Arslan Munir

Research Overview


My research targets embedded and cyber-physical systems, secure and trustworthy systems, computer architecture, parallel computing, intelligent systems, AI, computer vision, data analytics, and fault tolerance. In the following, I provide an overview of my recent research endeavors.


Cognitive Architectures and Deep Learning Accelerators

My research here targets design of cognitive architectures that can enable embedded devices to learn, think, and understand both physical and social worlds by themselves. My research also focuses on hardware/software co-design and acceleration of cost-efficient deep learning architectures.

    Selected Publications
  • Jong Hun Lee, Beomjin Park, Joonho Kong, and Arslan Munir, "Row-Wise Product-Based Sparse Matrix Multiplication Hardware Accelerator with Optimal Load Balancing", IEEE Access, vol. 10, pp. 64547-64559, June 2022.   PDF
  • Jisu Kwon, Joonho Kong, and Arslan Munir, "Sparse Convolutional Neural Network Acceleration with Lossless Input Feature Map Compression for Resource-Constrained Systems", IET Computers & Digital Techniques, vol. 16, no. 1, pp. 29-43, January 2022.   PDF
  • Mahmood Azhar Qureshi and Arslan Munir, "Sparse-PE: A Performance-Efficient Processing Engine Core for Sparse Convolutional Neural Networks", IEEE Access, vol. 9, pp. 151458-151475, November 2021.   PDF
  • Jisu Kwon, Joonho Kong, and Arslan Munir, "Sparse CNN Acceleration with Lossless Input Feature Map Compression for Resource-Constrained Systems", IET Computers & Digital Techniques, 2021.  
  • Yeongmin Kim, Joonho Kong, and Arslan Munir, "CPU-Accelerator Co-Scheduling for CNN Acceleration at the Edge", IEEE Access, vol. 8, pp. 211422-211433, November 2020.   PDF
  • Mahmood Azhar Qureshi and Arslan Munir, "NeuroMAX: A High Throughput, Multi-Threaded, Log-Based Accelerator for Convolutional Neural Networks", Proc. of IEEE/ACM International Conference On Computer Aided Design (ICCAD), San Diego, California, November 2020.   PDF
  • Kwangho Lee, Joonho Kong, and Arslan Munir, "HW/SW Co-Design of Cost-Efficient CNN Inference for Cognitive IoT", Proc. of IEEE International Conference on Intelligent Computing in Data Sciences (ICDS), Fez, Morocco, October 2020.   PDF
  • Bontak Gu, Joonho Kong, Arslan Munir, and Young Geun Kim, "A Framework for Distributed Deep Neural Network Training with Heterogeneous Computing Platforms", Proc. of IEEE International Conference on Parallel and Distributed Systems (ICPADS), Tianjin, China, December 2019. (acceptance rate: 28%)   PDF
  • Artificial Intelligence and Computer Vision

    My research here targets applications of Artificial Intelligence (AI) and computer vision at the edge. My research also focuses on applications of AI and computer vision for healthcare, military and Air Force applications.

