Ibrahim Akinjobi Aromoye | Computer Vision | Best Researcher Awards

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Mr.Ibrahim Akinjobi Aromoye | Computer Vision | Best Researcher Awards

Aromoye Akinjobi Ibrahim is a dedicated researcher in Electrical and Electronic Engineering, currently pursuing an MSc (Research) at Universiti Teknologi PETRONAS, Malaysia. His research focuses on hybrid drones for pipeline inspection, integrating machine learning to enhance surveillance capabilities. With a B.Eng. in Computer Engineering from the University of Ilorin, Nigeria, he has excelled in robotics, artificial intelligence, and digital systems. Aromoye has extensive experience as a research assistant, STEM educator, and university teaching assistant, contributing to 5G technology, UAV development, and machine learning applications. He has authored multiple research papers in reputable journals and conferences. A proactive leader, he has held executive roles in student associations and led innovative projects. His expertise spans embedded systems, IoT, and cybersecurity, complemented by certifications in Python, OpenCV, and AI-driven vision systems. He actively contributes to academic peer review and professional development, demonstrating a commitment to technological advancements and education.

Profile

Education 🎓

Aromoye Akinjobi Ibrahim is pursuing an MSc (Research) in Electrical and Electronic Engineering at Universiti Teknologi PETRONAS (2023-2025), focusing on hybrid drones for pipeline inspection under the supervision of Lo Hai Hiung and Patrick Sebastian. His research integrates machine learning with air buoyancy technology to enhance UAV flight time. He holds a B.Eng. in Computer Engineering from the University of Ilorin, Nigeria (2015-2021), graduating with a Second Class Honors (Upper) and a CGPA of 4.41/5.0. His undergraduate thesis involved developing a smart bidirectional digital counter with a light control system for energy-efficient automation. Excelling in digital signal processing, AI applications, robotics, and software engineering, he has consistently demonstrated technical excellence. His academic journey is enriched with top grades in core engineering courses and hands-on experience in embedded systems, IoT, and AI-driven automation, making him a skilled researcher and developer in advanced engineering technologies.

Experience đŸ‘šâ€đŸ«

Aromoye has diverse experience spanning research, teaching, and industry. As a Graduate Research Assistant at Universiti Teknologi PETRONAS (2023-present), he specializes in hybrid drone development, 5G technologies, and machine learning for UAVs. His contributions include designing autonomous systems and presenting research at international conferences. Previously, he was an Undergraduate Research Assistant at the University of Ilorin (2018-2021), where he worked on digital automation and AI-driven projects. In academia, he has been a Teaching Assistant at UTP, instructing courses in computer architecture, digital systems, and electronics. His industry roles include STEM Educator at STEMCafe (2022-2023), where he taught Python, robotics, and electronics, and a Mobile Games Development Instructor at Center4Tech (2019-2021), guiding students in game design. He also worked as a Network Support Engineer at the University of Ilorin (2018). His expertise spans AI, IoT, and automation, making him a versatile engineer and educator.

Awards & Recognitions 🏅

Aromoye has received prestigious scholarships and leadership recognitions. He is a recipient of the Yayasan Universiti Teknologi PETRONAS (YUTP-FRG) Grant (2023-2025), a fully funded scholarship supporting his MSc research in hybrid drones. As an undergraduate, he demonstrated leadership by serving as President of the Oyun Students’ Association at the University of Ilorin (2019-2021) and previously as its Public Relations Officer (2018-2019). He led several undergraduate research projects, including developing a smart bidirectional digital counter with a light controller system, earning accolades for innovation in automation. His contributions extend to professional peer review for IEEE Access and Results in Engineering. Additionally, he has attained multiple certifications in cybersecurity (MITRE ATT&CK), IoT, and AI applications, reinforcing his technical expertise. His dedication to academic excellence, leadership, and research impact continues to shape his career in engineering and technology.

