Ansari's Homepage

Mohsen Ansari, Ph.D.

Assistant Professor

Director of Cyber-Physical Systems Labratory (CPSLab)

Sharif University of Technology, Tehran, Iran.

Office: 624 (CE Building)

Email: ansari [at] sharif.edu
Tel: +9821 6616 5789
Fax: +9821 6616 9256

Short CV Education Positions Awards Laboratory Professional Services Courses

Mohsen Ansari is currently an assistant professor of computer engineering at Sharif University of Technology, Tehran, Iran. He received his Ph.D. degree in computer engineering from Sharif University of Technology, Tehran, Iran, in 2021. He was a visiting researcher in the Chair for Embedded Systems (CES), Karlsruhe Institute of Technology (KIT), Germany, from 2019 to 2021. He is currently the director of Cyber-Physical Systems Laboratory (CPSLab) at Sharif University of Technology. He was the technical program committee (TPC) member of ASP-DAC (2022 and 2023). Dr. Ansari is serving as an associate editor of the IEEE Embedded Systems Letter (ESL). His research interests include embedded machine learning, low-power design, real-time systems, cyber-physical systems, and hybrid systems design.

Research Interests

Cyber-Physical Systems Design
Embedded Machine Learning
Edge, Fog, and Cloud Computing
Machine Learning for CPSs and Sensor Information Processing
Thermal and Low Power Design of CPSs
Energy-Efficient, Fault-Tolerant, and Secure Computing

Page at: Google Scholar, ResearchGate, Linkedin

Education

Ph.D. in Computer Engineering, Department of Computer Science and Engineering, Sharif University of Technology, Tehran, Iran, Sep. 2016- Sep. 2021.
M.Sc. in Computer Engineering, Department of Computer Science and Engineering, Sharif University of Technology, Tehran, Iran, Sep. 2014- Aug. 2016.
B.Sc. in Computer Engineering, Department of Engineering, Shahed University, Tehran, Iran, Sep. 2010- Aug. 2014.

Assistant Professor, Department of Computer Science and Engineering, Sharif University of Technology, Tehran, Iran, Apr. 2022- Present.
Member of the board, Cyber-Physical Systems Society of Iran, Dec. 2021- Present.
Postdoctoral Fellow, Department of Computer Science and Engineering, Sharif University of Technology, Tehran, Iran, Sep. 2021-Apr. 2022.
Visiting Researcher, The Chair for Embedded Systems, Karlsruhe Institute of Technology, Karlsruhe, Germany, Oct. 2019- Apr. 2021.
Group Leader, Embedded Systems Research Laboratory (ESR-LAB), Department of Computer Science and Engineering, Sharif University of Technology, Tehran, Iran, Sep. 2016- Apr. 2022.

Open positions

There is no open position.

Awards

Recieved the Dr. Kazemi Ashtiani award from national elites fundation of Iran, 2024.
Recieved the outstanding young researcher award from Sharif University of Technology, 2023.
Recieved the Dr. Shahriari award (Faculty position) from national elites fundation of Iran, 2022.
Recieved the Dr. Chamran award (Postdoctoral position) from national elites fundation of Iran, 2021.
Elected as a national talent, 2016-2022.
Elected as the premier teacher assistant at Sharif University of Technology, 2017.
Ranked 3rd out of 1000 graduated students at Sharif University of Technology, 2016.
Ranked 2nd among 42 graduated students in computer architecture, Department of Computer Science and Engineering, Sharif University of Technology, 2016.
Admitted as an Exceptional Talent at Sharif University of Technology for M.Sc programs, 2014.
Ranked 1st out of 160 graduated students in department of engineering at Shahed University, 2014.

Welcome to CPSLab

Dear Visitor:

Welcome to our laboratory group's website. Our researches focus on Cyber-Physical Systems Design, Real-Time Embedded Systems Design, Low Power Design, Dependability Evaluation and Reliability Assessment, and Internet of Things (IoT). Cyber-Physical Systems Laboratory (CPSLab) is located in the Department of Computer Engineering , Sharif University of Technology.

News

// Newest // 2024/Mar.: New journal paper has been accepted at IEEE Access.