      Selected Publications
  • Sujith Gunturu, Arslan Munir, Hayat Ullah, Stephen Welch, and Daniel Flippo, "A Spatial AI-Based Agricultural Robotic Platform for Wheat Detection and Collision Avoidance", MDPI AI, vol. 3, no. 3, pp. 719-738, August 2022.   PDF
  • James Wensel, Hayat Ullah, and Arslan Munir, "ViT-ReT: Vision and Recurrent Transformer Neural Networks for Human Activity Recognition in Videos", CoRR Arxiv, Preprint. https://doi.org/10.48550/arXiv.2208.07929, August 2022. 
  • Hayat Ullah and Arslan Munir, "Human Activity Recognition Using Cascaded Dual Attention CNN and Bi-Directional GRU Framework", CoRR Arxiv, Preprint. https://doi.org/10.48550/arXiv.2208.05034, July 2022. 
  • Muhammad Zubair Khan, Yugyung Lee, Muazzam A. Khan, and Arslan Munir, "Towards Long-Range Pixels Connection for Context-Aware Semantic Segmentation", Proc. of IEEE International Conference on Biomedical and Health Informatics (BHI'22), Ioannina, Greece, September 2022.  PDF
  • Ali Hassaan Mughal, Pardhasai Chadalavada, Arslan Munir, Atri Dutta, and Mahmood Azhar Qureshi, "Design of Deep Neural Networks for Transfer Time Prediction of Spacecraft Electric Orbit-Raising", Elsevier Intelligent Systems with Applications, vol. 15, pp. 1-16, June 2022.  PDF
  • Muhammad Zubair Khan, Yugyung Lee, Arslan Munir, and Muazzam Ali Khan, "Detecting Chronic Vascular Damage with Attention-Guided Neural System", Proc. of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Houston, Texas, Online, December 2021. (acceptance rate: 19.6%)   PDF
  • Muhammad Zubair Khan, Yugyung Lee, Arslan Munir, and Muazzam Ali Khan, "Multi-Feature Extraction with Ensemble Network for Tracing Chronic Retinal Disorders", Proc. of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Houston, Texas, Online, December 2021. (acceptance rate: 19.6%)  PDF
  • Asfandyar Khan, Arif Iqbal Umar, Arslan Munir, Syed Hamad Shirazi, Muazzam Ali Khan, and Muhammad Adnan, "A QoS-Aware Machine Learning-Based Framework for AMI Applications in Smart Grid", MDPI Energies, Special Issue: Applications of Machine Learning and Evolutionary Computation in Smart Grids and Energy Communities, vol. 14, no. 23, article no. 8171, December 2021.   PDF
  • Arslan Munir, Jisu Kwon, Jong Hun Lee, Joonho Kong, Erik Blasch, Alexander Aved, and Khan Muhammad, "FogSurv: A Fog-Assisted Architecture for Urban Surveillance Using Artificial Intelligence and Data Fusion", IEEE Access, vol. 9, pp. 111938-111959, August 2021.   PDF
  • Khan Muhammad, Hayat Ullah, Mohammad S. Obaidat, Amin Ullah, Arslan Munir, Muhammad Sajjad, and Victor Hugo C. de Albuquerque, "AI-Driven Salient Soccer Events Recognition Framework for Next Generation IoT-Enabled Environments", IEEE Internet of Things Journal (IoT-J), 2021.   PDF
  • Arslan Munir, Erik Blasch, Jisu Kwon, Joonho Kong, and Alexander Aved, "Artificial Intelligence and Data Fusion at the Edge", IEEE Aerospace and Electronic Systems Magazine, 2021.   PDF
  • Arslan Munir, Jisu Kwon, Joonho Kong, Erik Blasch, Alexander Aved, and Khan Muhammad, "A Fog-Assisted Architecture for Urban Surveillance Using AI and Data Fusion", Proc. of the 23rd International Conference on Artificial Intelligence (ICAI'21), Las Vegas, Nevada, July 2021.  
  • Arslan Munir, Alexander Aved, and Erik Blasch, "Artificial Intelligence-Assisted Situational Awareness: An Air Force Perspective", Proc. of the 5th International Conference on Applied Cognitive Computing (ACC'21), Las Vegas, Nevada, July 2021.  
  • Artificial Intelligence Safety and Security

    The high rate of advances in machine learning and Artificial Intelligence (AI) techniques testify to the imminence of their widespread adoption in mission-critical systems. Already, many systems such as Unmanned Aerial Vehicles (UAVs), Intrusion Detection Systems (IDSs), and adaptive tactical radios employ some level of AI for automation and inference. This is while many more systems are expected to join this list in near future, such as industrial control systems, intelligent transportation systems including autonomous ground vehicles, smart cities, and power grids. This burgeoning integration of AI with strategic and tactical systems necessitates an in-depth, comprehensive, and practical investigation of resulting security challenges and threats. Furthermore, AI-enabled automation provides enhanced opportunities to thwart many traditional defensive techniques by leveraging approaches such as traffic analysis of covert communications, vulnerability discovery, and reverse engineering. Hence, investigation of defensive techniques against AI-enabled adversarial attacks is also of paramount importance. My research here aspires to develop comprehensive models, metrics, frameworks, and tools for analysis, implementation, and mitigation of adversarial attacks on AI systems. The AI Safety Reserach Initiative Blog provides more information and discussion about my recent endeavors related to AI safety and security reserach.

