Research

Microbiome Digital Twin

In the 21st century, the understanding of microbial ecology evolution has not been a more relevant challenge, especially as we are tackling new emerging threats to our health as well as the global environment. The aim of this research is to develop a microbiome digital twin that will connect to living bacterial cells, allowing us to predict their internal computing and communication patterns. The digital twin will be interconnected to wild-type bacteria through electrochemical nanosensors coupled with engineered bacterial biosensors, which will then be connected to a computer. This will lay the groundwork for an open platform for “Bacterial citizens on the Internet”, where we can develop (i) new forms of bio-cyber environmental monitoring systems, (ii) provide collaborative initiatives for global bacterial tracking to understand how bacteria evolve and spread globally, and (iii) utilize this platform for future medical diagnostic and treatments through miniature bio-hybrid implantable devices.

Wet Neuromorphic Computing

Gene Regulatory Neural Networks (GRNNs) harness the computational power of biological systems, transforming gene regulation into a dynamic, self-adaptive framework akin to artificial neural networks. In bacterial biofilms, these networks process environmental cues through interconnected transcription factors (TFs), mimicking weighted inputs and activation functions found in perceptrons. This bio-inspired intelligence reveals how nature encodes decision-making and learning at the molecular level, offering groundbreaking implications for synthetic biology, bio-computing, and adaptive AI systems. By bridging microbiology and machine learning, GRNNs pave the way for robust, decentralized computing models that evolve and respond autonomously to complex challenges. Gene Regulatory Neural Networks (GRNNs) communicate through quorum sensing (QS) diffusion, enabling inter-cellular signaling and coordinated decision-making. By modeling these biofilm-based networks as a Graph Neural Network (GNN), microbial communities dynamically exchange molecular signals (m), propagating regulatory information across interconnected biofilm clusters. This decentralized intelligence mirrors biological collective behavior, where each biofilm node processes, refines, and transmits information based on its gene-regulatory architecture. Such bio-inspired graph computations hold transformative potential for self-organizing AI, enabling robust, adaptive, and scalable biohybrid computing frameworks.

Terahertz Communications and Internet of Nano Things

While the telecommunications industry is rolling out 5G globally, the research community is busy researching new disruptive technologies. 6G is expected to progress into the upper millimeter-wave (100-300 GHz) and the terahertz (0.3- 10 THz) spectrum. The larger bandwidth available at THz frequencies has the potential to provide high data rates, approaching a terabit-per- second (Tbps) or more. This research aims to investigate the potential for Thz frequencies that can be used for both communications as well as sensing. One application is utilizing selected frequency ranges that are unsuitable for communication but are chosen to measure certain atmospheric gases. Another research direction is the development of Thz nanonetworks that can be embedded into building infrastructures to perform sensing.

Past Research

Brain-Machine Interface and Wireless Optogenetics (selected publications)

Bernal, S. L., Celdrán, A. H., Barros, M. T., Pérez, G. M., Balasubramaniam, S., “Security in Brain-Computer Interfaces: State-of-the-art, Opportunities, and Future Challenges”, ACM Computing Survey, vol. 54, no. 1, January 2021.
Wirdatmadja, S., Jornet, J. M., Koucheryavy, Y., Balasubramaniam, S., “Channel Impulse Analysis of Light Propagation for Point-to-point Nano Communications through Cortical Neurons”, IEEE Transactions on Communications, vol. 68, no. 11, 2020.
Donoghue, M., Jennings, B., and Balasubramaniam, S., “Capacity Analysis of a Peripheral Nerve using Modulated Compound Action Potential Pulses”, IEEE Transactions on Communications, vol. 67, no. 1, 2019.
Balasubramaniam, S., Wirdatmadja, S. A., Barros, M. T., Koucheryavy, Y., Stachowiak, M., and Jornet, J. M., “Wireless Communications for Optogenetics-based Brain Stimulation: Present Technology and Future Challenges”, IEEE Communications Magazine, vol. 56, no. 7, July 2018.
Wirdatmadja, S. A., Barros, M. T., Jornet, J. M., Koucheryavy, Y., and Balasubramaniam, S., “Wireless Optogenetic Nanonetworks for Brain Stimulation: Device Model and Charging Protocols”, IEEE Transactions on Nanobioscience, vol. 16, no. 8, 2017.

