Ali Asghar Heidari

Ali Asghar Heidari
National University of Singapore | NUS · Department of Computer Science

Exceptionally Talented Researcher funded by Iran's National Elites Foundation (INEF)
Best-quality Research and Development

About

217
Publications
209,373
Reads
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14,974
Citations
Citations since 2017
216 Research Items
14954 Citations
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201720182019202020212022202301,0002,0003,0004,0005,0006,000
201720182019202020212022202301,0002,0003,0004,0005,0006,000
Introduction
Ali Asghar Heidari has been an Exceptionally Talented Researcher with the School of the Computing National University of Singapore, the University of Tehran, and Iran's National Elites Foundation (INEF). He contributes to the best journals of IEEE Elsevier and has a deep vision of performance optimization. With more than 15766 citations and an H-index of 62, he has been ranked among the world's top computer scientists by guide2research, Stanford, and the top 1% reviewers in computer science.
Additional affiliations
December 2018 - February 2020
National University of Singapore
Position
  • Research internship
Description
  • NUS is 11th top university in the world (1th top university in Asia) based on QS World University Rankings 2019. https://news.nus.edu.sg/press-releases/QS-WUR-2019 https://www.comp.nus.edu.sg/
December 2017 - January 2020
Iran's National Elites Foundation (INEF)
Position
  • National Elite Researcher
Description
  • Iran's National Elites Foundation (INEF) recognizes and supports a few students from all universities in a competitive national level, and they recognize and support the development of Iranian scientists and professionals as exceptional talents in their discipline. Exceptionally talented members of the foundation include all those who expose exceptionally high intellectual capacity, academic aptitude, creative ability and artistic talents, especially contributors in promotion of global science.
September 2015 - September 2020
University of Tehran
Position
  • Exceptionally Talented Researcher
Education
December 2018 - February 2020
National University of Singapore
Field of study
  • Evolutionary Computation and Machine learning
September 2015 - September 2019
University of Tehran
Field of study
  • Information Systems
September 2012 - September 2015
University of Tehran
Field of study
  • Information Systems

Publications

Publications (217)
Article
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With the incremental use of e-mails as an essential and popular communication means over the Internet, there comes a serious threat that impacts the Internet and the society. This problem is known as spam. By receiving spam messages, Internet users are exposed to security issues, and minors are exposed to inappropriate contents. Moreover, spam mess...
Article
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With the increasing demand for security in many sectors, such as defense and health systems, developing secure Internet of Things (IoT) networks is a matter of great urgency. Looking at a potential solution for secure IoT systems, we inves- tigate the physical layer security of cooperative non-orthogonal multiple access (NOMA) systems. After decodi...
Article
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Analyzing surveillance videos is mandatory for the public and industrial security. Overwhelming growth in computer vision fields has been made to automate the surveillance system in terms of human activity recognition such as behavior analysis, Violence Detection (VD), etc. However, it is challenging to detect and analyze the violent scenes intelli...
Article
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In the Industry 4.0 era, the visualization and real-time automatic monitoring of smart cities supported by the Internet of Things is becoming increasingly important. The use of filtering algorithms in smart city monitoring is a feasible method for this purpose. However, maintaining fast and accurate monitoring in complex surveillance environments w...
Article
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Introduction: Feature selection is a typical NP-hard problem. The main methods include filter, wrapper-based, and embedded methods. Because of its characteristics, the wrapper method must include a swarm intelligence algorithm, and its performance in feature selection is closely related to the algorithm's quality. Therefore, it is essential to cho...
Article
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Lupus nephritis (LN) is one of the most common and serious clinical manifestations of systemic lupus erythematosus (SLE), which causes serious damage to the kidneys of patients. To effectively assist the pathological diagnosis of LN, many researchers utilize a scheme combining multi-threshold image segmentation (MIS) with metaheuristic algorithms (...