      Selected Publications
  • Vahid Behzadan and Arslan Munir, "Adversarial Reinforcement Learning Framework for Benchmarking Collision Avoidance Mechanisms in Autonomous Vehicles", IEEE Intelligent Transportation Systems Magazine (ITSM), vol. 13, no. 2, pp. 236-241, April 2019.   PDF
  • Vahid Behzadan, Arslan Munir, and Roman V. Yampolskiy, "A Psychopathological Approach to Safety Engineering in AI and AGI", Proc. of First International Workshop on Artificial Intelligence Safety Engineering (WAISE) @International Conference on Computer Safety, Reliability, and Security (SAFECOMP), Västerås, Sweden, September 2018 (accepted for publication). (acceptance rate: 50%)  PDF
  • Vahid Behzadan and Arslan Munir, "Mitigation of Policy Manipulation Attacks on Deep Q-Networks with Parameter-Space Noise", Proc. of First International Workshop on Artificial Intelligence Safety Engineering (WAISE) @International Conference on Computer Safety, Reliability, and Security (SAFECOMP), Västerås, Sweden, September 2018 (accepted for publication). (acceptance rate: 50%)  PDF
  • Vahid Behzadan and Arslan Munir, "Vulnerability of Deep Reinforcement Learning to Policy Induction Attacks", Proc. of International Conference on Machine Learning and Data Mining (MLDM), New York, New York, July 2017. (acceptance rate: 33.3%)   PDF
  • Secure and Trustworthy Systems

    As electronic and computing systems are increasingly permeating into a multitude of safety- and privacy- critical systems, such as intelligent transportation systems, smart grids, smart buildings and homes, smart Command, Control, Communications, Computers, Intelligence, Surveillance and Reconnaissance (C4ISR) and combat systems, integration of security in these systems is of paramount signficance. Recent research has demonstrated the vulnerability of these smart systems to a variety of attacks. My research agenda here is the design of secure and trustworthy intelligent systems, embedded systems, and cyber-physical systems by leveraging advances in computer architectures, hardware design, and machine learning.

      Selected Publications
  • Yousef Alghamdi, Arslan Munir, and Jawad Ahmad, "A Lightweight Image Encryption Algorithm Based on Chaotic Map and Random Substitution", MDPI Entropy, vol. 24, no. 10: 1344, pp. 1-25, September 2022.   PDF
  • Irum Matloob, Shoab Ahmed Khan, Rukaiya Rukaiya, Muazzam A. Khan Khattak, and Arslan Munir, "A Sequence Mining-Based Novel Architecture for Detecting Fraudulent Transactions in Healthcare Systems", IEEE Access, vol. 10, pp. 48447-48463, April 2022.   PDF
  • Jameel Arif, Muazzam A. Khan, Baraq Ghaleb, Jawad Ahmad, Arslan Munir, Umer Rashid, and Ahmed Al-Dubai, "A Novel Chaotic Permutation-Substitution Image Encryption Scheme Based on Logistic Map and Random Substitution", IEEE Access, vol. 10, pp. 12966-12982, January 2022.  PDF
  • Arslan Munir, Erik Blasch, Alexander Aved, Edward Paul Ratazzi, and Joonho Kong, "Security Issues in Situational Awareness: Adversarial Threats and Mitigation Techniques", IEEE Security & Privacy, 2022.  PDF
  • Dalton A. Hahn, Arslan Munir, and Vahid Behzadan, "Security and Privacy Issues in Intelligent Transportation Systems: Classification and Challenges", IEEE Intelligent Transportation Systems Magazine (ITSM), vol. 13, no. 1, pp. 181-196, 2021.   PDF
  • Bikash Poudel and Arslan Munir, "Design and Evaluation of a PVT Variation-Resistant TRNG Circuit", Proc. of IEEE International Conference on Computer Design (ICCD), Orlando, Florida, October 2018. (acceptance rate: 29%)   PDF
  • Bikash Poudel and Arslan Munir, "Design and Evaluation of a Reconfigurable ECU Architecture for Secure and Dependable Automotive CPS", IEEE Transactions on Dependable and Secure Computing (TDSC), 2018.  PDF
  • Arslan Munir and Farinaz Koushanfar, "Design and Analysis of Secure and Dependable Automotive CPS: A Steer-by-Wire Case Study", IEEE Transactions on Dependable and Secure Computing (TDSC), 2018 (accepted for publication).  PDF
  • Bikash Poudel and Arslan Munir, "Design and Evaluation of a Novel ECU Architecture for Secure and Dependable Automotive CPS", Proc. of IEEE Consumer Communications & Networking Conference (CCNC), Las Vegas, Nevada, January 2017. (acceptance rate: 34.8%)   PDF
  • Hardware-based Security

