Year 2022
Date
25 March 2022 (Friday)
Time
2.00pm – 3.00pm
Platform
Microsoft Teams
Speaker
Prof. Dr. Leong Wah June
Department of Mathematics, Faculty of Sciences
Universiti Putra Malaysia
Organizer/
Centre for Mathematical Sciences (CMS)
Abstract: In this talk, we first introduce and motivate the application of sparse optimization in wide variety of fundamental applications. A general proximal alternating linearized (PAL) method for solving a broad class of sparse optimization problems involving L0-norm is proposed. Building on the Kurdy-Lojasiewicz property, a brief convergence analysis is established. We then demonstrate the applicability of the PAL method in solving some real-life problems such as those in sparse optimal control of large-scale interconnected networks, portfolio optimization and image restoration.
Date
24 June 2022 (Friday)
Time
3.00pm – 4.00pm
Platform
Microsoft Teams
Speaker
Prof. Isamiddin Rakhimov
Faculty of Computer and Mathematical Sciences
Universiti Teknologi MARA (UiTM)
Organizer/
Centre for Mathematical Sciences (CMS)
Abstract: The talk devoted to the classification problem of finite-dimensional algebras. We review the general strategy applied so far. Then the classification problem of Lie algebras and certain classes of algebras closely related to the class of Lie algebras will be focused on. These classes of algebras wee introduced by J.L. Loday in 1994. We show links between these classes of algebras and provide the latest results on their classification problem in low dimensions.
Date
29 September 2022 (Thursday)
Time
3.00pm – 4.00pm
Platform
Microsoft Teams
Speaker
Prof Madya Dr. Siti Nur Iqmal Binti Ibrahim
Department of Mathematics and Statistics, Faculty of Science
Universiti Putra Malaysia
Organizer/
Centre for Mathematical Sciences (CMS)
Abstract: The basis of options has been the vanilla options, and many have studied extensions of this option to construct other options, called the exotic options, to attract investors. One such option is the power options. With its higher leverage with every change in the underlying asset, power options are deemed to be more profitable than the vanilla options.
In this work, we study pricing models for European-style power call options and a modified version of this option. First, we present the fast Fourier transform (FFT) option pricing model for power call options, and also apply the Monte Carlo simulation (MCS) to compare the efficiency between these two pricing models. Then, we present a pricing formula for power call options that includes a barrier, which is called the power down-barrier options. We also show that there exists a power put-power call parity relationship, and a transformation between the underlying asset and the power contract. This study is within the Black0Scholes environment.
Finally, we run numerical experiments where we first compare the FFT and MCS for pricing the power call options, and then we compare the prices between power call options and power down-barrier options.
Date
28 July 2022 (Thursday)
Time
3.00pm – 4.00pm
Platform
Microsoft Teams
Speaker
Prof. Yiu Ka-Fai, Cedric
Department of Applied Mathematics
The Hong Kong Polytechnic University
Organizer/
Centre for Mathematical Sciences (CMS)
Abstract: For signal processing, multi-sensors are often deployed in order to enhance signal quality in various ways. In general, beamforming technique can be applied via an array of sensors to enhance the required signal via spatial filtering. Designing better beamformers for different scenarios is essential when the sensor distribution and the environment has changed. Optimization plays an important role in the improvement process. In this talk, we will discuss some advances in the optimal design of multi-dimensional broadband beamforming system. We review on various approaches and discuss some of the performance issues. Different optimization models will be considered. In addition to optimizing filter coefficients, we found that the geometric configuration of the array is important for the accuracy of the designs. In view of this, microphone locations can be optimized together with the filter coefficients and the overall problem is formulated as a non-convex optimization problem. When wireless sensors are operated, it is possible to design the beamformer in a distribution manner. Furthermore, it is possible to employ only a subset of the sensors to satisfy a specified performance requirement. In this way, the complexity of the beamformers can be greatly reduced. We will illustrate by several examples the proposed methods.