Bio-inspired Communication Networks (selected publications)

Mineraud, J., Wang, L., Balasubramaniam, S., and Kangasharju, J., “Hybrid Renewable Energy Routing for ISP Network”, in Proc. of IEEE INFOCOM, San Francisco, USA, April 2016.
Balasubramaniam, S., Mineraud, J., Perry, P., Jennings, B., Murphy, L., Donnelly, W., and Botvich, D., “Coordinating Allocation of Resources for Multiple Virtual IPTV Providers to Maximise Revenue”, IEEE Transactions on Broadcasting, vol. 57, no. 4, December 2011.
Balasubramaniam, S., Botvich, D., Carroll, R., Mineraud, J., Nakano, T., Suda, T., and Donnelly, W., “Biologically Inspired Future Service Environment”, Computer Networks (Elsevier), vol. 55, no. 15, October 2011.
Balasubramaniam, S., Leibnitz, K., Lio', P., Botvich, D., and Murata, M., “Biological Principles for Future Internet Architecture Design”, IEEE Communications Magazine, vol. 49, no. 7, July 2011.
Balasubramaniam, S., Botvich, D., Mineraud, J., Donnelly, W., and Agoulmine, N., “BiRSM: Bio-inspired Resource Self-Management for All IP Networks”, IEEE Network, vol. 24, no. 3, May/June 2010.

Body Area and Sensor Networks (selected publications)

Ivanov, S., Balasubramaniam, S., Botvich, D., and Akan, O. B., “Gravity Gradient Routing for Information Delivery in Fog Wireless Sensor Networks”, Ad Hoc Networks, vol. 46, August 2016.
Ivanov, S., Foley, C., Botvich, D., and Balasubramaniam, S., “Virtual Groups for Patient WBAN Monitoring in Medical Environments”, IEEE Transactions on Biomedical Engineering, vol. 59, no. 11, November 2012.
Ivanov, S., Botvich, D., and Balasubramaniam, S., “Cooperative Wireless Sensor Environments Supporting Body Area Networks”, IEEE Transactions on Consumer Electronics, vol. 58, no. 2, May 2012.

Research Grants

“Bacterial-based Biosensor Digital Twin for Microbial Community Sensing”, NSF US-Ireland R&D Partnership: 3 Years (September 2023 – August 2026). Amount Funded: $399,974 as Lead-PI.
“Future Artificial Intelligence through Biomimetic Living micro-Brain”, NU Collaborative Initiative grant: 2 Years (July 2022 – June 2024). Amount Funded: $150K.
“VistaMilk – Milk by Design” Science Foundation Ireland Research Centre: 6 Years (September 2018 – August 2024). Amount Funded: €25 million for 5 PIs, and €3 million allocated to the Walton Institute with me as Co-PI.
“FutureNeuro” Science Foundation Ireland Research Centre: 6 Years (September 2018 – August 2024). Amount funded €10 million, and €100,000 allocated to myself as Funded Investigator.
“CONNECT”, Science Foundation Ireland Research Centre: 6 Years (January 2016 – December 2020). Amount Funded: €150,000 to me as a Funded Investigator.
“Theoretical and Experimental Development of Protocols for Molecular Communications,” Academy of Finland – Academy of Finland Research Fellow, Duration: 5 Years (September 2014 – August 2019). Amount Funded: €835, 000 allocated to myself as PI.
“A Biologically Inspired Framework supporting Network Management for the Future Internet,” Science Foundation Ireland - Starter Investigator Research Grant (SIRG), Duration: 4 Years (October 2009 –September 2013). Amount Funded: €362, 291 allocated to myself as PI.
“Distributed Green Routing for Software Routers,” Science Foundation Ireland, Duration: 3 Months (March 2012 – June 2012). Amount Funded: €9, 191.
“Nano Communication in Microfluidic Devices,” Tampere University, Strategic Application, Duration: 1 Year (January 2014-December 2014). Amount Funded: €100,000.
“Federated Autonomic Management of End-to-end Services,” Science Foundation Ireland Strategic Research Cluster, Duration: 5 Years (January 2009-December 2013), Amount Funded: $70,000.
“Serving Society: Management of Future Communication Network and Services,” Higher Education Authority, Ireland, Duration: 3 Years (October 2008-September 2011). Amount Funded: $140,000.

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