    Although traditional cryptographic protocols can be used to integrate security primitives in computing systems, traditional cryptography presents limitations regarding secure storage of secret keys and reliable identification of devices. A variety of attacks for extracting, estimating, or cloning secret keys that are stored digitally in a nonvolatile memory have been developed and reported over the past several years. Security issues for computing systems are exacerbated by the potential usage of counterfeit electronic components (i.e., an illegal forgery or imitation of an original design). My research agenda here is the hardware implementation of cryptographic protocols for performance and energy-efficiency, and to incorporate hardware-based security primitives (e.g., physically unclonable functions (PUFs), design and netlist obfuscation, hardware description language wrappers) in the design to create secure systems that are resistant to a variety of attacks, such as side-channel attacks, fault-injection attacks, and reverse engineering and modeling attacks.

      Selected Publications
  • Mahmood Azhar Qureshi and Arslan Munir, "PUF-RAKE: A PUF-based Robust and Lightweight Authentication and Key Establishment Protocol", IEEE Transactions on Dependable and Secure Computing (TDSC), 2021.   PDF
  • Bikash Poudel, Arslan Munir, Joonho Kong, and Muazzam A. Khan, "Design and Validation of Low-Power Secure and Dependable Elliptic Curve Cryptosystem", MDPI Journal of Low Power Electronics and Applications (JLPEA), Special Issue: Low-Power Hardware Security, vol. 11, no. 4, article no. 43, November 2021.   PDF
  • Mahmood Azhar Qureshi and Arslan Munir, "PUF-IPA: A PUF-based Identity Preserving Protocol for Internet of Things Authentication", Proc. of IEEE Consumer Communications & Networking Conference (CCNC), Las Vegas, Nevada, January 2020.  
  • Mahmood Azhar Qureshi and Arslan Munir, "PUF-RLA: A PUF-based Reliable and Lightweight Authentication Protocol employing Binary String Shuffling", Proc. of IEEE International Conference on Computer Design (ICCD), Abu Dhabi, United Arab Emirates (U.A.E.), November 2019. (acceptance rate: 23.8%)   PDF
  • Bikash Poudel and Arslan Munir, "Design and Evaluation of a PVT Variation-Resistant TRNG Circuit", Proc. of IEEE International Conference on Computer Design (ICCD), Orlando, Florida, October 2018. (acceptance rate: 29%)   PDF
  • Bikash Poudel, Sushil J. Louis, and Arslan Munir, "Evolving Side-Channel Resistant Reconfigurable Hardware for Elliptic Curve Cryptography", Proc. of IEEE Congress on Evolutionary Computation (CEC), Donostia - San Sebastián, Spain, June 2017. (acceptance rate: 57%)  PDF
  • Cyber-Transportation Systems

    Transportation systems are an integral part of contemporary human living. Cyber-Transportation Systems (CTS) integrate a multitude of embedded hard real-time control functionalities and advanced information and entertainment (infotainment) features. The true paradigm shift for future CTS is not only a result of this increasing plurality of subsystems and functions, but is also driven by the unprecedented levels of intra- and inter-ITS connections and communications as well as networking with external entities. My current ITS research focus on automotive embedded systems. Modern cars consist of more than 100 Electronic Control Units (ECUs) to implement various distributed control applications. The next generation of automotives (also known as cybercars) will further escalate the proliferation of ECUs to enable new and exciting control and infotainment applications. My research agenda, here, is to develop novel ECU architectures and approaches for the design of secure and dependable cybercars.