2024:

2024/Mar.: New journal paper has been accepted at IEEE Access.
2024/Feb.: Congratulations to Moein Esnaashari for successfully defending his thesis and graduating from masters education.
2024/Feb.: Congratulations to Abolfazl Younesi for successfully defending his thesis and graduating from masters education.
2024/Feb.: Congratulations to Hossein Hosseini Kasnavieh for successfully defending his thesis and graduating from masters education.

2023:

2023/June: New journal paper has been accepted at IEEE Transactions on Sustainable Computing.
2023/April: New top-tier conference paper has been accepted at RTAS 2023.
2023/Jan.: New journal paper has been accepted at IEEE Internet of Things Journal.

2022:

2022/Sep.: Congratulations to Seyyed Roozbeh Siyadatzadeh for successfully defending his M.Sc. thesis.
2022/July: New journal paper has been accepted at IEEE Transactions on Parallel and Distributed Systems.

Publications

Journal Papers

Abolfazl Younesi, Mohsen Ansari, MohammadAmin Fazli, Alireza Ejlali, Muhammad Shafique, Jörg Henkel, "A Comprehensive Survey of Convolutions in Deep Learning: Applications, Challenges, and Future Trends," IEEE Access, vol. 12, pp. 41180-41218, 2024.
Mohsen Ansari, Sepideh Safari, Nezam Rohbani, Alireza Ejlali, Bashir M Al-Hashimi, "Power-Efficient and Aging-Aware Primary/Backup Technique for Heterogeneous Embedded Systems," IEEE Transactions on Sustainable Computing, vol. 8, no. 4, pp. 715-726, Oct.-Dec. 2023.
Roozbeh Siyadatzadeh, Fatemeh Mehrafrooz, Mohsen Ansari, Bardia Safaei, Muhammad Shafique, Jörg Henkel, and Alireza Ejlali, "ReLIEF: A Reinforcement Learning-Based Real-Time Task Assignment Strategy in Emerging Fault-Tolerant Fog Computing," IEEE Internet of Things Journal, vol. 10, no. 12, pp. 10752-10763, 15 June, 2023.
Sina Yari-Karin, Roozbeh Siadatzadeh, Mohsen Ansari, and Alireza Ejlali, "Passive Primary/Backup-based Scheduling for Simultaneous Power and Reliability Management on Heterogeneous Embedded Systems," IEEE Transactions on Sustainable Computing, vol. 8, no. 1, pp. 82-93, 1 Jan.-March 2023.
Mohsen Ansari, Sepideh Safari, Heba Khdr, Pourya Gohari-Nazari, Jörg Henkel, Alireza Ejlali, and Shaahin Hessabi, "Power-Aware Checkpointing for Multicore Embedded Systems," IEEE Transactions on Parallel and Distributed Systems, vol. 33, no. 12, pp. 4410-4424, 1 Dec. 2022.
Mohsen Ansari, Sepideh Safari, Sina Yari-Karin, Pourya Gohari-Nazari, Heba Khdr, Muhammad Shafique, Jörg Henkel, and Alireza Ejlali, "Thermal-Aware Standby-Sparing Technique on Hetereogeneous Real-Time Embedded Systems," IEEE Transactions on Emerging Topics in Computing, vol. 10, no. 4, pp. 1883-1897, 1 Oct.-Dec. 2022.
Sepideh Safari, Mohsen Ansari, Heba Khdr, Pourya Gohari-Nazari,Sina Yari-Karin, Amir Yeganeh-Khaksar, Shaahin Hessabi, Alireza Ejlali, and Jörg Henkel, "A Survey of Fault-Tolerance Techniques for Embedded Systems from the Perspective of Power, Energy, and Thermal Issues," IEEE Access, vol. 10, pp. 12229-12251, 2022.
Sepideh Safari, Heba Khdr, Pourya Gohari-Nazari,Mohsen Ansari, Shaahin Hessabi, and Jörg Henkel, "TherMa-MiCs: Thermal-Aware Scheduling for Fault-Tolerant Mixed-Criticality Systems," IEEE Transactions on Parallel and Distributed Systems, vol. 33, no. 7, pp. 1678-1694, July 2022.