Article
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Harris Hawks optimization (HHO) is a swarm optimization approach capable of handling a broad range of optimization problems. HHO, on the other hand, is commonly plagued by inadequate exploitation and a sluggish rate of convergence for certain numerical optimization. This study combines the fireworks algorithm's explosion search mechanism into HHO a...
Article
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Aiming at the poor robustness and adaptability of traditional control methods for different situations, the deep deterministic policy gradient (DDPG) algorithm is improved by designing a hybrid function that includes different rewards superimposed on each other. In addition, the experience replay mechanism of DDPG is also improved by combining prio...
Article
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Unlabelled: The slime mould algorithm (SMA) is a new meta-heuristic algorithm recently proposed. The algorithm is inspired by the foraging behavior of polycephalus slime moulds. It simulates the behavior and morphological changes of slime moulds during foraging through adaptive weights. Although the original SMA's performance is better than most s...
Article
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Introduction Atopic dermatitis (AD) is an allergic disease with extreme itching that bothers patients. However, diagnosing AD depends on clinicians’ subjective judgment, which may be missed or misdiagnosed sometimes. Methods This paper establishes a medical prediction model for the first time on the basis of the enhanced particle swarm optimizatio...
Article
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If found and treated early, fast-growing skin cancers can dramatically prolong patients’ lives. Dermoscopy is a convenient and reliable tool during the fore-period detection stage of skin cancer, so the efficient processing of digital images of dermoscopy is particularly critical to improving the level of a skin cancer diagnosis. Notably, image seg...
Article
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Coronavirus Disease 2019 (COVID-19) is the most severe epidemic that is prevalent all over the world. How quickly and accurately identifying COVID-19 is of great significance to controlling the spread speed of the epidemic. Moreover, it is essential to accurately and rapidly identify COVID-19 lesions by analyzing Chest X-ray images. As we all know,...
Article
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Harris hawks optimization (HHO) has been accepted as one of the well-established swarm-based methods in the community of optimization and machine learning that primarily works based on multiple dynamic features and various exploratory and exploitative traits. Compared with other optimization algorithms, it has been observed that HHO can obtain high...
Article
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Computerized tomography (CT) is of great significance for the localization and diagnosis of liver cancer. Many scholars have recently applied deep learning methods to segment CT images of liver and liver tumors. Unlike natural images, medical image segmentation is usually more challenging due to its nature. Aiming at the problem of blurry boundarie...
Data
A complete MATLAB code of the ELSHADE-INR is attached to extract the parameters of the TD PV model. The developed ELSHADE-INR exhibits the best RMSE value, up to date, for the parameter optimization problem and can be used to extract any type of PV model. The contributions have been performed for both methodology (algorithm) and the objective funct...
Article
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Introduction Pulmonary embolism (PE) is a common thrombotic disease and potentially deadly cardiovascular disorder. The ratio of clinical misdiagnosis and missed diagnosis of PE is very large because patients with PE are asymptomatic or non-specific. Methods Using the clinical data from the First Affiliated Hospital of Wenzhou Medical University (...
Article
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The slime optimization algorithm (SMA) has recently received much attention from researchers because of its simple structure, excellent optimization capabilities, and acceptable convergence in dealing with various types of complex real-world problems. The increase in research enthusiasm has led to the emergence of many different advanced versions o...
Article
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The Salp Swarm Algorithm (SSA) is a recently proposed swarm intelligence algorithm inspired by salps, a marine creature similar to jellyfish. Despite its simple structure and solid exploratory ability, SSA suffers from low convergence accuracy and slow convergence speed when dealing with some complex problems. Therefore, this paper proposes an impr...
Article
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Introduction Pulmonary embolism (PE) is a cardiopulmonary condition that can be fatal. PE can lead to sudden cardiovascular collapse and is potentially life-threatening, necessitating risk classification to modify therapy following the diagnosis of PE. We collected clinical characteristics, routine blood data, and arterial blood gas analysis data f...
