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 šŸŽ“

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 šŸ‘Øā€šŸ«

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 šŸ…

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 Studentsā€™ 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 šŸ”¬

Aromoyeā€™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.

PublicationsĀ 

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

    Computer Modeling in Engineering & Sciences
    2025-01-27 |Ā Journal article
    DOI:Ā 10.32604/cmes.2025.058598
    Part ofISSN:Ā 1526-1506
    CONTRIBUTORS:Ā Ibrahim Akinjobi Aromoye;Ā Hai Hiung Lo;Ā Patrick Sebastian;Ā Shehu Lukman Ayinla;Ā 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 |Ā Conference paper
    DOI:Ā 10.1109/ISCAIE61308.2024.10576323
    EID:

    2-s2.0-85198901224

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

 

Alvaro Garcia | Computer vision | Best Researcher Award

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Dr. Alvaro Garcia | Computer vision | Best Researcher Award

Ɓlvaro GarcĆ­a MartĆ­n es Profesor Titular en la Universidad AutĆ³noma de Madrid, especializado en visiĆ³n por computadora y anĆ”lisis de video. šŸŽ“ Obtuvo su tĆ­tulo de Ingeniero de TelecomunicaciĆ³n en 2007, su MĆ”ster en IngenierĆ­a InformĆ”tica y Telecomunicaciones en 2009 y su Doctorado en 2013, todos en la Universidad AutĆ³noma de Madrid. šŸ« Ha trabajado en detecciĆ³n de personas, seguimiento de objetos y reconocimiento de eventos, con mĆ”s de 22 artĆ­culos en revistas indexadas y 28 en congresos. šŸ“ Ha realizado estancias en Carnegie Mellon University, Queen Mary University y Technical University of Berlin. šŸŒ Su investigaciĆ³n ha contribuido al desarrollo de sistemas de videovigilancia inteligentes, anĆ”lisis de secuencias de video y procesamiento de seƱales multimedia. šŸ“¹ Ha sido reconocido con prestigiosos premios y ha participado en mĆŗltiples proyectos europeos de innovaciĆ³n tecnolĆ³gica. šŸš€

Profile

Education šŸŽ“

šŸŽ“ Ingeniero de TelecomunicaciĆ³n por la Universidad AutĆ³noma de Madrid (2007). šŸŽ“ MĆ”ster en IngenierĆ­a InformĆ”tica y Telecomunicaciones con especializaciĆ³n en Tratamiento de SeƱales Multimedia en la Universidad AutĆ³noma de Madrid (2009). šŸŽ“ Doctor en IngenierĆ­a InformĆ”tica y TelecomunicaciĆ³n por la Universidad AutĆ³noma de Madrid (2013). Su formaciĆ³n 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). šŸŒ Durante su doctorado, recibiĆ³ la beca FPI-UAM para la realizaciĆ³n de su investigaciĆ³n. Su sĆ³lida formaciĆ³n acadĆ©mica le ha permitido contribuir significativamente al campo del anĆ”lisis de video y visiĆ³n por computadora, consolidĆ”ndose como un experto en la detecciĆ³n, seguimiento y reconocimiento de eventos en secuencias de video. šŸ“¹

Experience šŸ‘Øā€šŸ«

šŸ”¬ Se uniĆ³ al grupo VPU-Lab en la Universidad AutĆ³noma de Madrid en 2007. šŸ“” De 2008 a 2012, fue becario de investigaciĆ³n (FPI-UAM). šŸŽ“ Entre 2012 y 2014, trabajĆ³ como Profesor Ayudante. šŸ‘Øā€šŸ« De 2014 a 2019, fue Profesor Ayudante Doctor. šŸ“š De 2019 a 2023, ocupĆ³ el cargo de Profesor Contratado Doctor. šŸ›ļø Desde septiembre de 2023, es Profesor Titular en la Universidad AutĆ³noma de Madrid. šŸ† Ha participado en mĆŗltiples proyectos europeos sobre videovigilancia, transmisiĆ³n de contenido multimedia y reconocimiento de eventos, incluyendo PROMULTIDIS, ATI@SHIVA, EVENTVIDEO y MobiNetVideo. šŸš€ Ha realizado estancias de investigaciĆ³n en Carnegie Mellon University, Queen Mary University y Technical University of Berlin. šŸŒ Su experiencia docente abarca asignaturas en IngenierĆ­a de Telecomunicaciones, IngenierĆ­a InformĆ”tica e IngenierĆ­a BiomĆ©dica.