Mohsen Ansari, Sina Yari-Karin, Sepideh Safari, and Alireza Ejlal, "Power Management to Meet Thermal Safe Power in Fault-Tolerant Embedded Systems" TechRxiv, 2021, doi:10.36227/techrxiv.14703192.v1.
Amir Yeganeh-Khaksar, Mohsen Ansari, Sepideh Safari, Sina Yari-Karin, and Alireza Ejlali, "Ring-DVFS: Reliability-Aware Reinforcement Learning-Based DVFS for Real-Time Embedded Systems," IEEE Embedded Systems Letters, vol. 13, no. 3, pp. 146-149, September 2021.
Amir Yeganeh-Khaksar, Mohsen Ansari, and Alireza Ejlali, "ReMap: Reliability Management of Peak-Power-Aware Real-Time Embedded Systems through Task Replication," IEEE Transactions on Emerging Topics in Computing, in press.
Mohsen Ansari, Mohammad Salehi, Sepideh Safari, Alireza Ejlali, and Muhammad Shafique, "Peak-Power-Aware Primary-Backup Technique for Efficient Fault-Tolerance in Multicore Embedded Systems," IEEE Access, vol. 8, pp. 142843-142857, 2020.
Javad Saber-Latibari, Mohsen Ansari, Pourya Gohari-Nazari, Sina Yari-Karin, Amir Mahdi Hosseini Monazzah, and Alireza Ejlali, "READY: Reliability- and Deadline-Aware Power-Budgeting for Heterogeneous Multi-Core Systems," IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 40, no. 4, pp. 646-654, April 2021.
Mohsen Ansari, Amir Yeganeh-Khaksar, Sepideh Safari, and Alireza Ejlali, "Peak-Power-Aware Energy Management for Periodic Real-Time Applications," IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 39, no. 4, pp. 779-788, April 2020.
Mohsen Ansari, Javad Saber-Latibari, Mostafa Pasandideh, and Alireza Ejlali, "Simultaneous Management of Peak-Power and Reliability in Heterogeneous Multicore Embedded Systems," IEEE Transactions on Parallel and Distributed Systems, vol. 31, no. 3, pp. 623-633, 1 March 2020.
Mohsen Ansari, Mostafa Pasandideh, Javad Saber-Latibari, and Alireza Ejlali, "Meeting Thermal Safe Power in Fault-Tolerant Heterogeneous Embedded Systems," IEEE Embedded Systems Letters,vol. 12, no. 1, pp. 29-32, March 2020.
Mohsen Ansari, Mostafa Pasandideh, and Alireza Ejlali, "Peak Power Management in Standby-Sparing Systems," The CSI Journal on Computing Science and Information Technology, In Press (in Persian).
Sepideh Safari, Mohsen Ansari, Ghazal Ershadi, and Shaahin Hessabi, "On the Scheduling of Energy-Aware Fault-Tolerant Mixed-Criticality Multicore Systems with Service Guarantee Exploration," IEEE Transactions on Parallel and Distributed Systems, vol. 30, no. 10, pp. 2338-2354, 1 Oct. 2019.
Mohsen Ansari, Sepideh Safari, Amir Yeganeh-Khaksar, Mohammad Salehi, and Alireza Ejlali, "Peak Power Management to Meet Thermal Design Power in Fault-Tolerant Embedded Systems," IEEE Transactions on Parallel and Distributed Systems, vol. 30, no. 1, pp. 161-173, 1 Jan. 2019.
Sepideh Safari, Mohsen Ansari, Mohammad Salehi, and Alireza Ejlali, "Energy-Budget-Aware Reliability Management in Multi-Core Embedded Systems with Hybrid Energy Source," The CSI Journal on Computer Science and Engineering (JCSE), vol. 15, no. 2, pp. 31-43, 2018.
Mohsen Ansari, Sepideh Safari, Farimah R.Poursafaei, Mohammad Salehi, and Alireza Ejlali, "AdDQ: Low-Energy Hardware Replication for Real-Time Systems through Adaptive Dual Queue Scheduling," The CSI Journal on Computer Science and Engineering (JCSE), vol. 15, no. 1, pp. 31-38, 2017.