Date
26 August 2022 (Friday)
Time
2.30pm – 3.30pm
Platform
Microsoft Teams
Speaker
Dr. Mahendran Shitan
School of Mathematical and Computer Science
Heriot-Watt University, Malaysia
Organizer/
Centre for Mathematical Sciences (CMS)
Abstract: In this paper, we extend the idea of Gegenbauer process in the spatial domain by introducing a more general parameter and call this model as Spatial Gegenbauer Autoregressive (SGAR (1,1)) model. The spectral density and autocovariance functions of the model are introduced. The Yajima estimators of the Gegenbauer parameters, the log-periodogram regression estimators of the memory parameters and the Whittle's estimators of all parameters are discussed. The performance of these estimators is evaluated through a simulation study.
Date
31 October 2022 (Monday)
Time
3.00pm – 4.00pm
Platform
Microsoft Teams
Speaker
Ts. Dr. Hafizah Noor Bt Isa
Department of Physics, Kulliyyah of Science
International Islamic University Malaysia (IIUM)
Organizer/
Centre for Mathematical Sciences (CMS)
Abstract: Einstein's theory of general relativity predicted the existence of gravitational waves, but it was only in 2015 that they were finally detected by scientists working at LIGO laboratories. This discovery has been heralded as one of this century's greatest scientific breakthroughs and may have implications for our understanding not just dark matter or energy distributed throughout space-time- but time itself.
Date
29 April 2022 (Friday)
Time
2.00pm – 3.00pm
Platform
Microsoft Teams
Speaker
Associate Professor Dr. Chang Yun Fah
Actuarial Studies Program, School of Accounting and Finance, Faculty of Business and Law
Taylor's University
Organizer/
Centre for Mathematical Sciences (CMS)
Abstract: The functional relationship model (also called measurement error model or error in variables model) is a model extended from the classical linear regression where errors are assumed in both the X and Y variables which has been explored since the 19th century by Adcock (1878). Many further studies were then conducted to p-dimension of X and Y with single slope and uncorrelated variables. In this talk, we discuss a generalized version of Chang et al. (2010) works by allowing multicollinearity among the dimensions under study. The fundamental derivations on the model which includes multicollinearity to obtain the close form equations of the parameters and the properties of the estimated parameters will be discussed. At the end of the talk, simulation results and numerical example will also be presented.
Year 2021
Virtual Visit of External Examiner
Date: 6th & 7th December 2021
Platform: Microsoft Teams
Programme: Bachelor of Science (Honours) Applied Mathematics with Computing
External Examiner: Prof. Dr. Huang Huang-Nan (Tunghai University, Taiwan)
Programme: Bachelor of Science (Honours) Financial Mathematics
External Examiner: Prof. Dr. Yang Hailiang (The University of Hong Kong)
Date | 6 December 2021 (Monday) |
Time | 2.00pm – 3.00pm |
Platform | Microsoft Teams |
Speaker | Prof. Dr. Yang Hailiang Department of Statistics and Actuarial Science The University of Hong Kong Hong Kong |
Organizer/ Co-organizer | Department of Mathematical and Actuarial Sciences (DMAS) Centre for Mathematical Sciences (CMS) |
Abstract:
This paper studies deep learning approaches to find optimal reinsurance and dividend strategies for insurance companies. Due to the randomness of the financial ruin time to terminate the control processes, a Markov chain approximation-based iterative deep learning algorithm is developed to study this type of infinite-horizon optimal control problems. The optimal controls are approximated as deep neural networks in both cases of regular and singular types of dividend strategies. The framework of Markov chain approximation plays a key role in building the iterative equations and initialization of the algorithm. We implement this self-learning approach to approximate the optimal strategies and compare the learning results with existing analytical solutions. Satisfactory computation efficiency and accuracy are achieved as presented in numerical examples.
