Dr Michael Barros
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Email
m.barros@essex.ac.uk -
Location
5B.535, Colchester Campus
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Academic support hours
My Academic Support Hours are on Fridays from 11.00-12.00 either in-person or Zoom (Link available on Moodle)
Profile
Biography
Dr Barros is an Assistant Professor (Lecturer) in the School of Computer Science and Electronic Engineering at the University of Essex, UK. He is the head of the Unconventional Communications and Computing Laboratory, which is part of the BCI-NE research group. He received the PhD in Computer Science at the South East Technological University, Ireland, in 2016. He previously held multiple academic positions with prestigious grants in the Tampere University, Finland, (MSCA-IF) and Waterford Institute of Technology, Ireland (IRC GOI Postoc). Dr Barros has worked as a PI and Co-I in several grants winning a total of +€1.5M funded by the European Commission, BBSRC, Innovate UK, and others. Dr Barros is a Senior Member of the IEEE, a member of the EPSRC and BBSRC Engineering Biology Peer Review Colleges and a Fellow of the Higher Education Academy. He received the CONNECT Prof. Tom Brazil Excellence in Research Award in 2020. He has over 80 research peer-reviewed scientific publications in top journals and conferences such as Nature Scientific Reports, IEEE Transactions on Communications, IEEE Transactions on Vehicular Technology, in the areas of molecular and unconventional communications, biomedical engineering, bionano science and Beyond 5G. Since 2020, he is a review editor for the Frontiers in Communications and Networks journal in the area of unconventional communications. He also served as guest editor for the IEEE Transactions on Molecular, Biological and Multi-Scale Communications, Frontiers in Cellular Neuroscience and Digital Communications Networks journals. Link to the UC2 lab: https://www.essex.ac.uk/departments/computer-science-and-electronic-engineering/research/communications-and-networks/unconventional-communications-and-computing-laboratory
Qualifications
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PhD in Computer Science South East Technological University, (2016)
Appointments
University of Essex
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Lecturer of AI and Engineering in Medicine, University of Essex (1/6/2020 - present)
Other academic
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External Researcher/ Lead of Interest Group, The Alan Turing Institute (2/9/2024 - present)
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Member of the AI-ready Bioscience Datasets Working Group, AIBIO-UK network (6/10/2024 - present)
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MSCA-IF Research Fellow (part-time), Tampere University (9/2019 - 8/2022)
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EU Project Research Fellow, South East Technological University (1/10/2018 - 31/8/2019)
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IRC Government of Ireland Postdoc Fellow, South East Technological University (1/10/2016 - 30/9/2018)
Research and professional activities
Research interests
Biocomputing and Synthetic Biological Intelligence
Controlling tissue communication enables the discovery of novel activity patterns, unlocking new possibilities for adaptive biological behaviors. My research proposes biocomputing as a platform to optimize cellular communication for computational tasks, from Boolean logic circuits to biological artificial intelligence. Through both in-silico and in-vitro models, we have successfully demonstrated logic gate functions in astrocytes, neurons, and bacteria, proving the feasibility of this approach. This work encompasses the development of advanced control and optimization frameworks, integrating mathematical derivations in control theory with machine learning-based methods. Moving forward, I aim to expand the boundaries of biocomputing by identifying critical biological parameters for fully optimized systems. This research also focuses on extending in-vitro analyses to explore innovative sensing and therapeutic applications derived from biocomputing systems, paving the way for more efficient, adaptive, and biocompatible biomedical technologies.
Data-Driven 4D Bioprinting of Biohybrids
Data-driven 4D bioprinting is transforming the landscape of biomedical technology by enabling the development of smart, adaptive, and programmable biomaterials. Leveraging advanced AI and machine learning algorithms, my research focuses on designing and fabricating biohybrid materials tailored to individual patient needs. These biomaterials dynamically respond to changing biological environments and can be programmed for remote therapeutic interventions, offering unprecedented precision in regenerative medicine. By integrating environmental and biological data from their intended operational contexts, we devise strategies to optimize the functionality and performance of these biohybrids. This approach not only enhances patient outcomes through personalized medical solutions but also establishes a foundation for biocompatible materials with long-term stability and seamless integration into living systems. My work seeks to push the boundaries of bioprinting, paving the way for more efficient, versatile, and accessible technologies that will redefine the future of personalized medicine and bioengineering.