Conference Papers

Mohsen Ansari, Sepideh Safari, Amir Yeganeh-Khaksar, Roozbeh Syiadatzadeh, Pourya Gohari-Nazari, Heba Khdr, Muhammad Shafique, Jörg Henkel, and Alireza Ejlali "ATLAS: Aging-Aware Task Replication for Multicore Safety-Critical Systems," in 29th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS 2023), May 9-12, 2023.
Farimah R. Poursafaei, Sepideh Safari, Mohsen Ansari, Amir Yeganeh-Khaksar, Mohammad Salehi, and Alireza Ejlali, "Energy- and Reliability-Aware Task Replication in Safety-Critical Embedded Systems," Proc. of the 4th Int'l of the CSI Symposium on Real-Time and Embedded Systems and Technologies (RTEST), 2022.
Sina Yari-Karin, Ali Sahraei, Javad Saber-Latibari, Mohsen Ansari, Nezam Rohbani, and Alireza Ejlali, "A Comparative Study of Joint Power and Reliability Management Techniques in Multicore Embedded Systems," Proc. of the 3rd Int'l of the CSI Symposium on Real-Time and Embedded Systems and Technologies (RTEST), 2020.
Zahra Shirmohammadi, Mohsen Ansari, Sanaz Kazemi, Sepideh Safari and Seyed-Ghasem Miremadi, "PAM: a Packet Manipulation Mechanism for Mitigating the Crosstalk Faults in NoCs," Proc. of the 13th IEEE Int'l Conference on Dependable, Autonomic and secure computing (DASC), Liverpool, England, October, 2015
Farimah R. Poursafaei, Sepideh Safari, Mohsen Ansari, Mohammad Salehi, and Alireza Ejlali, "Offline Replication and Online Energy Management for Hard Real-Time Multicore Systems," Proc. of the 1st Int'l of the CSI Symposium on Real-Time and Embedded Systems and Technologies (RTEST), Tehran, Iran, October, 2015.
Sepideh Safari, Mohsen Ansari, Zahra Shirmohammadi, and Seyed-Ghasem Miremadi, "The effects of Error Correction and Detection Codes on The Reliability Improvement of NoCs against Crosstalk Faults," Proc. of the 7th Int'l Conference on Information and Knowledge Technology, Urmia, Iran, May, 2015 (in Persian).

Students

Current Ph.D. Students

Elyas Oustad

Email: elyas.oustad23@sharif.edu

Reseach System-Level Techniques for Optimizing Cyber-Physical Systems

Abstract: Cyber-physical systems (CPS) are complex systems with organic integration and in-depth collaboration of computation, communications and control (3C) technology. Nowadays, CPS are utilized frequently in a variety fields including: transportation, healthcare, Agriculture, electricity grid, and other applications. With continual acceleration of CPS field in these days, it will be effective on every activity of the daily life in the next few years. With the ever-increasing progress in information and communication technology (ICT), multidisciplinary research fields such as physical-cyber systems have expanded. Although CPS is constantly evolving and improving, there are still unsolved challenges that require more attention. Among the challenges that have attracted the attention of many researchers, we can mention the real-time nature of CPS, which needs to respond to requests at any time. Thermal issues has been one of the most attractive concepts in the cyber part of cyber-physical systems in recent years. Heat generation due to energy consumption results in accelerated thermal damage to the processing units, reducing their lifetime. Providing a system with high dependency is one of the other things that researchers are interested in. Reliability, safety and security are among the most important sub-branches of dependability that are considered in CPS infrastructures. It seems that with the growth and spread of these systems, the research on cyber-physical systems will expand even more.

Majid Hajilou

Email: majid.hajilou77@sharif.edu

Reseach Power Management in Mixed-Criticality Cyber-Physical Systems

Abstract: ---.