Research Interests 🔬

Aromoye’s research revolves around hybrid UAVs, AI-driven automation, and 5G-enabled surveillance systems. His MSc thesis at Universiti Teknologi PETRONAS explores the development of a Pipeline Inspection Air Buoyancy Hybrid Drone, enhancing flight efficiency through a combination of lighter-than-air and heavier-than-air technologies. His work integrates deep learning-based object detection algorithms for real-time pipeline monitoring. He has contributed to multiple research publications in IEEE Access, Neurocomputing, and Elsevier journals, covering UAV reconnaissance, transformer-based pipeline detection, and swarm intelligence. His research interests extend to AI-driven control systems, autonomous robotics, and IoT-based energy-efficient automation. Additionally, he investigates cybersecurity applications in UAVs and smart embedded systems. His interdisciplinary expertise enables him to develop innovative solutions for industrial surveillance, automation, and smart infrastructure, positioning him as a leading researcher in AI-integrated engineering technologies.

Publications 

  • Significant Advancements in UAV Technology for Reliable Oil and Gas Pipeline Monitoring

    Computer Modeling in Engineering & Sciences
    2025-01-27 | Journal article
    DOI: 10.32604/cmes.2025.058598
    Part ofISSN: 1526-1506
    CONTRIBUTORS: Ibrahim Akinjobi Aromoye; Hai Hiung Lo; Patrick Sebastian; Shehu Lukman Ayinla; Ghulam E Mustafa Abro

  • Real-Time Pipeline Tracking System on a RISC-V Embedded System Platform

    14th IEEE Symposium on Computer Applications and Industrial Electronics, ISCAIE 2024
    2024 | Conference paper
    DOI: 10.1109/ISCAIE61308.2024.10576323

    EID:

    2-s2.0-85198901224

    Part of ISBN: 9798350348798
    CONTRIBUTORS: Wei, E.S.S.; Aromoye, I.A.; Hiung, L.H.

 

Alvaro Garcia | Computer vision | Best Researcher Award

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Dr. Alvaro Garcia | Computer vision | Best Researcher Award

Álvaro GarcĂ­a MartĂ­n es Profesor Titular en la Universidad AutĂłnoma de Madrid, especializado en visiĂłn por computadora y anĂĄlisis de video. 🎓 Obtuvo su tĂ­tulo de Ingeniero de TelecomunicaciĂłn en 2007, su MĂĄster en IngenierĂ­a InformĂĄtica y Telecomunicaciones en 2009 y su Doctorado en 2013, todos en la Universidad AutĂłnoma de Madrid. đŸ« Ha trabajado en detecciĂłn de personas, seguimiento de objetos y reconocimiento de eventos, con mĂĄs de 22 artĂ­culos en revistas indexadas y 28 en congresos. 📝 Ha realizado estancias en Carnegie Mellon University, Queen Mary University y Technical University of Berlin. 🌍 Su investigaciĂłn ha contribuido al desarrollo de sistemas de videovigilancia inteligentes, anĂĄlisis de secuencias de video y procesamiento de señales multimedia. đŸ“č Ha sido reconocido con prestigiosos premios y ha participado en mĂșltiples proyectos europeos de innovaciĂłn tecnolĂłgica. 🚀

Profile

Education 🎓

🎓 Ingeniero de TelecomunicaciĂłn por la Universidad AutĂłnoma de Madrid (2007). 🎓 MĂĄster en IngenierĂ­a InformĂĄtica y Telecomunicaciones con especializaciĂłn en Tratamiento de Señales Multimedia en la Universidad AutĂłnoma de Madrid (2009). 🎓 Doctor en IngenierĂ­a InformĂĄtica y TelecomunicaciĂłn por la Universidad AutĂłnoma de Madrid (2013). Su formaciĂłn ha sido complementada con estancias en reconocidas universidades internacionales, incluyendo Carnegie Mellon University (EE.UU.), Queen Mary University (Reino Unido) y la Technical University of Berlin (Alemania). 🌍 Durante su doctorado, recibiĂł la beca FPI-UAM para la realizaciĂłn de su investigaciĂłn. Su sĂłlida formaciĂłn acadĂ©mica le ha permitido contribuir significativamente al campo del anĂĄlisis de video y visiĂłn por computadora, consolidĂĄndose como un experto en la detecciĂłn, seguimiento y reconocimiento de eventos en secuencias de video. đŸ“č