Virtual Visit of External Examiner for Bachelor of Science (Honours) Actuarial Science
Prof. Dr. Yam Sheung Chi Phillip
(The Chinese University of Hong Kong)
Date: 29th & 30th November 2021
Platform: Zoom
Research Talk by Invited Speaker from Universiti Teknologi PETRONAS
Date | 21 October 2021 (Thursday) |
Time | 10.00am – 11.00am |
Platform | Microsoft Teams |
Speaker | Assoc. Prof. Dr Hanita binti Daud Fundamental and Applied Sciences Department Universiti Teknologi PETRONAS Perak, Malaysia |
Organizer/ Co-organizer | Department of Mathematical and Actuarial Sciences (DMAS) Centre for Mathematical Sciences (CMS) |
Abstract:
Research Talk by Invited Speaker from Multimedia University Melaka, Malaysia
Date | 10 September 2021 (Friday) |
Time | 10.00am– 11.00am |
Platform | Microsoft Teams |
Speaker | Dr Nor Azlina Binti Ab Aziz Faculty of Engineering and Technology Multimedia University Melaka, Malaysia |
Organizer/ Co-organizer | Department of Mathematical and Actuarial Sciences (DMAS) Centre for Mathematical Sciences (CMS) |
Abstract:
Research Talk by Invited Speaker from Universiti Tun Hussein Onn Malaysia
Date | 20 August 2021 (Friday) |
Time | 10.00am– 11.00am |
Platform | Microsoft Teams |
Speaker | Dr Kek Sie Long PhD, CQRM Department of Mathematics and Statistics Universiti Tun Hussein Onn Malaysia Pagoh Campus, Muar, Johor, Malaysia |
Organizer/ Co-organizer | Department of Mathematical and Actuarial Sciences (DMAS) Centre for Mathematical Sciences (CMS) |
Abstract:
Research Talk by Invited Speaker from Universiti Sains Malaysia
Date | 13 August 2021 (Friday) |
Time | 10.00am– 11.00am |
Platform | Microsoft Teams |
Speaker | Dr Teh Wen Chean
School of Mathematical Sciences Universiti Sains Malaysia Pulau Pinang, Malaysia |
Organizer/ Co-organizer | Department of Mathematical and Actuarial Sciences (DMAS) Centre for Mathematical Sciences (CMS) |
Abstract:
Research Talk by Invited Speaker from Universiti Malaya
Date | 6 August 2021 (Friday) |
Time | 11.00am– 12.00pm |
Platform | Microsoft Teams |
Speaker | Assoc Prof Dr Ng Kok Haur
Institute of Mathematical Sciences Faculty of Science Universiti Malaya Kuala Lumpur, Malaysia |
Organizer/ Co-organizer | Department of Mathematical and Actuarial Sciences (DMAS) Centre for Mathematical Sciences (CMS) |
Abstract:
Research Talk by Invited Speaker from Universiti Malaysia Terrengganu (UMT)
Date | 30 July 2021 (Friday) |
Time | 11.00am– 12.00pm |
Platform | Microsoft Teams |
Speaker | Dr. Binyamin Yusoff
Mathematical Sciences Field Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terrenganu (UMT) Terrengganu, Malaysia |
Organizer/ Co-organizer | Department of Mathematical and Actuarial Sciences (DMAS) Centre for Mathematical Sciences (CMS) |
Abstract:
Research Talk by Invited Speaker from Universiti Teknologi MARA
Date | 16 July 2021 (Friday) |
Time | 11.00am– 12.00pm |
Platform | Microsoft Teams |
Speaker | Prof Dr. Yap Bee Wah
Institute for Big Data Analytics and Artificial Intelligence (IBDAAI) & Center of Statistical and Decision Science Studies Faculty of Computer and Mathematical Sciences (FSKM)
Universiti Teknologi MARA, Shah Alam, Selangor,
Malaysia |
Organizer/ Co-organizer | Department of Mathematical and Actuarial Sciences (DMAS) Centre for Mathematical Sciences (CMS) |
Abstract: