Сринивасан Сабаратинам
Факультет компьютерных наук
Должности
- Доцент — Факультет компьютерных наук, Департамент анализа данных и искусственного интеллекта
- Старший научный сотрудник — Факультет компьютерных наук, Научно-учебная лаборатория моделирования и управления сложными системами
Био
- · Начал работать в НИУ ВШЭ в 2021 году.
Образование
- 2016 · PhD
- 2010 · Магистратура: Университет Бхаратидасан, специальность «Физика», квалификация «Магистр наук»
Опыт работы
- · 2021-2024: : Постдок: Лаборатория моделирования и управления сложными системами, Национальный исследовательский университет (ВШЭ), Москва, Россия. Личная страница
- · 2019-2021: : Постдок: Группа BSICoS, I3A, Арагонский институт инженерных исследований, Университет Сарагосы, Испания
- · 2017-2019: : Постдок/руководитель проекта: Кафедра физики и астрофизики, Делийский университет, Нью-Дели, Индия
- · 2017-2018: : Технический ассистент и преподаватель: Преподавание программирования на языке 'C' для магистрантов в компьютерной лаборатории, кафедра физики и астрофизики, Делийский университет, Нью-Дели -110007. Эта возможность была предоставлена в рамках программы NPDF
- · 2016-2017: : Доцент кафедры физики: Преподавал инженерную физику и материаловедение на факультете науки и гуманитарных наук, Академия высшего образования Карпагам, Университет Карпагам, г. Коимбатур, Тамилнад, Индия (18.01.2017 - 30.04.2017)
- · 2013-2016: : Технический ассистент и преподаватель: Поддержка магистрантов в Школе физики, Университет Бхаратхидасан, в рамках программы UGC-BSR. Исследовательская стипендия в области науки для выдающихся студентов в форме старшего научного сотрудника/младшего научного сотрудника (29.03.2013 - 28.11.2016)
Идентификаторы исследователя
- ORCID:
0000-0003-2445-4800 - ResearcherID:
AAY-1493-2020 - Google Scholar: https://scholar.google.com/citations?user=ANWFuZIAAAAJ&hl=en
Публикации (27)
Self-feedback delay induces extreme events in the theoretical Brusselator system
2025 · ARTICLE · en
We present a study of the theoretical Brusselator model with time-delayed self-feedback, demonstrating its ability to induce extreme events when delays in reaction processes significantly influence subsequent dynamics, with and without diffusion. Stability analyses reveal the mechanisms driving this behavior with respect to the delay time. The occurrence of extreme events is validated using various numerical and statistical tools, including phase portraits, time series, probability distribution functions, return periods, and spatiotemporal evolution. A comprehensive two-parameter scan delineates the parameter regimes where the extreme events emerge, alongside the identification of transient chaos within specific regions of the parameter space. To confirm these numerical findings, we constructed an analog electronic circuit that emulates the model, providing experimental validation of the predicted dynamics.
Enhancing synchronization criteria for fractional-order chaotic neural networks via intermittent control: an extended dissipativity approach
2025 · ARTICLE · en
In this paper, a recurrent intermittent control (RIC) for the synchronization of fractional-order chaotic neural networks (FOCNNs) is proposed in view of the extended dissipativity-based approach. Successively, standard linear matrix inequalites (LMIs)-based extended dissipative criteria are derived through differential inclusions and inequality mechanisms. Several sufficient conditions are obtained to ensure the synchronization of FOCNNs. Furthermore, RIC is generated to solve the synchronization problem for the considered FOCNNs. Based on the piecewise Lyapunov functional, this paper derives a exponentially stable criterion in connection with linear matrix inequalities using the Matlab toolbox. Extended dissipativity can be employed to precisely define L2–L∞, H∞, passivity, and (Q, S, R)-ϑ dissipative performance. This is achieved by modifying the weighting matrices to achieve the desired performance level. The successful application of the stability criterion that was planned is demonstrated by the outcomes of the simulation.
Synergistic sunspot forecasting: a fusion of time series analysis and machine learning
2025 · ARTICLE · en
In this article, we conduct nonlinear time series analysis and utilise machine learning (ML) techniques for predicting and forecasting daily sunspot data sets. Additionally, we review available time series and ML techniques to provide a comprehensive overview. For time series analysis, the variations in the persistence of sunspot data sets were confirmed through Hurst exponent with various time lengths. Moreover, the fast Fourier transform was performed. For the ML approach, prediction and forecasting of sunspot data sets are performed with various simple ML algorithms. Recurrent neural networks (RNN), long–short time memories (LSTM) and gated recurrent unit (GRU) algorithms were used for the prediction. A discussion of the significant outcomes of the sunspot predictions made using the aforementioned algorithms is presented. With the use of these sunspot data sets, several statistical metrics, including R-squared, mean average error (MAE), etc., are examined. Further, the sunspot data forecast was done for more than eight solar cycles with the help of different forecasting algorithms (e.g., neural basis expansion analysis for time series (N-BEATS), neural hierarchical interpolation for the time series (NHITS), etc.). A summary of the sunspot predictions using several ML techniques in an effort to determine the most effective methodology is discussed.
Exploration and Analysis of Biodegradable Polymeric Films Reinforced with Surgical Face Masks Ash
2024 · ARTICLE · en
Disposable Surgical Face Masks (SFMs) are being used in the fght against Corona VIrus Disease-19 (COVID-19) during the pandemic. Since SFMs are made of polymers, their mass production causes severe environmental pollution. To reduce the SFM pollution, we have synthesized ash from the SFMs by incineration. A simple solution casting method is used to blend the surgical face mask ash (SFMA) with biodegradable hydroxypropyl methylcellulose polymer (HPMC). We have successfully adopted the Thermally Induced Phase Separation (TIPS) method to fabricate HPMC–SFMA flms using water as the solvent. The successful incorporation of SFM-derived ash into the HPMC matrix was confrmed by FT-IR and FESEM characterization techniques. The addition of SFMA to the HPMC matrix has implications for Young’s modulus, as well as their biodegradation behavior. The incorporation of SFMA in the HPMC matrix changes its stifness and elasticity, potentially afecting the flm’s mechanical performance. Furthermore, while HPMC is biodegradable, the inclusion of SFMA hinders its biodegradation rate and enhances the life span of HPMC. Hence, the HPMC–SFMA flms would be a promising candidate for agricultural mulching and this work leads to a conceptual basis for the production of novel materials in agricultural mulching.
Least fractional order memristor nonlinearity to exhibits chaos in a hidden hyperchaotic system
2024 · ARTICLE · en
In this article, we present least fractional nonlinearity for exhibiting chaos in a memristor-based hyper-chaotic multi-stable hidden system. When implementing memristor-based systems, distinct dimensions/order define the memristor nonlinearity. In this work, the memristor dimension has been changed fractionally to identify the lowest order of nonlinearity required to induce chaos in a proposed system. The two-parameter frequency scanning helps in understanding both oscillation and nonoscillation regimes. The system fractional nonlinearity strength will help in deeper understanding of mathematical modelling and control. In addition, multistability and hidden oscillations were thoroughly investigated in the proposed system. The current work combines analytical, numerical, and experimental methods to demonstrate the system dynamics
Extreme events in a damped Korteweg–de Vries (KdV) autonomous system: A comprehensive analysis
2024 · ARTICLE · en
This manuscript explores extreme events in a three-dimensional, damped Korteweg–de Vries (KdV) autonomous system that is derived from the jerk system with a modified basin. Through rigorous stability analysis, we identify the extreme events, confirmed using phase portraits, Poincaré return maps, time series, and probability distribution functions. The Dragon-king phenomenon is obtained and self-organised criticality is discussed. The regime of extreme events in a wide parameter range was obtained through two-parameter scanning. The analog circuit was constructed to mimicking dynamics of damped KdV equation and demonstrated in real-time hardware experiment as well as PSpice simulation. The experimental results show excellent agreement with the numerically obtained results. This study is the first comprehensive examination of extreme events in the damped KdV system, highlighting their nature and potential applications in chaos-based dynamical systems.