Article
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Multi-Source Domain Adaptation (MSDA) techniques have attracted widespread attention due to their availability to transfer knowledge from multiple source domains to the unlabeled target domain. Optimal transport (OT) has recently been utilized to measure the distance between distributions in virtual of its robustness. This paper proposes a novel OT...
Article
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Moth-flame optimization is a typical meta-heuristic algorithm, but it has the shortcomings of low-optimization accuracy and a high risk of falling into local optima. Therefore, this paper proposes an enhanced moth-flame optimization algorithm named HMCMMFO, which combines the mechanisms of hybrid mutation and chemotaxis motion, where the hybrid-mut...
Article
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Automated diagnostic techniques based on computed tomography (CT) scans of the chest for the coronavirus disease (COVID-19) help physicians detect suspected cases rapidly and precisely, which is critical in providing timely medical treatment and preventing the spread of epidemic outbreaks. Existing capsule networks have played a significant role in...
Article
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The sine cosine algorithm (SCA) is a metaheuristic algorithm proposed in recent years that does not resort to nature-related metaphors but explores and exploits the search space with the help of two simple mathematical functions of sine and cosine. SCA has fewer parameters and a simple structure and is widely used in various fields. However, it ten...
Article
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Melanoma is a malignant tumor formed by the cancerous transformation of melanocytes, and its medical images contain much information. However, the percentage of the critical information in the image is small, and the noise is non-uniformly distributed. We propose a new multi-threshold image segmentation model based on the two-dimensional histogram...
Article
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The slime mould algorithm (SMA) has become a classical algorithm applied in many fields since it was presented. Nevertheless, when faced with complex tasks, the algorithm converges slowly and tends to fall into the local optimum. So, there is still room for improvement in the performance of SMA. This work proposes a novel SMA variant (SDSMA), combi...
Article
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As science and technology advance, more engineering-type problems emerge. Technology development has likewise led to an increase in the complexity of optimization problems, and the need for new optimization techniques has increased. The swarm intelligence optimization algorithm is popular among researchers as a flexible, gradient-independent optimi...
Article
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The determination of photovoltaic parameters is of great importance for the reliability of solar system operation, continuity of the load power consumption, and control management of the energy source. Therefore, this study proposes an advanced backtracking search optimization algorithm (BSA) equipped with teaching and learning-based optimization (...
Article
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With the recent emphasis on new energy sources, solar photovoltaic cells have received widespread attention from scholars as a highly efficient and clean new energy source. Researchers model solar photovoltaic cells and analyze the values of various unknown parameters to improve their efficiency in converting solar energy into electric energy. To e...
Article
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Accurately identifying viruses from bacteria determine the therapy and outcome of patients suffering from pneumonia. This study focuses on exploring the capability of machine learning techniques in detecting the well-known influenza virus pneumonia from bacterial pneumonia based on the key variable quantity of blood tests and computer tomography (C...
Article
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The sine cosine algorithm (SCA) is a well-known meta-heuristic optimization algorithm. SCA has received much attention in various optimization fields due to its simple structure and excellent optimization capabilities. However, the dimension of objective function also increases with the increasing complexity of optimization tasks. This makes the or...
Article
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COVID-19 is pervasive and threatens the safety of people around the world. Therefore, now, a method is needed to diagnose COVID-19 accurately. The identification of COVID-19 by X-ray images is a common method. The target area is extracted from the X-ray images by image segmentation to improve classification efficiency and help doctors make a diagno...
Article
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Due to their insufficient generalization ability, iris segmentation algorithms based on deep learning cannot accurately segment iris images without corresponding ground truth (GT) data. Moreover, prior to recognition, the segmented image requires normalization to reduce the influence of pupil deformation. However, normalization of nonconnected iris...
Article
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The fine particulate matter (PM2.5) concentration has been a vital source of info and an essential indicator for measuring and studying the concentration of other air pollutants. It is crucial to realize more accurate predictions of PM2.5 and establish a high-accuracy PM2.5 prediction model due to their social impacts and cross-field applications i...