Experience đŸ‘šâ€đŸ«

🔬 Se uniĂł al grupo VPU-Lab en la Universidad AutĂłnoma de Madrid en 2007. 📡 De 2008 a 2012, fue becario de investigaciĂłn (FPI-UAM). 🎓 Entre 2012 y 2014, trabajĂł como Profesor Ayudante. đŸ‘šâ€đŸ« De 2014 a 2019, fue Profesor Ayudante Doctor. 📚 De 2019 a 2023, ocupĂł el cargo de Profesor Contratado Doctor. đŸ›ïž Desde septiembre de 2023, es Profesor Titular en la Universidad AutĂłnoma de Madrid. 🏆 Ha participado en mĂșltiples proyectos europeos sobre videovigilancia, transmisiĂłn de contenido multimedia y reconocimiento de eventos, incluyendo PROMULTIDIS, ATI@SHIVA, EVENTVIDEO y MobiNetVideo. 🚀 Ha realizado estancias de investigaciĂłn en Carnegie Mellon University, Queen Mary University y Technical University of Berlin. 🌍 Su experiencia docente abarca asignaturas en IngenierĂ­a de Telecomunicaciones, IngenierĂ­a InformĂĄtica e IngenierĂ­a BiomĂ©dica.

Research Interests 🔬

🎯 Su investigaciĂłn se centra en la visiĂłn por computadora, el anĂĄlisis de secuencias de video y la inteligencia artificial aplicada a entornos de videovigilancia. đŸ“č Especialista en detecciĂłn de personas, seguimiento de objetos y reconocimiento de eventos en video. 🧠 Desarrolla algoritmos de aprendizaje profundo y visiĂłn artificial para mejorar la seguridad y automatizaciĂłn en ciudades inteligentes. đŸ™ïž Ha trabajado en proyectos sobre videovigilancia, transmisiĂłn multimedia y detecciĂłn de anomalĂ­as en video. 🔬 Su investigaciĂłn incluye procesamiento de imĂĄgenes, anĂĄlisis semĂĄntico y redes neuronales profundas. 🚀 Participa activamente en proyectos internacionales y colabora con universidades como Carnegie Mellon, Queen Mary y TU Berlin. 🌍 Ha publicado en IEEE Transactions on Intelligent Transportation Systems, Sensors y Pattern Recognition, consolidĂĄndose como un referente en el campo de la visiĂłn por computadora. 📜

Awards & Recognitions 🏅

đŸ„‡ Medalla “Juan LĂłpez de Peñalver” 2017, otorgada por la Real Academia de IngenierĂ­a. 📜 Reconocimiento por su contribuciĂłn a la ingenierĂ­a española en el campo de la visiĂłn por computadora y anĂĄlisis de video. đŸ›ïž Ha recibido financiaciĂłn para mĂșltiples proyectos de investigaciĂłn europeos y nacionales. 🔬 Ha participado en iniciativas de innovaciĂłn en videovigilancia y anĂĄlisis de video para seguridad. 🚀 Sus contribuciones han sido publicadas en las principales conferencias y revistas cientĂ­ficas del ĂĄrea. 📚 Su trabajo ha sido citado mĂĄs de 4500 veces y cuenta con un Ă­ndice h de 16 en Google Scholar. 📊

Publications 

1. Rafael Martín-Nieto, Álvaro García-Martín, Alexander G. Hauptmann, and Jose. M.
Martínez: “Automatic vacant parking places management system using multicamera
vehicle detection”. IEEE Transactions on Intelligent Transportation Systems, Volume 20,
Issue 3, pp. 1069-1080, ISSN 1524-9050, March 2019.

2. Rafael Martín-Nieto, Álvaro García-Martín, Jose. M. Martínez, and Juan C. SanMiguel:
“Enhancing multi-camera people detection by online automatic parametrization using
detection transfer and self-correlation maximization”. Sensors, Volume 18, Issue 12, ISSN
1424-8220, December 2018.

3. Álvaro García-Martín, Juan C. SanMiguel and Jose. M. Martínez: “Coarse-to-fine adaptive
people detection for video sequences by maximizing mutual information”. Sensors,
Volume 19, Issue 4, ISSN 1424-8220, January 2019.