Current M.Sc. Students

Mehrab Toghani

Email: mehrab.toghani79@sharif.edu

Thesis Energy- and Reliability-Aware Active Strategies for Mixed-Criticality Cyber-Physical Systems

Abstract: Mixed-Criticality Systems (MCSs) have attracted attention in the last decade due to their potential to perform functions with different critical levels. Today, these systems are used in various industries such as automotive, railway, aerospace, and healthcare. MCSs are mainly multi-core, making scheduling applications on these systems a critical challenge, and finding the optimal solution is impossible due to its NP-hard nature. On the other hand, MCSs are usually battery-based and used in safety-critical systems, so energy consumption management and fault tolerance are essential in these systems. As a result, proposing an appropriate scheduler for MCSs that simultaneously considers energy consumption and system reliability has become a significant challenge.

Mahdi Barati

Email: mahdi.barati765@sharif.edu

Thesis Decentralized Machine Learning-Based Resource Management in Fog-Edge Environments

Abstract: Federated learning is a distributed machine learning strategy that enables training a global model by learning from multiple decentralized edge clients. This approach offers advantages, such as scalability and data privacy. However, in fog-edge environments where devices have limited resources, resource management becomes crucial. The Internet-of-Things (IoTs) enabled devices, e.g., robots, drone, and embedded devices, may have limited computational capabilities, low bandwidth and limited storage capacity. Embedded devices typically have a limited available energy. For instance, smart-phones and many IoT nodes are battery-powered. Consequently, energy-efficient training is essential to reach a high accuracy. The goal of this thesis is to develop energy-efficient techniques for federated learning. This could be, for instance, client selection, which needs to determine for each client when it should be active during training. The developed techniques can be evaluated on an existing distributed platform with several embedded devices, such as NVIDIA Jetson Nano and Raspberry Pi.

Soheil Mahdizadeh

Email: soheil.mahdizadeh@sharif.edu

Thesis ---

Abstract: ---

Mohammad Pour-Ashouri

Email: mohamad.pourashory79@sharif.edu

Thesis ---

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AmirMahdi Rasooli

Email: mahdi.rasouli76@sharif.edu

Thesis ---

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MohammadSadra Galavani

Email: sadra.galavani79@sharif.edu

Thesis ---

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Graduated M.Sc. Students

Abolfazl younesi

Current Position: ----

Thesis Game Theory-Based Approach for Reliability and Power Management in Fog Computing

Abstract: Fog computing is a distributed computing paradigm that acts as a middle layer between cloud data centers and IoT-based devices/sensors. Because cloud-based services are geographically centralized, they often cannot cope with the storage and processing needs of billions of geographically distributed IoT devices/sensors. As a result, a congested network, high latency, and low quality of service (QoS) are experienced. In fog computing, computing nodes are distributed throughout the edge network and can be shared. The basic challenges in these systems are power consumption, reliability, and delay (timing). To solve the mentioned challenges, game theory as an efficient solution for modeling and evaluating the behavior of decision-making systems whose ultimate goal is to find the optimal solution(s) for players who seek They are specific goals so that they play a significant role in allocating resources, creating an efficient schedule, making appropriate momentary decisions, etc.

Moein Esnaashari

Current Position: ----

Thesis Learning-Based Reliability and Power management in Multicore systems

Abstract: Power consumption and reliability are the factors that are very important in the design of multi-core or many-core platforms. In other words, in multi-core Cyber-Physical Systems (CPSs), the reliability target and compliance with timing and power constraints are three important design factors. The existence of several processing cores in these systems allows us to exploit different fault-tolerant techniques and power consumption management methods. The power- and reliability-aware methods based on Machine Learning (ML) can adapt themselves to the system working conditions and system workload and learn from the conditions that occurred in the last periods. Also, the ML-based approaches benefit from two main advantages: a) For resource management, control becomes more accurate or comprehensive and helps to implement resource management even under uncertainty, such as changes in power demand or memory access; b) ML methods such as Reinforcement Learning (RL) or Neural Networks (NNs) are efficient to handle scenarios for which the system is not trained. Therefore, using a dynamic method that can make the best decision according to the environmental and system conditions can improve the system's performance compared to static methods. The previous works that were surveyed showed a preference for RL, especially Deep Reinforcement Learning (DRL), to obtain a better online analysis of the system state. In conclusion, the main advantage and novelty of using DRL- or RL-based methods over heuristic ones is their ability to make decisions about the incoming task in the online or run-time phase.