      Selected Publications
  • Zakria Qadir, Arslan Munir, Tehreem Ashfaq, Hafiz Suliman Munawar, Muazzam A. Khan, and Khoa Le, "A Prototype of an Energy-Efficient MAGLEV Train: A Step Towards Cleaner Train Transport", Elsevier Cleaner Engineering and Technology, vol. 4, pp. 1-11, October 2021.   PDF
  • Dalton A. Hahn, Arslan Munir, and Vahid Behzadan, "Security and Privacy Issues in Intelligent Transportation Systems: Classification and Challenges", IEEE Intelligent Transportation Systems Magazine (ITSM), vol. 13, no. 1, pp. 181-196, 2021.   PDF
  • Arslan Munir and Farinaz Koushanfar, "Design and Analysis of Secure and Dependable Automotive CPS: A Steer-by-Wire Case Study", IEEE Transactions on Dependable and Secure Computing (TDSC), vol. 17, no. 4, pp. 813-827, July-August 2020.  PDF
  • Vahid Behzadan and Arslan Munir, "Adversarial Exploitation of Emergent Dynamics in Smart Cities", Proc. of IEEE International Smart Cities Conference (ISC2), Kansas City, Missouri, September 2018.   PDF
  • Bikash Poudel, Naresh Kumar Giri, and Arslan Munir, "Design and Comparative Evaluation of GPGPU- and FPGA-based MPSoC ECU Architectures for Secure, Dependable, and Real-Time Automotive CPS", Proc. of IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP), Seattle, Washington, July 2017. (acceptance rate: 29.8%) — Selected as Best Paper Finalist (one of the top three papers in IEEE ASAP, 2017)   PDF
  • Arslan Munir, "Safety Assessment and Design of Dependable Cybercars: For today and the future", IEEE Consumer Electronics (CE) Magazine, vol. 6, no. 2, pp. 69-77, April 2017.   PDF
  • Arslan Munir and Farinaz Koushanfar, "Design and Performance Analysis of Secure and Dependable Cybercars: A Steer-by-Wire Case Study", Proc. of IEEE Consumer Communications & Networking Conference (CCNC), Las Vegas, Nevada, January 2016. (acceptance rate: 32%)   PDF
  • Internet of Things (IoT)

    IoT is a network of physical things, objects or devices, such as Radio-Frequency Identification (RFID) tags, sensors, actuators, mobile phones, tablets, and laptops. Objects in IoT are uniquely identifiable through an addressing scheme, and interact and cooperate with neighboring things to reach common goals. IoT enables objects to be sensed and controlled remotely across existing network infrastructure, including Internet, thereby creating opportunities for more direct integration of the physical world into the cyber world. IoT becomes an instance of Cyber-Physical Systems (CPS) with the incorporation of sensors and actuators in IoT devices. Objects in IoT can be grouped into geographical or logical clusters. Various IoT clusters generate a huge amount of data from diverse locations, which engenders the need to index, store, and process this data more efficiently. Offloading computation and storage from IoT devices to cloud is an increasing practice as many IoT devices are resource constrained, and are unable to meet the escalating computation and storage requirements of various applications in situ.

    Although cloud computing paradigm is able to handle the huge amount of data from IoT clusters, however, the transfer of this enormous data to cloud computers presents a challenge due to limited bandwidth. Furthermore, many IoT and CPS applications are real-time and offloading all of these applications' compute-intensive tasks to the cloud is not feasible because of real-time constraints. Consequently, there is a need to process data near data source and the edge computing provides a solution to this problem. My research here focuses on developing novel IoT architectures and lightweight optimization methodologies to better meet diverse and varying application requirements, and developing data movement strategies between IoT devices, edge server, and the cloud data center that consider performance, energy, and real-time constraints of IoT applications.

      Selected Publications
  • Muhammad Aneeq Abid, Naokhaiz Afaqui, Muazzam A. Khan, Muhammad Waseem Akhtar, Asad Waqar Malik, Arslan Munir, Jawad Ahmad, and Balawal Shabir, "Evolution towards Smart and Software-Defined Internet of Things", MDPI AI, vol. 3, no. 1, pp. 100-123, February 2022. PDF
  • Prasanna Kansakar and Arslan Munir, "Selecting Microarchitecture Configuration of Processors for Internet of Things", IEEE Transactions on Emerging Topics in Computing (TETC), 2018 (accepted for publication). PDF
  • Prasanna Kansakar and Arslan Munir, "A Two-Tiered Heterogeneous and Reconfigurable Application Processor for Future Internet of Things", Proc. of IEEE Computer Society Annual Symposium on VLSI (ISVLSI), Hong Kong, China, July 2018. (acceptance rate: 29%)   PDF
  • Raj Mani Shukla and Arslan Munir, "An Efficient Computation Offloading Architecture for the Internet of Things (IoT) Devices", Proc. of IEEE Consumer Communications & Networking Conference (CCNC), Las Vegas, Nevada, January 2017. (acceptance rate: 34.8%) PDF
  • Arslan Munir, Ann Gordon-Ross, Susan Lysecky, and Roman Lysecky, "A Lightweight Dynamic Optimization Methodology and Application Metrics Estimation Model for Wireless Sensor Networks", Elsevier Sustainable Computing: Informatics and Systems, vol. 3, no. 2, pp. 94-108, June 2013. PDF
  • Fog Computing