AI in Biology and Medicine: Building Biological Digital Twins
Molecular propagation, interaction, and information encoding are central to the complexity of biological and medical systems. My research harnesses the transformative potential of AI to decode these processes, addressing the inherent challenges and limitations of experimental biology. By leveraging machine learning and computational models, we aim to improve disease detection and therapeutic interventions, providing biologists and medical professionals with powerful tools for precision healthcare. This work focuses on the development of biological digital twins—highly detailed 3D+T reconstructions of tissues and organs, including neurons, astrocytes, smooth muscle cells, epithelial cells, and bacteria. These digital twins, validated against in-vitro experimental data, enable real-time simulation and predictive modeling of biological behaviors. Our research spans a wide range of critical areas, including genetic information processing, molecular biophysical modeling, and dynamical biomarker discovery, alongside cutting-edge advancements in gene network analysis and microscopic imaging. By bridging the gap between in-silico and experimental biology, this work aims to redefine how AI integrates with biology and medicine, enabling breakthroughs in personalized healthcare and accessible medical solutions worldwide.
Wireless Distributed Biohybrid Interfaces
The successful implementation of large-scale, long-term biohybrid systems relies on the precise coordination and distribution of devices or externally controlled cells for targeted sensing and actuation within biological environments. My research focuses on advancing wireless communication frameworks, enabling these biohybrid systems to interact seamlessly with each other and external entities—a concept foundational to the vision of the Internet of Bio-Nano Things. We have developed and refined networking protocols for ultrasound-based communication, facilitating interactions between external controllers and implantable devices. This includes powering batteryless implantable systems that serve as AI-driven neural interfaces, capable of functioning as high-precision sensing mechanisms for biological neural networks. Our work now explores integrating multiple communication modalities, such as ultrasound, optical, and RF-mmWave signals, to create robust and efficient multi-channel systems. By validating these models with 3D ex-vivo platforms, we aim to overcome challenges like signal loss and impedance mismatches, pushing the boundaries of high-bandwidth, biocompatible wireless interfaces. This research is paving the way for the next generation of biohybrid technologies with applications in regenerative medicine, neural interfacing, and beyond.
Conferences and presentations
MBMC Track Chair
IEEE Conference on Communications, 1/7/2023
TPC Co-Chair
ACM NANOCOM 2021, 13/9/2021
Teaching and supervision
Current teaching responsibilities
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Team Project Challenge (CE101)
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C++ Programming (CE221)
Current supervision
Publications
Publications (3)
Basso, G., Scherer, R. and Barros, MT., (2024). Embodied Biocomputing Sequential Circuits with Data Processing and Storage for Neurons-on-a-chip
Barros, M. and Scherer, R., (2024). Rational Engineering of Neurons-on-a-chip Towards Embodied Biological Intelligence
