Orono, Maine – Temitope Olayinka, a doctoral researcher in Electrical and Computer Engineering at the University of Maine, is drawing attention for interdisciplinary work that connects biomedical signal modeling with artificial intelligence and secure computing. Currently a Research Assistant in Orono, Olayinka contributes to projects at the intersection of ocular biomechanics, data science, and applied machine learning, bringing prior industry experience in network operations and sensor integration to academic research and community STEM programs.
“Science that makes a difference is science that reaches people, whether by improving diagnostics, protecting systems, or inspiring students to see themselves as problem-solvers,” said Temitope. “My goal is to design models and tools that are practical, testable, and ready to help.”
A Research Portfolio Focused on Impact
Olayinka’s graduate research explores relationships among physiological pressures and ocular health, including work co-authored with collaborators on the role of mean arterial pressure and intraocular pressure in distinguishing glaucomatous from non-glaucomatous eyes. The findings were disseminated through Investigative Ophthalmology & Visual Science and presented at the Association for Research in Vision and Ophthalmology (ARVO) 2025 conference, reflecting her growing presence in translational eye research.
Beyond ophthalmic modeling, her publication record includes peer-reviewed studies on convolutional neural networks for real-time gender prediction, support-vector machines and LSTM for network user-activity analysis, an Enhanced Dynamic Cluster Algorithm addressing insider-threat IP spoofing, and applications of artificial neural networks and fuzzy logic for decision support in health contexts.These works highlight a consistent theme: converting complex signals and datasets into reliable insights for clinical and operational decision-making.
From Telecom Sites to the Research Lab: A Systems Mindset
Before her current Ph.D. work, Olayinka served as an Access/IT Control Officer with Uziben Nigeria Limited, configuring and integrating multi-sensor systems on telecom sites, fuel, motion, smoke, temperature sensors, power meters, gate locks, and automatic transfer switches alongside disaster-recovery planning and ongoing upgrades across live networks. That hands-on background informs her academic research today, particularly in data acquisition, sensor reliability, and fault tolerance.
Earlier roles as an Assistant Network Administrator at Obafemi Awolowo University and Information Technologist at Fagbe Farms strengthened her foundations in LAN/WAN support, database maintenance, network troubleshooting, and governance strategies for data systems
Teaching, Mentorship, and Service
Before joining the University of Maine as a Research Assistant, Olayinka taught cybersecurity as an Assistant Lecturer at First Technical University, Ibadan, where she developed course materials and assisted students on research projects. She continues to invest in talent development through judging and mentoring roles. In 2025, she served as a judge for the Middle School Science & Engineering Fair, and in 2024, she supported VEX Robotics competitions and Consider Engineering mentoring sessions for high-school students, guiding robot design, programming, and engineering problem-solving.
Her service to the scholarly community includes peer-review contributions: she was invited to review a manuscript for IEEE Access (a leading venue in electrical and computer engineering) and reviewed two papers for ICARTI 2025, an international conference on technology and innovation. Invitations also included volunteering at the Lobstah Bowl VEX V5 Robotics Competition Signature Event, where she assisted teams in applying engineering principles to competition-ready builds
Education and Professional Preparation
Olayinka is pursuing a Ph.D. in Electrical and Computer Engineering at the University of Maine (2023–present). She holds an M.Sc. in Computer Science (Distinction) from Ladoke Akintola University of Technology and a B.Sc. (Honors) in Computer Science from Ajayi Crowther University. Her professional training includes Python programming, Heartsaver® First Aid CPR AED, Project Management (PRINCE2), and Cisco coursework, including CCNA and CCNP training.
Publications and Selected Topics
- Ocular Biomechanics & Vision Science: Co-authored study on arterial and intraocular pressures in glaucoma contexts, published in Investigative Ophthalmology & Visual Science, with a corresponding ARVO 2025 poster.
- Machine Learning & Computer Vision: Procedia Computer Science paper on real-time CNN-based gender prediction; Vallis Aurea article on SVM and LSTM for network activity analysis.
- Cybersecurity & Network Reliability: A study proposes EDPU-based clustering for IP spoofing mitigation, an ETMR + Markov approach to reduce operational downtime in traffic systems, and fuzzy k-NN for anomaly detection in customer call profiles.
- Health Decision Support: ANN + Fuzzy Logic model for child dietary prescription, illustrating cross-domain problem solving in health informatics
Collectively, these works address pressing needs in health diagnostics, infrastructure resilience, and secure systems, while maintaining an applied focus that supports real-world deployment.
Professional Memberships
Olayinka participates in communities that nurture science, engineering, and privacy practice: ARVO (Member-in-Training), Society of Women Engineers (SWE), National Society of Black Engineers (NSBE), International Association of Privacy Professionals (IAPP), and Computer Professionals of Nigeria (CPN). These affiliations reflect her engagement with both domain-specific and cross-cutting professional standards.
Community Outreach and STEM Advocacy
In Maine, Olayinka contributes to a pipeline of student opportunities through Upward Bound-aligned mentoring experiences and signature competitions such as VEX Robotics, where high school teams test designs under time and rule constraints. She has facilitated engineering workshops, helped prepare teams for regional competitions, and guided students through debugging and iteration skills foundational to engineering practice.
Her service at public showcases including the BIW (Bath Iron Works) Interactive Trailer visit—helps students connect hands-on demonstrations with shipbuilding, manufacturing, and advanced engineering careers, expanding local awareness of technical pathways.
Skills and Tooling
Temitope’s technical toolkit spans Python, MATLAB, and Kali for security contexts, in addition to a practical command of sensor interfaces and network equipment from her earlier industry roles. Across research and applications, she prioritizes reproducibility, clear documentation, and validation steps that make models and methods useful for teams beyond the lab.
A Trajectory Centered on Collaboration and Real-World Use
Olayinka’s progression—from networked sensor deployment in the field, to university classrooms, to interdisciplinary research—demonstrates continuity: a focus on solving concrete problems, aligning models with measurements, and communicating results to stakeholders. Her recent peer-review invitations, conference service, and local judging roles indicate professional trust in her subject-matter judgment and technical literacy.
“Whether it’s a clinical variable, a network anomaly, or a robotics challenge, the questions are similar: What signals matter, how reliable are they, and how can we design systems that respond with accuracy?” she said. “I’m excited to keep working at that boundary where data becomes decisions.”
About Temitope Olayinka
Temitope Olayinka is a Ph.D. researcher in Electrical and Computer Engineering at the University of Maine and a Research Assistant contributing to studies in ocular biomechanics, machine learning, and secure systems. She previously served as an Assistant Lecturer in cybersecurity and held roles in telecom sensor integration, network administration, and information technology. Her publications include venue-indexed articles on computer vision, anomaly detection, security architecture, traffic-system reliability, and AI-assisted decision support in health contexts. Olayinka serves as a peer reviewer and STEM mentor, supporting the next generation of engineers and data scientists.
Media Contact
Temitope Olayinka welcomes collaboration with research labs, hospitals, health-tech companies, engineering programs, and STEM outreach organizations committed to advancing biomedical modeling, AI for health, secure computing, and student mentorship. She offers invited talks, short courses, and hands-on workshops on topics such as:
- Ocular biomechanics and physiological signal modeling
- Machine learning for clinical decision support and health informatics
- Cybersecurity fundamentals for sensor-rich and networked systems
- Data science workflows (Python/MATLAB), validation, and reproducibility
- STEM program facilitation and mentor training for high-school and early-college learners
For partnership inquiries, speaking engagements, or media features, please contact:
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