Dr Daniel Martins
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Email
daniel.martins@essex.ac.uk -
Location
5B.534, Colchester Campus
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Academic support hours
Thursday and Friday from 1pm to 2pm, either in-person or Zoom (link available on Moodle)
Profile
Biography
Daniel received his PhD from Waterford Institute of Technology (2019), his MSc in Electrical Engineering, from Federal University of Campina Grande, Brazil (2014), and his BSc in Telecommunications Engineering, from UNIJORGE, Brazil (2008). He is an IEEE Member and volunteer, since 2005, contributing with the development of student and professional activities in South America, Ireland, and UK. He has some academic and research experience from Brazil and Ireland, where he has designed applied communications systems (industry, agriculture, and health). Currently, Daniel is investigating how bacteria process molecular signals to propose novel bacteria-based biosensing and biocomputing devices. He has experience in the following subjects: Communications Networks, Sound Processing, Signal Analysis and Processing, Communications Systems, Computational Synthetic Biology and Molecular Communications.
Qualifications
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PhD Waterford Institute of Technology,
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MSc in Electrical Engineering Federal University of Campina Grande,
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Postgraduate Diploma on University Lecturing Jorge Amado University Center,
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BSc in Telecommunications Engineering Jorge Amado University Center,
Appointments
University of Essex
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Lecturer, University of Essex (30/10/2023 - present)
Other academic
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Postdoctoral Researcher, Walton Institute, South East Technological University (2/12/2019 - 17/10/2023)
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Lecturer, Engineering, UNINASSAU (2/3/2015 - 31/7/2015)
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Course Coordinator, Telecommunications and Informatics, Vocational School Redemptorist (4/2/2013 - 30/6/2014)
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Assistant Lecturer, Engineering, Jorge Amado University Center (1/2/2010 - 29/7/2011)
Research and professional activities
Research interests
Bacteria-based computing and communication systems
Bacterial cells can be designed to sense and compute molecules. These molecules drive the individual/collective bacterial behaviour which can lead to beneficial/harmful effects to the location where they can be found. This study focus on using mathematical and computational methods to further investigate the molecular communications that enable bacterial cells to compute/sense biological information. For this purpose, simple computing tasks will be implemented using bacterial cells in custom simulators (using MATLAB/Python), and the results will be analysed through the lens of communications and computing systems theory.
Bacteria-based Functional Materials
Bacterial biofilms have been applied to design functional materials. In this investigation, bacterial biofilms will be generated using a 3D printer and matched to a specific function (e.g. biosensing and drug delivery) to provide insights on the control of bacterial responses to stimuli. These materials will be applied as experimental platforms to study the bacterial signalling process. This work will be supported by custom simulations using MATLAB/Python.
Biological Game Theory
Theoretical and experimental investigation of the interactions among prokaryotic cells and organisms using game theory, machine learning and optimisation concepts to understand how their signalling affect their survivability. This work will support and extend the analysis of: 1) interactions between nematodes and root bacteria that result in healthy soil/plants; 2) optimisation of biological negative/positive feedback loops that lead cells to amplify/reduce the expression of molecular signals.
Molecular Signal Processing
Cells (prokaryotic/eukaryotic) utilise signalling pathways to process information at the molecular level. I have investigated and supported the research of theoretical nanoscale devices that operates based on this cellular signalling mechanisms using bacteria and neurons. Currently, I am interested in investigating how cells process molecular information leading to different states (e.g. healthy and unhealthy) to create computational models that support in vitro experimentation studies. This investigation requires the understanding and analysis of biological data (retrieved from databanks) to generate mathematical and computational models using MATLAB/Python.
Agent-based Simulation of Biological Systems
Agent-based models have been applied to biological systems to understand the impact of individual cells on their populations' behaviours. This work have two goals: 1) Characterise bacterial/cell population behaviour through their individual contributions; 2) Design simulators based on biological agents to represent the populations behaviours. This study will support the design of complex bacteria-based devices/systems and explore the signalling associated with their individual and collective behaviours. This investigation will rely on MATLAB/Python/other languages to design the simulators which will be validated using data available on public and University of Essex databases.
Teaching and supervision
Current teaching responsibilities
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Team Project Challenge (CE101)
Publications
Publications (4)
Somathilaka, S., Martins, DP., Li, X., Li, Y. and Balasubramaniam, S., (2023). Inferring Gene Regulatory Neural Networks for Bacterial Decision Making in Biofilms
Koucheryavy, Y., Yastrebova, A., Martins, DP. and Balasubramaniam, S., (2021). A Review on Bio-Cyber Interfaces for Intrabody Molecular Communications Systems
Martins, DP., Barros, MT., O'Sullivan, B., Seymour, I., O'Riordan, A., Coffey, L., Sweeney, J. and Balasubramaniam, S., (2021). Microfluidic-based Bacterial Molecular Computing on a Chip
Martins, DP., Q-O'Reilly, H., Coffey, L., Cotter, PD. and Balasubramaniam, S., (2020). Hydrogel-based Bio-nanomachine Transmitters for Bacterial Molecular Communications
Journal articles (11)
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
Somathilaka, SS., Balasubramaniam, S., Martins, DP. and Li, X., (2023). Revealing gene regulation-based neural network computing in bacteria. Biophysical Reports. 3 (3), 100118-100118
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., 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
Somathilaka, SS., Martins, DP., Barton, W., O'Sullivan, O., Cotter, PD. and Balasubramaniam, S., (2022). A Graph-Based Molecular Communications Model Analysis of the Human Gut Bacteriome. IEEE Journal of Biomedical and Health Informatics. 26 (7), 3567-3577
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
López Bernal, S., Perez Martins, D. and Huertas Celdrán, A., (2021). Towards the mitigation of distributed denial-of-service cyberbioattacks in bacteria-based biosensing systems. Digital Signal Processing. 118, 103241-103241
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
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
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. and Alencar, MS., (2013). Análise e Caracterização Matemática do Ruído Gerado por Ventiladores Industriais. Revista de Tecnologia da Informação e Comunicação. 4 (1), 42-46
Conferences (7)
Somathilaka, SS., Martins, DP. and Balasubramaniam, S., (2022). Information Flow of Cascading Bacterial Molecular Communication Systems with Cooperative Amplification
Martins, DP., Drohan, J., Foley, S., Coffey, L. and Balasubramaniam, S., (2021). Modulated Molecular Channel Coding Scheme for Multi-Bacterial Transmitters
Martins, DP., Balasubramaniam, S., Cotter, PD. and O'Sullivan, O., (2021). Binding Process Analysis of Bacterial-based AND Logic Gates
Martins, DP., O'Reilly, HQ., Coffey, L., Cotter, PD. and Balasubramaniam, S., (2020). Hydrogel-based Bio-nanomachine Transmitters for Bacterial Molecular Communications
Bernal, SL., Martins, DP. and Celdran, AH., (2020). Distributed Denial of Service Cyberbioattack Affecting Bacteria-based Biosensing Systems
Martins, DP., Barros, MT. and Balasubramaniam, S., (2016). Using Competing Bacterial Communication to Disassemble Biofilms
Martins, DP. and Alencar, MS., (2014). A new approach to noise measurement and analysis in an industrial facility
Contact
Academic support hours:
Thursday and Friday from 1pm to 2pm, either in-person or Zoom (link available on Moodle)
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