Dr. Bijoy M B

With over 2 decades of experience in the IT R&D and Training, I’ve made significant contributions to projects such as the Quantum Network Simulator and developing system software stack for quantum computers and accelerators. My expertise also encompasses virtualization and hypervisor security, for ensuring robust and secure computing environments. Additionally, I’ve authored numerous publications. Currently my interest lies on Quantum Machine Learning.

• M.Tech (Computer and Information Science) from Cochin University of Science and Technology, Kerala.
• B. Tech (Computer Science & Engineering) from Kannur University, Kerala.

Quantum Network Simulator

Quantum Network Simulator has been developed at C-DAC Bangalore, with funding from the Ministry of Electronics & Information Technology (MeitY), Govt. of India.  This tool provides a simulation framework that can be used for modelling quantum networks and study the performance of different quantum network protocols, topologies and configurations.

System Software Stack for Quantum Processors and Quantum Accelerators

A functional Quantum Computing (QC) ecosystem requires extensive software components.  The software ecosystem is fundamental to QC systems design.  Quantum Accelerators are emerging speedup enablers as a specialized module incorporated with the Cluster based Supercomputing architectures.  The work involves the development of Quantum Compilers that can be coupled with simulation tools and resource estimators like qubit estimators.

Virtualization and Hypervisor Security

Security in Cloud computing, has assumed utmost importance in determining the proliferation of this new business model of computing.  While the privacy and information security risks have been addressed and are well-known, the paradigm may bring other long-term risks that are neither widely recognized nor addressed.  Owing to the fine-grained hardware resource multiplexing that forms the base of any Cloud computing stack, a series of attacks that are not intuitive surface in the realm of doing business with Cloud Computing.  The project work involves analysis of some of the attacks that impede the functioning of the critical layers of the Cloud computing stack – namely the Virtualization and the Hypervisor technologies.

QoS Framework for the Grid

The aim of this project is to build a framework to quantify and deliver Quality of Services(QoS) to the functionalities offered by the Grid. The goal is to ensure guaranteed delivery of the QoS parameters to the applications running on the grid infrastructure. The project also includes identification, quantification, measurement and monitoring of the QoS Parameters offered to the grid services.

Interoperability with European & US Grids

The project was conceived with an aim to achieve interoperability between the European Grid for E-Science (EGEE) and the Indian Garuda grid. Interoperation at various layers of middleware – including unified Job submission, data & information access, were included as part of the project deliverables.

An additional effort was carried out to integrate the cancer Grid (caGrid) from the National Cancer Institute of the USA, and the Indian Garuda grid. The aim is to integrate the technology layers of both these grids and allow seamless provisioning of applications & data to the cancer research community in India and the United States of America.

Gridhra – Grid Debugger and Runtime Analyzer

This project involved the design and development of a debugger and profiler framework for the grid infrastructure. It facilitated source level debugging of parallel processes and application threads, running on heterogeneous platforms, either individually or collectively. The profiler comprised of displaying performance characteristics of the massively parallel applications running over the grid, thereby helping the developers in fine-tuning their applications. Runtime analysis included a graphical time line display of all the parallel processes, with the corresponding communication overheads and function level break up of the application.

Service Oriented Architecture for Garuda

The goal of this activity was to design and implement a Service oriented framework for the Garuda grid. An exhaustive exploration was carried out to realize this, which involved detailed market surveys and studies on various components of the grid infrastructure. As a deliverable of the project, a service oriented architecture framework was proposed and implemented, comprising of a right mix of open source, proprietary and in-house developed components.

GARUDA Sigma

Garuda Sigma is a complete user friendly installation package with all the required software components to be deployed in Garuda Grid nodes. The objective of this toolkit is to setup basic infrastructure for the GARUDA Grid nodes. This Installation package provides a special and easy method for the distribution, installation and updating the required software on required computer systems/nodes.

Porting of Parallel debugger on 64 bit HPC Clusters

This project involved the porting of the DIViA – parallel Debugger with Integrated Visualizer and Analyzer, on 64 bit IBM AIX platforms. The activity comprised of replacing the underlying low level source debugger to support the newer 64 bit parallel computing architectures. Multi-thread support was introduced to the profiler, to speed up the MPI call tracing operations.

1. M. B. Bijoy et al., “Deep Cleaner—A Few Shot Image Dataset Cleaner Using Supervised Contrastive Learning,” in IEEE Access, vol. 11, pp. 18727-18738, 2023, doi: 10.1109/ACCESS.2023.3247500.
2. Bijoy MB, Akondi SM, Abdul Fathaah S, Raut A, Pournami PN, Jayaraj PB. Cervix type detection using a self-supervision boosted object detection technique. Int J Imaging Syst Technol. 2022; 32(5): 1615-1630. doi:10.1002/ima.22696
3. Asvija, B., Eswari, R. and Bijoy, M.B., 2021. Security threat modelling with bayesian networks and sensitivity analysis for IAAS virtualization stack. Journal of Organizational and End User Computing (JOEUC), 33(4), pp.44-69.
4. Asvija, B., Eswari, R. and Bijoy, M.B., 2020. Bayesian attack graphs for platform virtualized infrastructures in clouds. Journal of Information Security and Applications, 51, p.102455.
5. Asvija, B., Eswari, R. and Bijoy, M.B., 2020. Template attacks on ECC implementations using performance counters in CPU. Microelectronics Journal, 106, p.104935.
6. Asvija B, R. Eswari, M.B. Bijoy. 2019. Security in hardware assisted virtualization for cloud computing—State of the art issues and challenges. Computer Networks. 151(Mar 2019). Elsevier. pp. 68-92.
7. Asvija, B., Eswari, R. and Bijoy, M.B., 2017, October. Virtualization detection strategies and their outcomes in public clouds. In Postgraduate Research in Microelectronics and Electronics (PrimeAsia), 2017 IEEE Asia Pacific Conference on (pp. 45-48). IEEE.