Hossein Hosseini Kasnavieh

Current Position: ----

Thesis Dynamic Task Replication with Imperfect Fault Detection in Multicore Cyber-Physical Systems

Abstract: With the rise of safety-critical applications in Cyber-Physical Systems, enhancing these systems' reliability has become imperative. On the other hand, as these systems typically have access to limited energy sources like batteries, their energy consumption must be managed. However, since fault-tolerance methods often impose redundancies on the system, they lead to a rise in energy consumption. Therefore, increasing reliability and reducing energy are at odds with each other, making joint management of them challenging work.

Roozbeh Siyadatzadeh

Current Position: Ph.D. Student, Computer Science, Leiden University

Thesis Learning-based Task Replication for Reliability Improvement in Multicore Embedded systems

Abstract: Cyber-Physical Systems, which include embedded systems, have become an important part of modern life. As a result, cyber-physical systems must be reliable and safe. When it comes to improving reliability and safety, task replication is a powerful method. However, it may violate the real-time constraints of the tasks and accelerate the aging effects of the system by raising the on-chip temperature. To overcome these issues, we need an appropriate method to implement task replication wisely and carefully in runtime to consider the actual case scenarios of the system. Machine learning is an effective and formidable tool in a variety of fields. Therefore our goal is to provide a machine-learning based method to implement task replication in a way that minimizes the harmful effects of the task replication.

Sina Yari-Karin

Current Position: Ph.D. Student, Department of Computer Science, George Mason University

Thesis Aging-Aware Power Management in Heterogeneous Fault-Tolerant Embedded Systems

Abstract: High reliability and low power consumption are two crucial requirements of embedded systems. To do this, embedded systems exploit fault-tolerant techniques to keep reliability at a guaranteed level and power management methods to reduce power consumption. However, the inherent redundancy of the fault-tolerant techniques increases the power consumption and, consequently, the system temperature, which leads to an increase in the rate of the aging phenomenon. Power management methods increase the system's lifetime by reducing the system temperature. However, some power management methods (e.g., Dynamic Voltage and Frequency Scaling) increase the fault rate. Recently, heterogeneous multicore systems provide an effective solution to manage embedded systems requirements. Using the heterogeneous platform is an appropriate solution for low power consumption and reliability enhancement. In the heterogeneous platforms, the simultaneous use of high-performance and low-power cores had attracted much attention. High-performance cores improve reliability and performance with their faster speeds, and the low-power cores reduce power consumption. However, the applications' execution, especially real-time applications, is more complicated than homogeneous systems due to different core types in the heterogeneous systems. In this research, an intelligent standby-sparing technique for heterogeneous systems is presented, which, with the knowledge of the system's aging, maintains reliability at a guaranteed level and selects the appropriate core type for the tasks' execution while considering the core-level power and timing constraints.

Javad Saber Latibari

Current Position: PhD Candidate, University of California, Riverside

Thesis Reliability-Aware Power Management for Heterogeneous Multicore Embedded Systems

Abstract: In recent years, heterogeneous architectures have been used extensively in the design of digital systems, so that these heterogeneous substrates are used to achieve low power, efficiency, and reliability. In addition, heterogeneous multicore systems, due to the provision of a wide range of facilities to balance the power/energy consumption and reliability, can be a suitable solution to achieve simultaneous low power consumption and high reliability. Most heterogeneous systems have a number of heterogeneous islands which can have its own voltage and frequency. For example, the Exynos 5 Octa processor which is based on ARM's big.LITTLE architecture has two heterogeneous islands that are located on each island with four homogeneous cores. Hence, the use of such architectures are proposed for future generations of embedded systems. In this research, we aim at considering effects of heterogeneous architectures on the energy/power consumption in multicore embedded systems.

