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 👨‍🏫

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 García Martín es Profesor Titular en la Universidad Autónoma de Madrid, especializado en visión por computadora y análisis de video. 🎓 Obtuvo su título de Ingeniero de Telecomunicación en 2007, su Máster en Ingeniería Informática y Telecomunicaciones en 2009 y su Doctorado en 2013, todos en la Universidad Autónoma de Madrid. 🏫 Ha trabajado en detección de personas, seguimiento de objetos y reconocimiento de eventos, con más de 22 artículos en revistas indexadas y 28 en congresos. 📝 Ha realizado estancias en Carnegie Mellon University, Queen Mary University y Technical University of Berlin. 🌍 Su investigación ha contribuido al desarrollo de sistemas de videovigilancia inteligentes, análisis de secuencias de video y procesamiento de señales multimedia. 📹 Ha sido reconocido con prestigiosos premios y ha participado en múltiples proyectos europeos de innovación tecnológica. 🚀

Profile

Education 🎓

🎓 Ingeniero de Telecomunicación por la Universidad Autónoma de Madrid (2007). 🎓 Máster en Ingeniería Informática y Telecomunicaciones con especialización en Tratamiento de Señales Multimedia en la Universidad Autónoma de Madrid (2009). 🎓 Doctor en Ingeniería Informática y Telecomunicación por la Universidad Autónoma de Madrid (2013). Su formación 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, recibió la beca FPI-UAM para la realización de su investigación. Su sólida formación académica le ha permitido contribuir significativamente al campo del análisis de video y visión por computadora, consolidándose como un experto en la detección, seguimiento y reconocimiento de eventos en secuencias de video. 📹

Experience 👨‍🏫

🔬 Se unió al grupo VPU-Lab en la Universidad Autónoma de Madrid en 2007. 📡 De 2008 a 2012, fue becario de investigación (FPI-UAM). 🎓 Entre 2012 y 2014, trabajó como Profesor Ayudante. 👨‍🏫 De 2014 a 2019, fue Profesor Ayudante Doctor. 📚 De 2019 a 2023, ocupó el cargo de Profesor Contratado Doctor. 🏛️ Desde septiembre de 2023, es Profesor Titular en la Universidad Autónoma de Madrid. 🏆 Ha participado en múltiples proyectos europeos sobre videovigilancia, transmisión de contenido multimedia y reconocimiento de eventos, incluyendo PROMULTIDIS, ATI@SHIVA, EVENTVIDEO y MobiNetVideo. 🚀 Ha realizado estancias de investigación en Carnegie Mellon University, Queen Mary University y Technical University of Berlin. 🌍 Su experiencia docente abarca asignaturas en Ingeniería de Telecomunicaciones, Ingeniería Informática e Ingeniería Biomédica.

Research Interests 🔬

🎯 Su investigación se centra en la visión por computadora, el análisis de secuencias de video y la inteligencia artificial aplicada a entornos de videovigilancia. 📹 Especialista en detección de personas, seguimiento de objetos y reconocimiento de eventos en video. 🧠 Desarrolla algoritmos de aprendizaje profundo y visión artificial para mejorar la seguridad y automatización en ciudades inteligentes. 🏙️ Ha trabajado en proyectos sobre videovigilancia, transmisión multimedia y detección de anomalías en video. 🔬 Su investigación incluye procesamiento de imágenes, análisis semántico 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, consolidándose como un referente en el campo de la visión por computadora. 📜

Awards & Recognitions 🏅

🥇 Medalla “Juan López de Peñalver” 2017, otorgada por la Real Academia de Ingeniería. 📜 Reconocimiento por su contribución a la ingeniería española en el campo de la visión por computadora y análisis de video. 🏛️ Ha recibido financiación para múltiples proyectos de investigación europeos y nacionales. 🔬 Ha participado en iniciativas de innovación en videovigilancia y análisis de video para seguridad. 🚀 Sus contribuciones han sido publicadas en las principales conferencias y revistas científicas del área. 📚 Su trabajo ha sido citado más de 4500 veces y cuenta con un índice 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 López-Cifuentes, Marcos Escudero-Viñolo, Jesús Bescós and Álvaro GarcíaMartín: “Semantic-Aware Scene Recognition”. Pattern Recognition. Accepted February
2020.

5. Paula Moral, Álvaro García-Martín, Marcos Escudero Viñolo, Jose M. Martinez, Jesus
Bescós, 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 Pérez-Villar, Álvaro García-Martín, Jesús Bescós, 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 García-Martín, José M. Martinez. “An Image-Processing Toolkit
for Remote Photoplethysmography”, Multimedia Tools and Applications. July 2024.

11. Juan Ignacio Bravo Pérez-Villar, Álvaro García-Martín, Jesús Bescós, 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 Galán, Miguel González, Paula Moral, Álvaro García-Martín, Jose M. Martinez:
“Transforming Urban Waste Collection Inventory: AI-Based Container Classification and
Re-Identification”. Waste Management, Feb 2025.