    Fog computing is a novel trend in computing that aims to process data near data source. The fog computing pushes applications, services, data, and computing power away from the centralized nodes to the logical extremes of a network. The fog computing significantly decreases the data volume that must be moved between end devices and cloud. The fog computing reduces the latency of data transmission from IoT devices to the offloaded server because of the proximity of fog to the IoT devices. The fog computing enables data analytics and knowledge generation to occur at the data source. Although fog computing alleviates some of the issues facing the realization of future IoT applications, the fog nodes (e.g., edge servers, routers, base stations) may not be able to meet performance, throughput, energy, and latency constraints of future IoT applications unless the fog computing architecture is adapted to meet these application requirements. This adaptation is needed at both the system-level and node-level for fog computing. My research here targets design of a reconfigurable fog node architecture, and developing fog-assisted architectures for smart cities, smart farming, and hospitality industry.

      Selected Publications
  • Arslan Munir, Jisu Kwon, Jong Hun Lee, Joonho Kong, Erik Blasch, Alexander Aved, and Khan Muhammad, "FogSurv: A Fog-Assisted Architecture for Urban Surveillance Using Artificial Intelligence and Data Fusion", IEEE Access, vol. 9, pp. 111938-111959, August 2021.   PDF
  • Prasanna Kansakar, Arslan Munir, and Neda Shabani, "A Fog-Assisted Architecture to Support an Evolving Hospitality Industry in Smart Cities", Proc. of the 16th International Conference on Frontiers of Information Technology (FIT), Islamabad, Pakistan, December 2018. (acceptance rate: 23%)   PDF
  • Prasanna Kansakar, Arslan Munir, and Neda Shabani, "A Fog-assisted Architecture to Support an Evolving Hospitality Industry", Proc. of Annual International Council on Hotel, Restaurant, and Institutional Education (ICHRIE) Conference, Palm Springs, California, July 2018.   PDF
  • Arslan Munir, Prasanna Kansakar, and Samee U. Khan, "IFCIoT: Integrated Fog Cloud IoT: A novel architectural paradigm for the future Internet of Things", IEEE Consumer Electronics (CE) Magazine, vol. 6, no. 3, pp. 74-82, July 2017.   PDF
  • Parallel and Reconfigurable Architectures

    Technological advancements in silicon industry, as predicted by Moore's law, have enabled integration of billions of transistors on-chip. To exploit this high transistor density, computing systems, including embedded systems, are undergoing a paradigm shift from serial systems (single-core) to parallel systems (multicore). This paradigm shift has led to the emergence of diverse parallel multicore architectures in a plethora of application domains. Innovative multicore architectures have emerged to meet the performance requirements of various compute-intensive applications. Due to the increasing proliferation of computing systems in diverse application domains, the need for application-specific design of parallel processing platforms is paramount. Although application-specific integrated circuits (ASICs) offer tremendous improvments in performance and power, cost of ASICs can be prohibitive especially for niche markets. Consequently, reconfigurable architectures provide a feasible alternative to ASICs for a plethora of application domains. In order to tailor reconfigurable architectures for application-specific requirements, a multitude of computing parameters (e.g., processor cores, operating frequency, cache sizes) and communication parameters (e.g., transmission power, antenna gain, modulation) need to be tuned accordingly. My research agenda, here, is the HW/SW co-design and optimization of performance per watt for parallel architectures, and to develop novel design and optimization methodologies to tune various reconfigurable architectural parameters for different application domains.