Research Interests šŸ”¬

šŸŽÆ Su investigaciĆ³n se centra en la visiĆ³n por computadora, el anĆ”lisis de secuencias de video y la inteligencia artificial aplicada a entornos de videovigilancia. šŸ“¹ Especialista en detecciĆ³n de personas, seguimiento de objetos y reconocimiento de eventos en video. šŸ§  Desarrolla algoritmos de aprendizaje profundo y visiĆ³n artificial para mejorar la seguridad y automatizaciĆ³n en ciudades inteligentes. šŸ™ļø Ha trabajado en proyectos sobre videovigilancia, transmisiĆ³n multimedia y detecciĆ³n de anomalĆ­as en video. šŸ”¬ Su investigaciĆ³n incluye procesamiento de imĆ”genes, anĆ”lisis semĆ”ntico y redes neuronales profundas. šŸš€ Participa activamente en proyectos internacionales y colabora con universidades como Carnegie Mellon, Queen Mary y TU Berlin. šŸŒ Ha publicado en IEEE Transactions on Intelligent Transportation Systems, Sensors y Pattern Recognition, consolidĆ”ndose como un referente en el campo de la visiĆ³n por computadora. šŸ“œ

Awards & Recognitions šŸ…

šŸ„‡ Medalla “Juan LĆ³pez de PeƱalver” 2017, otorgada por la Real Academia de IngenierĆ­a. šŸ“œ Reconocimiento por su contribuciĆ³n a la ingenierĆ­a espaƱola en el campo de la visiĆ³n por computadora y anĆ”lisis de video. šŸ›ļø Ha recibido financiaciĆ³n para mĆŗltiples proyectos de investigaciĆ³n europeos y nacionales. šŸ”¬ Ha participado en iniciativas de innovaciĆ³n en videovigilancia y anĆ”lisis de video para seguridad. šŸš€ Sus contribuciones han sido publicadas en las principales conferencias y revistas cientĆ­ficas del Ć”rea. šŸ“š Su trabajo ha sido citado mĆ”s de 4500 veces y cuenta con un Ć­ndice h de 16 en Google Scholar. šŸ“Š

PublicationsĀ 

1. Rafael Martƭn-Nieto, Ɓlvaro Garcƭa-Martƭn, Alexander G. Hauptmann, and Jose. M.
MartĆ­nez: ā€œAutomatic vacant parking places management system using multicamera
vehicle detectionā€. IEEE Transactions on Intelligent Transportation Systems, Volume 20,
Issue 3, pp. 1069-1080, ISSN 1524-9050, March 2019.

2. Rafael Martƭn-Nieto, Ɓlvaro Garcƭa-Martƭn, Jose. M. Martƭnez, and Juan C. SanMiguel:
ā€œEnhancing multi-camera people detection by online automatic parametrization using
detection transfer and self-correlation maximizationā€. Sensors, Volume 18, Issue 12, ISSN
1424-8220, December 2018.

3. Ɓlvaro GarcĆ­a-MartĆ­n, Juan C. SanMiguel and Jose. M. MartĆ­nez: ā€œCoarse-to-fine adaptive
people detection for video sequences by maximizing mutual informationā€. Sensors,
Volume 19, Issue 4, ISSN 1424-8220, January 2019.

4. Alejandro LĆ³pez-Cifuentes, Marcos Escudero-ViƱolo, JesĆŗs BescĆ³s and Ɓlvaro GarcĆ­aMartĆ­n: ā€œSemantic-Aware Scene Recognitionā€. Pattern Recognition. Accepted February
2020.

5. Paula Moral, Ɓlvaro Garcƭa-Martƭn, Marcos Escudero ViƱolo, Jose M. Martinez, Jesus
BescĆ³s, Jesus PeƱuela, Juan Carlos Martinez, Gonzalo Alvis: ā€œTowards automatic waste
containers management in cities via computer vision: containers localization and geopositioning in city mapsā€. Waste Management, June 2022.

6. Javier Montalvo, Ɓlvaro GarcĆ­a-MartĆ­n, Jesus BescĆ³s: ā€œExploiting Semantic Segmentation
to Boost Reinforcement Learning in Video Game Environmentsā€. Multimedia Tools and
Applications. September 2022.

7. Paula Moral, Ɓlvaro GarcĆ­a-MartĆ­n, Jose M. Martinez, Jesus BescĆ³s: ā€œEnhancing Vehicle
Re-Identification Via Synthetic Training Datasets and Re-ranking Based on Video-Clips
Informationā€. Multimedia Tools and Applications. February 2023.