Regis, CDM., Rodrigues, WF., Santos, KFCD., Oriente, TN., Balasubramaniam, S. and Barros, MT., (2024). Assessing Pregnancy Health Risks from Zika Infections Based on Homeodynamic Molecular Communications
Journal articles (52)
Laissue, P., Barros, M., Li K, Bell S and Gourlay, C., Quantifying mitochondrial fragmentation as a robust indicator of phototoxicity in live cell fluorescence imaging.. Frontiers in Cell and Developmental Biology (IF 9.7)
Laissue, P., Barros, M., Neaves, L., Moss, K-A. and Mullineaux, P., Advanced fluorescence microscopy and AI-based image restoration for non-invasively imaging ROS biosensors and plant cell dynamics.. tbd
Borges, LF., Barros, MT. and Nogueira, M., (2024). Cell signaling error control for reliable molecular communications. Frontiers in Communications and Networks. 5, 1332379-
Barros, MT., Paci, M., Tervonen, A., Passini, E., Koivumäki, JT., Hyttinen, J. and Lenk, K., (2024). From Multiscale Biophysics to Digital Twins of Tissues and Organs: Future Opportunities for in-silico Pharmacology. IEEE Transactions on Molecular, Biological and Multi-Scale Communications. 10 (4), 576-594
Schöfmann, CM., Fasli, M. and Barros, MT., (2024). Investigating Biologically Plausible Neural Networks for Reservoir Computing Solutions. IEEE Access. 12, 50698-50709
Genocchi, B., Ahtiainen, A., Niemi, A., Barros, MT., Tanskanen, JMA., Lenk, K., Hyttinen, J. and Puthanmadam Subramaniyam, N., (2024). Astrocytes induce desynchronization and reduce predictability in neuron–astrocyte networks cultured on microelectrode arrays. Royal Society Open Science. 11 (10), 240839-
Adonias, GL., Siljak, H., Balasubramaniam, S. and Barros, MT., (2024). In silico modelling of neuron signal impact of cytokine storm-induced demyelination.. Open Biology. 14 (9), 1-14
Barros, MT., Kagan, BJ., Hartung, T. and Smirnova, L., (2024). Editorial: Intersection between the biological and digital: synthetic biological intelligence and organoid intelligence. Frontiers in Cellular Neuroscience. 18, 1542629-
Egan, M., Kuscu, M., Barros, MT., Booth, M., Llopis-Lorente, A., Magarini, M., Martins, DP., Schäfer, M. and Stano, P., (2023). Toward Interdisciplinary Synergies in Molecular Communications: Perspectives from Synthetic Biology, Nanotechnology, Communications Engineering and Philosophy of Science. Life. 13 (1), 208-208
Basso, G. and Barros, MT., (2023). Biocomputing Model Using Tripartite Synapses Provides Reliable Neuronal Logic Gating with Spike Pattern Diversity.. IEEE Transactions on NanoBioscience. 22 (2), 401-412
Firew, H. and Barros, M., (2023). An Adaptable Lateral Resolution Acoustic Beamforming for the Internet of Bio-Nano Things in the Brain. IEEE Transactions on Molecular, Biological and Multi-Scale Communications. 9 (2), 217-221
Kuscu, M., Stano, P., Egan, M., Barros, MT., Unluturk, BD. and Payne, GF., (2023). Guest Editorial Special Feature on Bio-Chem-ICTs: Synergies Between Bio/Nanotechnologies and Molecular Communications. IEEE Transactions on Molecular, Biological and Multi-Scale Communications. 9 (3), 351-353
Regis, CDM., Silva, ÍDS., Guimarães, PIA., Silva, ETDAD. and Barros, MT., (2023). Dual Ionic Transport Using Ca²⁺and Na²⁺ Signaling for Molecular Communication Systems. IEEE Access. 11, 61331-61345
Adonias, GL., Duffy, C., Barros, MT., McCoy, CE. and Balasubramaniam, S., (2022). Analysis of the Information Capacity of Neuronal Molecular Communications Under Demyelination and Remyelination.. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 29, 2765-2774
