an eminent panel of judges comprising Mr. Heminda Jayaweera, Mr. Fayaz Hudah, Mr. Chalinda Abeykon and Mr. Josh Robsen. This pitching session took place on July 24, 2022 at the Department of Electronic and Telecommunication Engineering in a vibrant setting with many students and staff members watching and deliberating about the possible impact of the projects.Read More
Nima Wickramasinghe from the Department of Electronic and Telecommunication Engineering (ENTC), together with his mentor Mohamed Athif from the Department of Biomedical Engineering, Boston University (previously an undergraduate at ENTC) have written a research paper, titled “Multi-label Classification of Reduced-lead ECGs using an Interpretable Deep Convolutional Neural Network” which has been accepted to be published in the journal Physiological Measurement as a special issue paper.
In their work, they propose a novel method to identify the presence of 26 cardiac abnormalities in an ECG recording with reduced leads. Even though most of the previous work relies on 12-lead ECGs, classification using reduced leads remained unexplored. In their research, they trained a deep convolutional neural network to classify the ECG recordings and showed that the reduced-lead model performs comparably to the 12-lead model. In addition to accurately classifying the cardiac abnormalities, they have used SHAP (shapley additive explanations: a game-theoretic approach used to explain the output of any machine learning model) to interpret the deep learning model. The authors identified that the model learns almost the same diagnostic criteria used by cardiologists to classify cardiac abnormalities. By analyzing the model through SHAP, they were able to detect why the model underperforms in some of the classes, which was mainly due to the lack of discriminating features in reduced leads, labeling inconsistencies in the dataset, and low number of samples.
Physiological Measurement is a journal that covers the quantitative measurement and visualization of physiological structure and function in clinical research and practice, with an emphasis on the development of new methods of measurement and their validation. The Sustainable Education Foundation facilitated the collaboration between the 2 authors.
DOI Link to the paper: https://doi.org/10.1088/1361-6579/ac73d5Read More
Mr. Pasan Dissanayake and Dr. Prathapasinghe Dharmawansa of ENTC have Published Two Research Papers in the Prestigious Journal IEEE Transactions on Information Theory
Two research papers written by Mr. Pasan Dissanayake and Dr. Prathapasinghe Dharmawansa of ENTC have been published in the prestigious journal IEEE Transactions on Information Theory. IEEE Transactions on Information Theory is the world’s No. 1 journal in the areas of Information and Communication theory research. This truly exceptional achievement will make the research history of ENTC. This extraordinary academic achievement will be a guiding spirit for the current and future researchers in the entire university system of Sri Lanka. Moreover, it will help place ENTC among the top researchers in information and communication theory in the world. The details of the two papers are as follows.
1. Distribution of the Scaled Condition Number of Single-spiked Complex Wishart Matrices
This paper statistically characterizes the scaled condition number (SCN) of single-spiked complex Wishart matrices by deriving its density function. The statistical characteristics of the SCN and its variants have been instrumental in understanding many physical phenomena across a heterogeneous field of sciences. While numerical analysts and statistical physicists are interested in the behavior of the SCN for white Wishart matrices, the case corresponding to correlated Wishart matrices are of paramount importance in wireless communications and statistics. In particular, the SCN has been used as a performance metric in certain wireless signal processing applications involving multiple-input multiple-output (MIMO) systems, in which the antenna correlation gives rise to the correlated Wishart matrix. Recently, the SCN has been proposed as one of the test statistics for blind spectrum sensing in cognitive radio (CR) systems. The key concept behind CR is to opportunistically utilize the underutilized spectrum in view of improving the spectral efficiency of modern wireless networks. Against this backdrop, this paper leverages powerful random matrix theoretic techniques and the novel density of the SCN to statistically characterize the receiver operating characteristics (i.e., ROC) of the aforementioned detector. Since the modern wireless architectures facilitate the use of large antenna/sensor arrays with comparable observational sample acquisition, the analysis has been extended to the asymptotic regime in which the number of antennas of the detector and the samples diverge at the same rate so that their ratio remains constant. It turns out that, in this asymptotic regime, the statistical power of the SCN based detector can be approximated by the most celebrated Tracy-Widom distribution corresponding to the complex matrices. Moreover, numerical results have revealed that those asymptotic results compare favourably with their not so large dimensional counterparts.
2. The Eigenvectors of Single-spiked Complex Wishart Matrices: Finite and Asymptotic Analyses
This paper investigates the finite dimensional distributions of the eigenvectors corresponding to the extreme eigenvalues (i.e., the minimum and the maximum) of single-spiked complex Wishart matrices. These spikes arise in various practical settings in different scientific disciplines. For instance, they correspond to the first few dominant factors in factor models arising in financial economics, the number of clusters in gene expression data, and the number of signals in detection and estimation theory. In particular, the focus is on the distributions of the squared modulus of the eigen-projectors (i.e., projection of the spiked-vector onto the leading and least eigenvectors) of single-spiked Wishart matrices. This metric is commonly used to infer information about the latent spiked-vector using the eigenvectors of the sample covariance matrix. A concrete example in this respect is the principal component analysis (PCA) in which the eigenvectors of the unknown population covariance matrix is approximated by the eigenvectors of the sample covariance matrix. This metric has further been used in the covariance estimation based on the optimal shrinkage of the eigenvalues of the sample covariance matrix in the high dimensional setting when the unobserved population covariance matrix assumes the spiked structure. This paper leverages the powerful contour integral representation of unitary integrals and orthogonal polynomial techniques to derive closed-form expressions for the densities of the above metrics. A somewhat surprising stochastic convergence result pertaining to the above metrics has also been established. Finally, the same analytical framework has been extended to derive the corresponding destines for real and singular Wishart scenarios; however, with closed-form solutions limited to a few special configurations only.