Mostafa Pasandideh

Current Position: PhD Student, WAIKATO University

Thesis Peak-Power and Energy Co-management in Fault-Tolerant Multicore Embedded Systems

Abstract: Today, Dark Silicon is a pervasive problem, especially when core heterogeneity or timing guarantees are involved, for which using multicores with different power and performance characteristics are suitable architectures. We focus on minimizing peak power and energy consumption simultaneously for heterogeneous tiled multicores by considering different power characteristics of different cores, where all cores or accelerators inside a tile share the same voltage and frequency levels. For such architectures, the violation of TDP can result in significant performance losses in homogeneous and heterogeneous multicore systems. Having better power budgeting techniques is a major step towards dealing with the dark silicon problem. We attempt to propose an optimal resource management technique that introduces power density as a novel system level constraint, in order to avoid thermal violations.

Amir Yeganeh

Current Position: Technical Lead, Donyaye Pardazesh (Processing World)

Thesis Peak-Power-Aware Task Replication to Manage Reliability for Multicore Embedded Systems

Abstract: The number and diversity of cores in embedded systems is increasing rapidly. Modern embedded processors provide multiple cores for parallel computing, and hence power dissipation and thermal issues have assumed increasing significance in embedded system design. Meanwhile, reliability has become important concern in the design of embedded systems. Task replication is a powerful way to achieve high reliability, however, it is not possible to increase replications rapidly due to the Thermal Design Power (TDP) constraint. Exceeding the TDP constraint may active the Dynamic Thermal Management (DTM) to ensure thermal stability, but significant performance losses in frequent triggers of DTM. We consider the problem of achieving a given reliability target for a set of periodic real-time tasks running on a multicore system according to the TDP constraint.

Professional Services

Editorial Board (Accosiate Editor):

IEEE Embedded Systems Letters, 2024-Present.

Conference Technical Program Committee Member:

The 5th CPSSI International Symposium on Cyber-Physical Systems (Application and Theory) (CPSAT 2024), TPC and Industrial Relation Chair.

Asia and South Pacific Design Automation Conference (ASP-DAC 2024), TPC.

Asia and South Pacific Design Automation Conference (ASP-DAC 2023), TPC.

The 28th International Computer Conference, Computer Society of Iran (CSICC 2023), TPC and Publication Chair.

Reviewer:

IEEE Transactions on Circuits and Systems I: Regular (TCAS-I).

IEEE Transactions on Consumer Electronics (TCE).

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD).

IEEE Transactions on Very Large Scale Integration (VLSI) Systems (TVLSI).

IEEE Transactions on Sustainable Computing (TSUSC).

IEEE Access.

IEEE Embedded Systems Letter.

IEEE Open Journal of the Computer Society.

Plos One, PLOS.

ACM Transactions on Design Automation of Electronic Systems (TODAES).

ACM Transactions on Embedded Computing Systems (TECS).

Vehicular Communications, Elsevier.

Reliability Engineering and System Safety (RESS), Elsevier.

Microprocessors and Microsystems (MICPRO), Elsevier.

Journal of Systems Architecture (JSA), Elsevier.

The Journal of Supercomputing, Springer.

IETE Journal of Research.

Scientia Iranica - Journal - Elsevier.

Journal of Circuits, Systems, and Computers (JCSC).

Graduate:

Cyber-Physical Systems (CPS), Sharif University of Technology, Department of Computer Science and Engineering, Fall 2022 and Fall 2023.

System on Chip (SoC), Sharif University of Technology, Department of Computer Science and Engineering, Spring 2023 and Spring 2024.

Undergraduate:

Embedded Systems (Undergraduate), Sharif University of Technology, Department of Computer Science and Engineering, Fall 2021, Spring and Fall 2022, Spring 2023, Fall 2023, and Spring 2024.

Real-Time Computing (Undergraduate), Sharif University of Technology, Department of Computer Science and Engineering, Spring 2022.

Numerical Methods (Undergraduate), Sharif University of Technology, Department of Computer Science and Engineering, Groups 1 & 2, Fall 2018.

Numerical Methods (Undergraduate), Sharif University of Technology, Department of Computer Science and Engineering, Fall 2017.

Digital Design (Logic Design) (Undergraduate), Sharif University of Technology, International Campus-Tehran, Fall 2017.