Barros, MT., Siljak, H., Mullen, P., Papadias, C., Hyttinen, J. and Marchetti, N., (2022). Objective Supervised Machine Learning-Based Classification and Inference of Biological Neuronal Networks. Molecules. 27 (19), 6256-6256
Martins, DP., Barros, MT., O'Sullivan, BJ., Seymour, I., O'Riordan, A., Coffey, L., Sweeney, JB. and Balasubramaniam, S., (2022). Microfluidic-Based Bacterial Molecular Computing on a Chip. IEEE Sensors Journal. 22 (17), 16772-16784
Siljak, H., Barros, MT., Cooke, L. and Marchetti, N., (2022). Intelligent Dynamic Indoor Aerosol Sensing Using Terahertz Band Wireless Communication Systems. IEEE Networking Letters. 4 (4), 184-188
Siljak, H., Barros, MT., D'Arcy, N., Martins, DP., Marchetti, N. and Balasubramaniam, S., (2022). Applying Intelligent Reflector Surfaces for Detecting Violent Expiratory Aerosol Cloud using Terahertz Signals. IEEE Network. 37 (5), 56-63
Lenk, K., Genocchi, B., Barros, MT. and Hyttinen, JAK., (2021). Larger Connection Radius Increases Hub Astrocyte Number in a 3D Neuron-Astrocyte Network Model. IEEE Transactions on Molecular, Biological and Multi-Scale Communications. 7 (2), 83-88
Barros, MT., Doan, P., Kandhavelu, M., Jennings, B. and Balasubramaniam, S., (2021). Engineering calcium signaling of astrocytes for neural-molecular computing logic gates.. Scientific Reports. 11 (1), 595-
Bernal, SL., Celdrán, AH., Pérez, GM., Barros, MT. and Balasubramaniam, S., (2021). Security in Brain-Computer Interfaces: State-of-the-Art, Opportunities, and Future Challenges. ACM Computing Surveys. 54 (1), 1-35
Barros, MT., Veletic, M., Kanada, M., Pierobon, M., Vainio, S., Balasingham, I. and Balasubramaniam, S., (2021). Molecular Communications in Viral Infections Research: Modelling, Experimental Data and Future Directions. IEEE Transactions on Molecular, Biological and Multi-Scale Communications. 7 (3), 121-141
Borges, LF., Barros, MT. and Nogueira, M., (2021). Toward Reliable Intra-Body Molecular Communication: An Error Control Perspective. IEEE Communications Magazine. 59 (5), 114-120
Haselmayr, W., Hyttinen, J., Schafer, M., Femminella, M., Morris, RJ., Lenk, K., Noel, A. and Barros, MT., (2021). Special Issue—Advances in Molecular Communications: Theory, Experiment, and Application. IEEE Transactions on Molecular, Biological and Multi-Scale Communications. 7 (2), 69-72
Balasubramaniam, S., Barros, MT., Veletic, M., Kanada, M., Pierobon, M., Vainio, S. and Balasingham, I., (2021). Editorial—Special Issue on Molecular Communications for Diagnostics and Therapeutic Development of Infectious Diseases. IEEE Transactions on Molecular, Biological and Multi-Scale Communications. 7 (3), 117-120
Siljak, H., Ashraf, N., Barros, MT., Martins, DP., Butler, B., Farhang, A., Marchetti, N. and Balasubramaniam, S., (2021). Evolving Intelligent Reflector Surface Toward 6G for Public Health: Application in Airborne Virus Detection. IEEE Network. 35 (5), 306-312
Moioli, RC., Nardelli, PHJ., Barros, MT., Saad, W., Hekmatmanesh, A., Silva, PEG., de Sena, AS., Dzaferagic, M., Siljak, H., Van Leekwijck, W., Melgarejo, DC. and Latre, S., (2021). Neurosciences and Wireless Networks: The Potential of Brain-Type Communications and Their Applications. IEEE Communications Surveys and Tutorials. 23 (3), 1599-1621
Ahtiainen, A., Genocchi, B., Tanskanen, JMA., Barros, MT., Hyttinen, JAK. and Lenk, K., (2021). Astrocytes Exhibit a Protective Role in Neuronal Firing Patterns under Chemically Induced Seizures in Neuron-Astrocyte Co-Cultures.. International Journal of Molecular Sciences. 22 (23), 12770-12770