8. Roberto Alcover-Couso, Juan C. SanMiguel, Marcos Escudero-ViƱolo and Alvaro GarciaMartin: ā€œOn exploring weakly supervised domain adaptation strategies for semantic
segmentation using synthetic dataā€. Multimedia Tools and Applications. February 2023.

9. Juan Ignacio Bravo PĆ©rez-Villar, Ɓlvaro GarcĆ­a-MartĆ­n, JesĆŗs BescĆ³s, Marcos EscuderoViƱolo: ā€œSpacecraft Pose Estimation: Robust 2D and 3D-Structural Losses and
Unsupervised Domain Adaptation by Inter-Model Consensusā€. IEEE Transactions on
Aerospace and Electronic Systems. August 2023.

10. Javier Montalvo, Ɓlvaro GarcĆ­a-MartĆ­n, JosĆ© M. Martinez. “An Image-Processing Toolkit
for Remote Photoplethysmography”, Multimedia Tools and Applications. July 2024.

11. Juan Ignacio Bravo PĆ©rez-Villar, Ɓlvaro GarcĆ­a-MartĆ­n, JesĆŗs BescĆ³s, Juan C. SanMiguel:
ā€œTest-Time Adaptation for Keypoint-Based Spacecraft Pose Estimation Based on
Predicted-View Synthesisā€. IEEE Transactions on Aerospace and Electronic Systems.
May 2024.

12. Kirill Sirotkin, Marcos Escudero-ViƱolo, Pablo Carballeira, Ɓlvaro Garcƭa-Martƭn:
ā€œImproved Transferability of Self-Supervised Learning Models Through Batch
Normalization Finetuningā€. Applied Intelligence. Aug 2024.

13. Javier GalƔn, Miguel GonzƔlez, Paula Moral, Ɓlvaro Garcƭa-Martƭn, Jose M. Martinez:
ā€œTransforming Urban Waste Collection Inventory: AI-Based Container Classification and
Re-Identificationā€. Waste Management, Feb 2025.

Gerardo Fernandez | Eye tracking | Excellence in Innovation

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Dr. Gerardo Fernandez | Eye tracking | Excellence in Innovation

Gerardo Abel FernĆ”ndez šŸ‡¦šŸ‡·, born on October 29, 1976, in BahĆ­a Blanca, Argentina, is a researcher specializing in neuroscience and cognitive science šŸ§ . He is a professor and adjunct researcher at CONICET, focusing on eye movement-based biomarkers for neurodegenerative diseases šŸ‘€. His work integrates philosophy, cognitive psychology, and technology to advance Alzheimerā€™s diagnosis šŸ„.

Profile

Education šŸŽ“

šŸŽ“ Gerardo Abel FernĆ”ndez 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 Alzheimerā€™s biomarkers. His expertise in cognitive science and technological innovation has led to the development of diagnostic tools for early neurodegenerative disease detection. šŸ“ššŸ”šŸ§ 

Experience šŸ‘Øā€šŸ«

šŸ’¼ Dr. Gerardo Abel FernĆ”ndez has extensive experience in neuroscience research and technological innovation. He served as a Professor of Audiovisual Language at UNS (2011ā€“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 Alzheimerā€™s disease. Dr. FernĆ”ndez is also a scientific reviewer for prestigious journals like PlosOne, Journal of Alzheimerā€™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. šŸ…šŸ”¬šŸ‘ļø

Research Interests šŸ”¬

šŸ”¬ Dr. Gerardo Abel FernĆ”ndez specializes in cognitive neuroscience, neurodegenerative disease biomarkers, and eye-tracking technology. His research focuses on early Alzheimerā€™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 Alzheimerā€™s disease. His patented eye-tracking system has clinical applications in detecting mild cognitive impairment and Alzheimerā€™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. šŸ§ šŸ‘ļøšŸ“Š

Awards & Recognitions šŸ…

šŸ† Dr. Gerardo Abel FernĆ”ndez has received numerous awards for his contributions to neuroscience, cognitive evaluation, and Alzheimerā€™s diagnostics. His eye-tracking research for Alzheimerā€™s detection earned the Dr. JosĆ© 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 DĆ¼sseldorf. His research and patented cognitive evaluation equipment have been acknowledged by ANMAT (Argentinaā€™s National Administration of Drugs, Foods, and Medical Technology) and INPI (Argentinaā€™s National Patent Office). Dr. FernĆ”ndez’s groundbreaking innovations in neurocognitive assessments have positioned him as a leading figure in technological advancements for early Alzheimerā€™s detection. šŸ…šŸ§ šŸ”¬

Publications šŸ“š

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

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

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

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

  • Microsaccadic behavior when developing a complex dynamical activity

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

    EID:

    2-s2.0-85053731401