4. Alejandro LĂłpez-Cifuentes, Marcos Escudero-Viñolo, JesĂșs BescĂłs and Álvaro GarcĂ­aMartĂ­n: “Semantic-Aware Scene Recognition”. Pattern Recognition. Accepted February
2020.

5. Paula Moral, Álvaro García-Martín, Marcos Escudero Viñolo, Jose M. Martinez, Jesus
BescĂłs, Jesus Peñuela, Juan Carlos Martinez, Gonzalo Alvis: “Towards automatic waste
containers management in cities via computer vision: containers localization and geopositioning in city maps”. Waste Management, June 2022.

6. Javier Montalvo, Álvaro García-Martín, Jesus Bescós: “Exploiting Semantic Segmentation
to Boost Reinforcement Learning in Video Game Environments”. Multimedia Tools and
Applications. September 2022.

7. Paula Moral, Álvaro García-Martín, Jose M. Martinez, Jesus Bescós: “Enhancing Vehicle
Re-Identification Via Synthetic Training Datasets and Re-ranking Based on Video-Clips
Information”. Multimedia Tools and Applications. February 2023.

8. Roberto Alcover-Couso, Juan C. SanMiguel, Marcos Escudero-Viñolo and Alvaro GarciaMartin: “On exploring weakly supervised domain adaptation strategies for semantic
segmentation using synthetic data”. Multimedia Tools and Applications. February 2023.

9. Juan Ignacio Bravo PĂ©rez-Villar, Álvaro GarcĂ­a-MartĂ­n, JesĂșs BescĂłs, Marcos EscuderoViñolo: “Spacecraft Pose Estimation: Robust 2D and 3D-Structural Losses and
Unsupervised Domain Adaptation by Inter-Model Consensus”. IEEE Transactions on
Aerospace and Electronic Systems. August 2023.

10. Javier Montalvo, Álvaro GarcĂ­a-MartĂ­n, JosĂ© M. Martinez. “An Image-Processing Toolkit
for Remote Photoplethysmography”, Multimedia Tools and Applications. July 2024.

11. Juan Ignacio Bravo PĂ©rez-Villar, Álvaro GarcĂ­a-MartĂ­n, JesĂșs BescĂłs, Juan C. SanMiguel:
“Test-Time Adaptation for Keypoint-Based Spacecraft Pose Estimation Based on
Predicted-View Synthesis”. IEEE Transactions on Aerospace and Electronic Systems.
May 2024.

12. Kirill Sirotkin, Marcos Escudero-Viñolo, Pablo Carballeira, Álvaro García-Martín:
“Improved Transferability of Self-Supervised Learning Models Through Batch
Normalization Finetuning”. Applied Intelligence. Aug 2024.

13. Javier Galån, Miguel Gonzålez, Paula Moral, Álvaro García-Martín, Jose M. Martinez:
“Transforming Urban Waste Collection Inventory: AI-Based Container Classification and
Re-Identification”. Waste Management, Feb 2025.

Gerardo Fernandez | Eye tracking | Excellence in Innovation

Published on by Cognitive Scientist Awards

Dr. Gerardo Fernandez | Eye tracking | Excellence in Innovation

Gerardo Abel FernĂĄndez đŸ‡ŠđŸ‡·, born on October 29, 1976, in BahĂ­a Blanca, Argentina, is a researcher specializing in neuroscience and cognitive science 🧠. He is a professor and adjunct researcher at CONICET, focusing on eye movement-based biomarkers for neurodegenerative diseases 👀. His work integrates philosophy, cognitive psychology, and technology to advance Alzheimer’s diagnosis đŸ„.