Barros, MT., Velez, G., Arregui, H., Loyo, E., Sharma, K., Mujika, A. and Jennings, B., (2020). CogITS: cognition‐enabled network management for 5G V2X communication. IET Intelligent Transport Systems. 14 (3), 182-189
Veletic, M., Barros, MT., Arjmandi, H., Balasubramaniam, S. and Balasingham, I., (2020). Modeling of Modulated Exosome Release From Differentiated Induced Neural Stem Cells for Targeted Drug Delivery. IEEE Transactions on NanoBioscience. 19 (3), 357-367
Adonias, GL., Yastrebova, A., Barros, MT., Koucheryavy, Y., Cleary, F. and Balasubramaniam, S., (2020). Utilizing Neurons for Digital Logic Circuits: A Molecular Communications Analysis. IEEE Transactions on NanoBioscience. 19 (2), 224-236
Barros, MT. and Dey, S., (2020). Feed-Forward and Feedback Control in Astrocytes for Ca2+-Based Molecular Communications Nanonetworks. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 17 (4), 1174-1186
Pengnoo, M., Barros, MT., Wuttisittikulkij, L., Butler, B., Davy, A. and Balasubramaniam, S., (2020). Digital Twin for Metasurface Reflector Management in 6G Terahertz Communications. IEEE Access. 8, 114580-114596
Bernal, SL., Celdran, AH., Maimo, LF., Barros, MT., Balasubramaniam, S. and Perez, GM., (2020). Cyberattacks on Miniature Brain Implants to Disrupt Spontaneous Neural Signaling. IEEE Access. 8, 152204-152222
Adonias, GL., Siljak, H., Barros, MT., Marchetti, N., White, M. and Balasubramaniam, S., (2020). Reconfigurable Filtering of Neuro-Spike Communications Using Synthetically Engineered Logic Circuits.. Frontiers in Computational Neuroscience. 14, 556628-
Martins, DP., Barros, MT. and Balasubramaniam, S., (2019). Quality and Capacity Analysis of Molecular Communications in Bacterial Synthetic Logic Circuits. IEEE Transactions on NanoBioscience. 18 (4), 628-639
Arregui, H., Mujika, A., Loyo, E., Velez, G., Barros, MT. and Otaegui, O., (2019). Short-Term Vehicle Traffic Prediction for Terahertz Line-of-Sight Estimation and Optimization in Small Cells. IEEE Access. 7, 144408-144424
Barros, MT., Siljak, H., Ekky, A. and Marchetti, N., (2019). A Topology Inference Method of Cortical Neuron Networks Based on Network Tomography and the Internet of Bio-Nano Things. IEEE Networking Letters. 1 (4), 142-145
Martins, DP., Barros, MT., Pierobon, M., Kandhavelu, M., Lio, P. and Balasubramaniam, S., (2018). Computational Models for Trapping Ebola Virus Using Engineered Bacteria. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 15 (6), 2017-2027
Martins, DP., Leetanasaksakul, K., Barros, MT., Thamchaipenet, A., Donnelly, W. and Balasubramaniam, S., (2018). Molecular Communications Pulse-Based Jamming Model for Bacterial Biofilm Suppression. IEEE Transactions on NanoBioscience. 17 (4), 533-542
Balasubramaniam, S., Wirdatmadja, SA., Barros, MT., Koucheryavy, Y., Stachowiak, M. and Jornet, JM., (2018). Wireless Communications for Optogenetics-Based Brain Stimulation: Present Technology and Future Challenges. IEEE Communications Magazine. 56 (7), 218-224
Barros, MT., Silva, W. and Regis, CDM., (2018). The Multi-Scale Impact of the Alzheimer’s Disease on the Topology Diversity of Astrocytes Molecular Communications Nanonetworks. IEEE Access. 6, 78904-78917
Barros, MT., (2017). Ca 2+ -signaling-based molecular communication systems: Design and future research directions. Nano Communication Networks. 11, 103-113