Article
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Background Moth-flame optimization will meet the premature and stagnation phenomenon when encountering difficult optimization tasks. Objective To overcome the above shortcomings, this paper presented a quasi-reflection moth-flame optimization algorithm with refraction learning called QRMFO to strengthen the property of ordinary MFO and apply it in...
Article
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Harris hawks optimization has been a popular swarm intelligence algorithm in recent years. In order to improve the local exploitation ability of the algorithm and improve the problem of slow convergence speed, an enhanced Harris hawks optimization algorithm based on Laplace crossover and random replacement strategy is proposed. This variant uses tw...
Article
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A large volume of high-dimensional genetic data has been produced in modern medicine and biology fields. Data-driven decision-making is particularly crucial to clinical practice and relevant procedures. However, high-dimensional data in these fields increase the processing complexity and scale. Identifying representative genes and reducing the data...
Article
Sine Cosine Algorithm (SCA), as a recently viral population-based meta-heuristic, which is in the extensive application for a variety of optimization cases. Regardless of the concerns on its novelty, SCA updates the population based on a simple updating rule with a basic structure and few parameters. However, it is considered that SCA remains the w...
Article
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The whale optimizer is a popular metaheuristic algorithm, which has the problems of weak global exploration, easy falling into local optimum, and low optimization accuracy when searching for the optimal solution. To solve these problems, this paper proposes an enhanced whale optimization algorithm based on the worst individual disturbance (WD) and...
Article
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The Hunger Games Search (HGS) algorithm is a recently proposed population-based optimization algorithm that mimics a common phenomenon of animals searching for food due to hunger stimuli and has a simple and easy-to-understand structure. However, the original HGS still suffers from shortcomings, such as low population diversity and the tendency to...
Article
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Photovoltaic (PV) technology can convert solar energy to electric power, which is an essential tool for future years. Subsequently, several static solar PV models have been designed to simulate the current in a PV cell. However, the modeling process of PV systems requires extracting the unknown parameters of these cells, which can be modeled as an...
Article
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Measurement data based on current and voltage of photovoltaic (PV) systems and the establishment of more accurate and stable solar system models are of typical significance for the design, control, evaluation and optimization of PV systems. Accurate and stable parameter evaluation for PV systems needs to be based on more efficient optimization tech...
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As a recent meta-heuristic algorithm, the uniqueness of the grasshopper optimization algorithm (GOA) is to imitate the biological features of grasshoppers for single-objective optimization cases. Despite its advanced optimization ability, the basic GOA has a set of shortcomings that pose challenges in numerous practical scenarios. The GOA core limi...
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This paper focuses on the study of Coronavirus Disease 2019 (COVID-19) X-ray image segmentation technology. We present a new multilevel image segmentation method based on the swarm intelligence algorithm (SIA) to enhance the image segmentation of COVID-19 X-rays. This paper first introduces an improved ant colony optimization algorithm, and later d...
Article
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Intradialytic hypotension (IDH) is a serious complication of hemodialysis (HD), with an incidence of more than 20%. IDH induces ischemic organ damage and even reduces the ultrafiltration and duration of HD sessions. Frequent attacks of IDH are a risk factor for death in HD patients. Malnutrition is common in HD patients and is also associated with...
Article
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In this paper, an efficient sine cosine differential gradient-based optimization method is proposed for identifying unknown parameters of photovoltaic models. In the simulation, parameter identification is formulated as an objective function to be minimized based on the error between the estimated and experimental data. Based on the original gradie...
Article
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The shuffled frog leaping algorithm is a new optimization algorithm proposed to solve the combinatorial optimization problem, which effectively combines the memetic algorithm based on a memetic algorithm and the particle swarm algorithm based on population behavior. The algorithm is widely used because it is easy to implement and requires few param...