      Selected Publications
  • Jong Hun Lee, Beomjin Park, Joonho Kong, and Arslan Munir, "Row-Wise Product-Based Sparse Matrix Multiplication Hardware Accelerator with Optimal Load Balancing", IEEE Access, vol. 10, pp. 64547-64559, June 2022.   PDF
  • Prasanna Kansakar and Arslan Munir, "A Design Space Exploration Methodology for Parameter Optimization in Multicore Processors", IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 29, no. 1, pp. 2-15, January 2018.   PDF
  • Tosiron Adegbija, Ann Gordon-Ross, and Arslan Munir, "Phase Distance Mapping: A Phase-based Cache Tuning Methodology for Embedded Systems", Springer Design Design Automation for Embedded Systems (DAES), vol. 18, no. 3, pp. 251-278, September 2014. PDF
  • Arslan Munir, Ann Gordon-Ross, and Sanjay Ranka, "Multi-core Embedded Wireless Sensor Networks: Architecture and Applications", IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 25, no. 6, pp. 1553-1562, June 2014. PDF
  • Arslan Munir, Farinaz Koushanfar, Ann Gordon-Ross, and Sanjay Ranka, "High-Performance Optimizations on Tiled Many-Core Embedded Systems: A Matrix Multiplication Case Study", (ACM/Springer) The Journal of Supercomputing, vol. 66, no. 1, pp. 431-487, October 2013. PDF
  • Information Technology in Business and Hospitality Industry

    Information systems are an integral part of business and hospitality industry today. The Information Technology (IT) helps streamline operations, reduce costs, improve efficiency, and maximize profit in various facets of business and hospitality industry. Meeting the customers' expectations is a key factor in various businesses, including the hospitality industry, to grasp the customers' loyalty. To achieve this goal, marketing professionals in this industry actively look for ways to utilize their data in the best possible manner and advance their data analytic solutions, such as identifying a unique market segmentation clustering and developing a recommendation system. Consequently, there is a need to develop computing architectures and approaches to collect and utilize this data in best possible manner. While utilizing data analytics to improve business profitablity and improve customer satisfaction is auspicious, there exist challenges to ensure security and privacy of this data. My research goal here is to design novel architectures and methodolgies (e.g., clustering and recommendation) to assist in information gathering, analytics, and decision-making geared towards improving customer experience, enhancing business insight, and increasing revenue while safeguarding security and privacy of customer and organizational data.

      Selected Publications
  • Neda Shabani, Arslan Munir, and Saraju P. Mohanty, "A Study of Big Data Analytics in Internal Auditing", Proc. of Intelligent Systems Conference (IntelliSys), Amsterdam, Netherlands, September 2021.   PDF
  • Neda Shabani and Arslan Munir, "A Review of Cyber Security Issues in Hospitality Industry", Proc. of Computing Conference, London, United Kingdom, July 2020.  
  • Neda Shabani, Arslan Munir, and Azizul Hassan, "E-Marketing via Augmented Reality: A Case Study in the Tourism and Hospitality Industry", IEEE Potentials, vol. 38, no. 1, pp. 43-47, January 2019.   PDF
  • Prasanna Kansakar, Arslan Munir, and Neda Shabani, "Technology in Hospitality Industry: Prospects and Challenges", IEEE Consumer Electronics (CE) Magazine, vol. 8, no. 3, pp. 60-65, May 2019.   PDF
  • Prasanna Kansakar, Arslan Munir, and Neda Shabani, "A Fog-Assisted Architecture to Support an Evolving Hospitality Industry in Smart Cities", Proc. of the 16th International Conference on Frontiers of Information Technology (FIT), Islamabad, Pakistan, December 2018. (acceptance rate: 23%)   PDF
  • Prasanna Kansakar, Arslan Munir, and Neda Shabani, "A Fog-assisted Architecture to Support an Evolving Hospitality Industry", Proc. of Annual International Council on Hotel, Restaurant, and Institutional Education (ICHRIE) Conference, Palm Springs, California, July 2018.   PDF
  • Neda Shabani, Arslan Munir, and Avishek Bose, "Analysis of Big Data Maturity Stage in Hospitality Industry", Proc. of 23rd Annual Graduate Education and Graduate Student Research Conference in Hospitality and Tourism, Fort Worth, Texas, January 2018.   PDF