Dynamical instabilities cause extreme events in a theoretical Brusselator model
2024 · ARTICLE · en
In this manuscript, we report the rich dynamics of the theoretical Brusselator model, which is driven by a periodic external force. We observed and confirmed a variety of dynamical features with the most interesting extreme events behaviour in the proposed system. The dynamics of the system are characterised by the bifurcation diagram, Lyapunov exponent, phase portraits, and time series segments. The extreme events behaviour is characterised by the probability distribution function, instantaneous phase calculation, and Poincaré return map. Real-time hardware experiments were carried out using an analog electronic circuit, and the outcomes of the experimental observations were confirmed with the numerically obtained results. To the best of our knowledge, we believe that it is for the first time that the occurrence of extreme events has been reported using both the numerical simulation studies and the real-time analog electronic experimental observations on this forced Brusselator chemical model.
Investigation of transient extreme events in a mutually coupled star network of theoretical Brusselator system
2024 · ARTICLE · en
In this article, we present evidence of a distinct class of extreme events that occur during the transient chaotic state within network modeling using the Brusselator with a mutually coupled star network. We analyze the phenomenon of transient extreme events in the network by focusing on the lifetimes of chaotic states. These events are identified through the finite-time Lyapunov exponent and quantified using threshold and statistical methods, including the probability distribution function (PDF), generalized extreme value (GEV) distribution, and return period plots. We also evaluate the transitions of these extreme events by examining the average synchronization error and the system’s energy function. Our findings, validated across networks of various sizes, demonstrate consistent patterns and behaviors, contributing to a deeper understanding of transient extreme events in complex networks.
Event-triggered reachable set estimation for synchronization of Markovian jump complex-valued delayed neural networks under cyber-attacks
2024 в печати · ARTICLE · en
This paper focuses on the reachable set estimation for synchronizing of complex-valued neural networks (CVNNs) using an event-triggered (ET) approach and cyber-attacks. The system parameters are set up using Markovian switching rules. The proposed controller effectively saves the communication resources for the designed CVNNs. The main objective of this paper is to find an ellipsoid that can contain the state trajectory of the system as small as possible in the presence of control. From a physics point of view, the system can be likened to a dynamic system subjected to external perturbations, where the goal is to contain the trajectory of the system’s state within a bounded region, similar to confining particle motion in phase space. To achieve this objective, we propose a novel approach based on the reachable set technique, which allows us to obtain an ellipsoid that contains the state trajectory of the system while minimizing its size. Utilizing the standard Lyapunov–Krasovskii functional (LKF), integral inequality approaches, some sufficient stability formed in terms of linear matrix inequalities (LMIs) are derived for the synchronization of CVNNs under the ET scheme, which can be solved using MATLAB’s YALMIP toolbox. These conditions ensure that the states of the CVNNs converge to zero and that the synchronization error is bounded. Finally, numerical simulation results are provided to demonstrate the practicality and effectiveness of the proposed theoretical results.
Effect and importance of artificial extreme event in Indian Covid-19 vaccination data sets
2023 · ARTICLE · en
In this present manuscript, we investigate the Indian COVID-19 vaccination data sets from the beginning of the vaccination. We observed the artificial extreme events (AEE) in a vaccination process during the Teeka Utsav massive vaccination plan. We found some importance and effects of this event and subsequently we analyse the data set with the moving average. This study explores the reason behind the effects with respect to the second and third waves of COVID-19 in India. The importance of the extremely vaccinated days is discussed in this present manuscript.
Курсы (1)
-
Modern Concepts of Dynamical Neural Networks · 2 раза
2025/2026, 2024/2025 · Магистратура / Магистратура направление: 01.04.02 Прикладная математика и информатика / Маго-лего · Анг