Article
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The ant colony optimization algorithm is a classical swarm intelligence algorithm, but it cannot be used for continuous class optimization problems. A continuous ant colony optimization algorithm (ACOR) is proposed to overcome this difficulty. Still, some problems exist, such as quickly falling into local optimum, slow convergence speed, and low co...
Article
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The inherent multimodal and nonlinear characteristics of solar photovoltaic (PV) systems make it challenging to accurately extract PV parameters. Therefore, this study proposes an efficient and accurate optimization technique, improved Hunger Games Search, to identify unknown parameters in PV systems named IHGS. IHGS makes full use of the populatio...
Article
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COVID-19 is currently raging worldwide, with more patients being diagnosed every day. It usually is diagnosed by examining pathological photographs of the patient's lungs. There is a lot of detailed and essential information on chest radiographs, but manual processing is not as efficient or accurate. As a result, how efficiently analyzing and proce...
Article
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Feature selection is a crucial preprocessing step in the sphere of machine learning and data mining, devoted to reducing the data dimensionality to improve the performance of learning models. In this paper, a vigorous metaheuristic named hunger games search (HGS) is integrated with a multi-strategy (MS) framework, including chaos theory, greedy sel...
Article
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Swarm salp algorithm is a swarm intelligence optimization algorithm enlightened by the movement and foraging behaviors of the salp population. The salp swarm algorithm (SSA) has a simple structure and fast processing speed and can gain significant results on objective functions with fewer local optima. However, it has poor exploration ability and i...
Article
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Tomato production is often threatened by the bites of several pests (mainly whiteflies and cotton bollworms). Pests exist throughout the tomato growing season, and it is necessary to detect and prevent these stubborn pests in time to reduce the economic losses caused by pests. Deep learning has been widely used to identify plant diseases and insect...
Article
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Systemic lupus erythematosus is a chronic autoimmune disease that affects kidney in most patients. Lupus nephritis (LN) is divided into six categories by the International Society of Nephrology/Renal Pathology Society (ISN/RPS). The purpose of this research is to build a framework for discriminating between ISN/RPS pure class V(MLN) and classes III...
Article
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Intradialytic hypotension (IDH) is the most common acute complication in hemodialysis (HD) sessions and is associated with increased morbidity and mortality in HD patients. To prevent the episode of IDH, it is critical to predict its occurrence. Chronic kidney disease-mineral and bone disorders (CKD-MBD) induce cardiac and vascular calcification, w...
Article
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Peripheral hypertension (PH) is a rare and fatal condition that leads to right heart failure and death. The pathophysiology of PH and potential therapeutic approaches are yet unknown. The development of PH animal models and their proper evaluation are critical to PH research. This work presents an effective analysis technology for PH from arterial...
Article
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The heap-based optimizer (HBO) is an optimization method proposed in recent years that may face local stagnation problems and show slow convergence speed due to the lack of detailed analysis of optimal solutions and a comprehensive search. Therefore, to mitigate these drawbacks and strengthen the performance of the algorithm in the field of medical...
Article
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In recent years, a range of novel and pseudonovel optimization algorithms has been proposed for solving engineering problems. Swarm intelligence optimization algorithms (SIAs) have become popular methods, and the whale optimization algorithm (WOA) is one of the highly discussed SIAs. However, regardless of novelty concerns about this method, the ba...
Article
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In this paper, an adaptive Harris hawk optimization with persistent trigonometric (sine–cosine)-differences (ADHHO) is proposed for parameter identification of Photovoltaic (PV) systems. In the optimized version of HHO, we innovatively propose the persistent-trigonometric-differences mechanism for improving the global search capability of HHO; more...
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Grey wolf optimizer (GWO) is a widespread metaphor-based algorithm based on the enhanced variants of velocity-free particle swarm optimizer with proven defects and shortcomings in performance. Regardless of the proven defect and lack of novelty in this algorithm, the GWO has a simple algorithm and it may face considerable unbalanced exploration and...