Barros, MT., Mullins, R. and Balasubramaniam, S., (2017). Integrated Terahertz Communication With Reflectors for 5G Small-Cell Networks. IEEE Transactions on Vehicular Technology. 66 (7), 5647-5657
Wirdatmadja, SA., Barros, MT., Koucheryavy, Y., Jornet, JM. and Balasubramaniam, S., (2017). Wireless Optogenetic Nanonetworks for Brain Stimulation: Device Model and Charging Protocols. IEEE Transactions on NanoBioscience. 16 (8), 859-872
Taynnan Barros, M., Balasubramaniam, S. and Jennings, B., (2015). Comparative End-to-End Analysis of Ca2+-Signaling-Based Molecular Communication in Biological Tissues. IEEE Transactions on Communications. 63 (12), 5128-5142
Barros, MT., Balasubramaniam, S. and Jennings, B., (2014). Using Information Metrics and Molecular Communication to Detect Cellular Tissue Deformation. IEEE Transactions on NanoBioscience. 13 (3), 278-288
Barros, MT., Balasubramaniam, S., Jennings, B. and Koucheryavy, Y., (2014). Transmission Protocols for Calcium-Signaling-Based Molecular Communications in Deformable Cellular Tissue. IEEE Transactions on Nanotechnology. 13 (4), 779-788
De Alencar, MS., Lins, PR. and Barros, MT., (2013). Stochastic analysis of the laser spectrum considering the phase noise effect. Journal of Microwaves, Optoelectronics and Electromagnetic Applications. 12 (SPEC. ISSUE 2), 57-65
Taynnan Barros, M., Cezar de Morais Gomes, R. and Fabiano Batista Ferreira da Costa, A., (2012). Routing Architecture for Vehicular Ad-Hoc Networks. IEEE Latin America Transactions. 10 (1), 1411-1419
Taynnan Barros, M., Ribeiro Lins, P. and Sampaio Alencar, M., (2012). Traffic Grooming for Clonal Selection Routing over Dynamically Wavelength-Routed Switched Networks. IEEE Latin America Transactions. 10 (1), 1435-1443
Barros, MT., Lins Junior, PR. and Alencar, MS., (2011). CSA: A Route Clonal Selection Algorithm for Dynamic WDM Networks. Journal of Communications Software and Systems. 7 (4), 121-121
Book chapters (1)
(2013). VANET dynamic routing protocols: evaluation, challenges and solutions. In: Dynamic Ad-Hoc Networks. Institution of Engineering and Technology. 121- 140. 9781849196475
Conferences (28)
Borges, LF., Barros, MT. and Nogueira, M., Modelo de Comunicação Molecular Multiportadora com Ruído Intracelular e Intercelular
Barros, M. and Scherer, R., Rational Engineering of Neurons-on-a-chip Towards Embodied Biological Intelligence
Stano, P., Kuscu, M., Barros, M., Egan, M., Kuruma, Y., Balasubramaniam, S., Wang, J. and Nakano, T., Molecular Communication Approaches for Wetware Artificial Life: A Workshop Report
Fonseca, C., Barros, MT., Odysseos, A., Kidambi, S. and Balasubramaniam, S., (2022). Quasi-spherical absorbing receiver model of glioblastoma cells for exosome-based molecular communications
Lotter, S., Barros, MT., Schober, R. and Schafer, M., (2022). Signal Reception With Generic Three-State Receptors in Synaptic MC
Fonseca, B., Fonseca, C., Barros, M., White, M., Abhyankar, V., Borkholder, DA. and Balasubramaniam, S., (2021). Ultrasound-based Control of Micro-Bubbles for Exosome Delivery in Treating COVID-19 Lung Damage
Hyttinen, J., Genocchi, B., Ahtiainen, A., Tanskanen, JMA., Lenk, K. and Barros, MT., (2021). Astrocytes in modulating subcellular, cellular and intercellular molecular neuronal communication
Fonseca, C., Barros, MT., Odysseos, A. and Balasubramaniam, S., (2021). Predator-Prey Adaptive Control for Exosome-based Molecular Communications Glioblastoma Treatment
Genocchi, B., Ahtiainen, A., Barros, MT., Tanskanen, JMA., Hyttinen, J. and Lenk, K., (2021). Astrocytic control in in vitro and simulated neuron-astrocyte networks