Profile

Education 🎓

🎓 Gerardo Abel FernĂĄndez obtained a degree in Philosophy (2003) from Universidad Nacional del Sur (UNS), Argentina, with a specialization in Logic and Epistemology. He later pursued a PhD in Philosophy (2011) at UNS, with his thesis titled “Dynamic word processing during reading: Mental strategies driving visual exploration”, earning a perfect 10/10 with special mention. His academic journey includes postdoctoral research as a fellow at AGENCIA (ANPCYT) and the DAAD Max Planck Institute in Berlin. His educational background bridges philosophy, neuroscience, and cognitive psychology, forming a solid foundation for his pioneering research in eye movement analysis and Alzheimer’s biomarkers. His expertise in cognitive science and technological innovation has led to the development of diagnostic tools for early neurodegenerative disease detection. 📚🔍🧠

Experience đŸ‘šâ€đŸ«

đŸ’Œ Dr. Gerardo Abel FernĂĄndez has extensive experience in neuroscience research and technological innovation. He served as a Professor of Audiovisual Language at UNS (2011–2013) and is currently an Adjunct Researcher at CONICET, focusing on non-endemic degenerative pathologies. He has worked as a Visiting Scholar at Heriot-Watt University and Strathclyde University (UK), contributing to the development of eye-tracking biomarkers for Alzheimer’s disease. Dr. FernĂĄndez is also a scientific reviewer for prestigious journals like PlosOne, Journal of Alzheimer’s Disease, and Neuropsychologia. As CTO of Viewmind, he leads biocognitive and functional performance measurement innovations. He has patented cognitive evaluation methods and received grants from institutions like ANPCYT and DAAD. His interdisciplinary expertise spans cognitive neuroscience, machine learning applications in diagnostics, and technological development for neurodegenerative disease assessment. đŸ…đŸ”ŹđŸ‘ïž

Research Interests 🔬

🔬 Dr. Gerardo Abel FernĂĄndez specializes in cognitive neuroscience, neurodegenerative disease biomarkers, and eye-tracking technology. His research focuses on early Alzheimer’s detection through oculomotor behavior analysis. He has developed innovative methods to study visual exploration, reading difficulties, and memory impairments in neurodegenerative conditions. His work integrates machine learning and artificial intelligence for cognitive assessment tools. As a Visiting Scholar in the UK, he contributed to developing biomarkers for Alzheimer’s disease. His patented eye-tracking system has clinical applications in detecting mild cognitive impairment and Alzheimer’s disease. He has published extensively in peer-reviewed journals, exploring predictive eye movement models and their correlation with cognitive decline. His cutting-edge research bridges philosophy, neuroscience, and technology, offering non-invasive diagnostic solutions for early-stage neurodegeneration. His ultimate goal is to revolutionize cognitive healthcare through technological innovation. đŸ§ đŸ‘ïžđŸ“Š

Awards & Recognitions 🏅

🏆 Dr. Gerardo Abel FernĂĄndez has received numerous awards for his contributions to neuroscience, cognitive evaluation, and Alzheimer’s diagnostics. His eye-tracking research for Alzheimer’s detection earned the Dr. JosĂ© Borda Clinical Psychiatry Prize at the 22nd International Congress of Psychiatry. He won the Novartis Innovation Award for his work on measuring cognitive performance in health and disease. As CTO of Viewmind, his team received international recognition, including the Fit4Start Luxembourg Award for health applications and the Medica Innovation Prize in DĂŒsseldorf. His research and patented cognitive evaluation equipment have been acknowledged by ANMAT (Argentina’s National Administration of Drugs, Foods, and Medical Technology) and INPI (Argentina’s National Patent Office). Dr. FernĂĄndez’s groundbreaking innovations in neurocognitive assessments have positioned him as a leading figure in technological advancements for early Alzheimer’s detection. 🏅🧠🔬

Publications 📚

  • Oculomotor behaviors and integrative memory functions in the alzheimer’s clinical syndrome

    Journal of Alzheimer’s Disease
    2021 | Journal article
    DOI: 10.3233/JAD-201189

  • A non-invasive tool for attention-deficit disorder analysis based on gaze tracks.

    ACM International Conference Proceeding Series
    2019 | Conference paper
    DOI: 10.1145/3309772.3309777

  • Microsaccadic behavior when developing a complex dynamical activity

    Journal of Integrative Neuroscience
    2018 | Journal article
    DOI: 10.3233/JIN-170057

    EID:

    2-s2.0-85053731401