Abadal, S., Barros, MT. and Krishnaswamy, B., (2021). Technical Program Committee Chairs Message
Borges, LF., Barros, MT. and Nogueira, M., (2021). A Synchronization Protocol for Multi-User Cell Signaling-Based Molecular Communication
Borges, LF., Barros, MT. and Nogueira, M., (2020). A Multi-Carrier Molecular Communication Model for Astrocyte Tissues
Veletić, M., Barros, MT., Balasingham, I. and Balasubramaniam, S., (2019). A Molecular Communication Model of Exosome-mediated Brain Drug Delivery
Guimarães, AM., de Carvalho, GIF., Silva Cruz, MDC., Lima, FS., Regis, CDM. and Barros, MT., (2019). Analyzing the effect of body temperature variation in maturation response time of B lymphocytes
RUBIN, DJ., WU, J., PATEL, D., HAJARI, U. and BARROS, M., (2019). 172-LB: Phone-Based Management by a PharmD May Improve Glycemic Control More Than Endocrinology Care Alone
Barros, MT., (2018). Capacity of the hierarchical multi-layered cortical microcircuit communication channel
Adonias, GL., Barros, MT., Doyle, L. and Balasubramaniam, S., (2018). Utilising EEG signals for modulating neural molecular communications
Benediktsson, JA., Dressler, F., Payne, GF., Juntti, M., Schober, R., Tentzeris, EM., Kokkoniemi, J., Balasingham, I., Jornet, JM., Han, C., Feng, L., Barros, M., Perli, S., Caleffi, M., Lehtomaki, J., Vegni, AM., Dinc, E., Cacciapuoti, AS., Kuscu, M., Sakkaff, Z., Akyildiz, IF., Balasubramaniam, S., Akan, OB., Pierobon, M., Nakano, T. and Armada, AG., (2018). ACM NANOCOM 2018: 5th ACM international conference on nanoscale computing and communication: Reykjavik, Iceland, September 5-7, 2018
Barros, MT. and Dey, S., (2017). Set point regulation of astrocyte intracellular Ca2+ signalling
Martins, DP., Barros, MT. and Balasubramaniam, S., (2016). Using Competing Bacterial Communication to Disassemble Biofilms
Barros, MT., Balasubramaniam, S., Jennings, B. and Koucheryavy, Y., (2014). Adaptive transmission protocol for molecular communications in cellular tissues
Barros, MT., Gomes, R., de Alencar, MS. and da Costa, AFBF., (2013). IP traffic classifiers applied to DiffServ networks
Barros, MT., Gomes, RC., De Alencar, MS. and Costa, AF., (2013). Feature filtering techniques applied in IP traffic classification
Barros, MT., Balasubramaniam, S. and Jennings, B., (2013). Error control for calcium signaling based molecular communication
Barros, MT., Gomes, R., Costa, A. and Wang, R., (2012). Evaluation of performance and scalability of routing protocols for VANETs on the Manhattan Mobility Model
Ribeiro, LP., Barros, MT. and de Alencar, MS., (2011). Performance of wavelength assignment heuristics in a dynamic optical network with adaptive routing and traffic grooming
Barros, M., Costa, A. and Gomes, R., (2010). GVDSR: A Dynamic Routing stategy for Vehicular Ad-hoc Networks
Barros, MT., Lins, PR. and Alencar, MS., (2010). Performance comparison between dynamic optical circuit switching and optical burst switching
Grants and funding
2023
Optimisation of exosome-based therapies from 3D BioPrinted stem cell structures
University of Essex (BBSRC IAA)
ROS signaling in plants: Are we missing a fundamental pathway?
Biotechnology and Biological Sciences Research Council
2022
Instant Makr Ltd KTP Application (June 22_23 R2)
Innovate UK (formerly Technology Strategy Board)
Contact
Academic support hours:
My Academic Support Hours are on Fridays from 11.00-12.00 either in-person or Zoom (Link available on Moodle)