Mudassar Raza | Machine Learning | Best Researcher Award

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Prof. Mudassar Raza | Machine Learning | Best Researcher Award

Prof. Dr. Mudassar Raza is a leading AI researcher and academician, serving as a Professor at Namal University, Mianwali, Pakistan. He is a Senior IEEE Member, Chair Publications of IEEE Islamabad Section, and an Academic Editor for PLOS ONE. With 20+ years of teaching and research experience, he has worked at HITEC University Taxila and COMSATS University Islamabad. His research spans AI, deep learning, image processing, and cybersecurity. He has published 135+ research papers with a cumulative impact factor of 215+, 6066+ citations, an H-index of 44, and an I-10 index of 93. He was listed in Elsevier’s World’s Top 2% Scientists (2023) and ranked #11 in Computer Science in Pakistan. Dr. Raza has supervised 3 PhDs, co-supervising 6 more, and mentored 100+ undergraduate R&D projects. He actively contributes to academia, industry collaborations, and curriculum development while serving as a reviewer for prestigious journals. 🌍📖

Profile

Education 🎓

  • Ph.D. in Control Science & Engineering (2014-2017) – University of Science & Technology of China (USTC), China 🇨🇳
    • Specialization: Pattern Recognition & Intelligent Systems
  • MS (Computer Science) (2009-2010) – Iqra University, Islamabad, Pakistan 🇵🇰
    • CGPA: 3.64 | Specialization: Image Processing
  • MCS (Master of Computer Science) (2004-2006) – COMSATS Institute of Information Technology, Pakistan
    • CGPA: 3.24 | 80% Marks
  • BCS (Bachelor in Computer Science) (1999-2003) – Punjab University, Lahore, Pakistan
    • CGPA: 3.28 | 64.25% Marks
  • Higher Secondary (Pre-Engineering) – Islamabad College for Boys
  • Matriculation (Science) – Islamabad College for Boys
    Dr. Raza’s academic journey is marked by top-tier universities and a strong focus on AI, pattern recognition, and cybersecurity. 🎓📚

Experience 👨‍🏫

  • Professor (2024-Present) – Namal University, Mianwali
    • Teaching AI, Cybersecurity, and Research Supervision
  • Associate Professor/Head AI & Cybersecurity Program (2023-2024) – HITEC University, Taxila
    • Led AI & Cybersecurity programs, supervised PhDs, and organized industry-academic collaborations
  • Associate Professor (2023) – COMSATS University, Islamabad
  • Assistant Professor (2012-2023) – COMSATS University, Islamabad
  • Lecturer (2008-2012) – COMSATS University, Islamabad
  • Research Associate (2006-2008) – COMSATS University, Islamabad
    Dr. Raza has 20+ years of experience in academia, R&D, and industry collaborations, contributing significantly to AI, deep learning, and cybersecurity. 🏫📊

Research Interests 🔬

Prof. Dr. Mudassar Raza’s research revolves around Artificial Intelligence, Deep Learning, Computer Vision, Image Processing, Cybersecurity, and Parallel Programming. His work includes pattern recognition, intelligent systems, visual robotics, and AI-driven cybersecurity solutions. With 135+ international publications, he has significantly contributed to AI’s real-world applications. His research impact includes 6066+ citations, an H-index of 44, and an I-10 index of 93. He leads multiple AI research groups, supervises PhD/MS students, and actively collaborates with industry and academia. His work is frequently cited, placing him among the top AI researchers globally. As an IEEE Senior Member and a PLOS ONE Academic Editor, he is a key figure in AI-driven innovations and technology advancements. 🧠📊

  • National Youth Award 2008 by the Prime Minister of Pakistan for contributions to Computer Science 🎖️
  • Listed in World’s Top 2% Scientists (2023) by Elsevier 🌍
  • Ranked #11 in Computer Science in Pakistan by AD Scientific Index 📊
  • Senior IEEE Member (ID: 91289691) 🔬
  • HEC Approved PhD Supervisor 🎓
  • Best Research Productivity Awardee at COMSATS University multiple times 🏆
  • Recognized by ResearchGate with a Research Interest Score higher than 97% of members 📈
  • Reviewer & Editor for prestigious journals including PLOS ONE 📝
    Dr. Raza has received numerous accolades for his contributions to AI, research excellence, and academia. 🌟

Publications 📚

Yangyang Huang | Object detection | Excellence in Innovation

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Dr. Yangyang Huang | Object detection | Excellence in Innovation

Yangyang Huang is a Ph.D. student at the School of Computer Science and Engineering, South China University of Technology (SCUT), Guangzhou, China. His research focuses on artificial intelligence, computer vision, and large models. He previously graduated from Wuhan University, where he developed a strong foundation in AI and computational sciences. Yangyang has contributed to significant research projects, including the Collaborative Innovation Major Project for Industry, University, and Research. His work, “LVMUM: Toward Open-World Object Detection with Large Vision Models and Unsupervised Modeling,” has gained notable citations. Passionate about AI advancements, he actively participates in academic collaborations and professional memberships, contributing to AI-driven innovations.

Profile

Education 🎓

Yangyang Huang completed his undergraduate studies at Wuhan University, where he gained expertise in artificial intelligence and computational sciences. Currently, he is pursuing his Ph.D. at the School of Computer Science and Engineering, South China University of Technology (SCUT), Guangzhou, China. His doctoral research focuses on large vision models, unsupervised modeling, and object detection. He has been involved in cutting-edge AI research, particularly in deep learning and computer vision. His academic journey has been marked by significant contributions to AI-driven innovations, leading to multiple publications in high-impact journals. Yangyang actively collaborates with researchers in academia and industry, further strengthening his expertise in AI and machine learning applications.

Experience 👨‍🏫

Yangyang Huang has extensive research experience in artificial intelligence, computer vision, and large models. As a Ph.D. student at SCUT, he has been involved in the Collaborative Innovation Major Project for Industry, University, and Research. His research contributions include developing large vision models for open-world object detection, leading to highly cited publications. Yangyang has also participated in consultancy and industry projects, applying AI techniques to real-world problems. He has authored several journal articles indexed in SCI and Scopus and has contributed to the academic community through editorial roles. His collaborative research efforts have led to impactful AI advancements, making him a rising scholar in the field of AI and machine learning.

Research Interests 🔬

Yangyang Huang’s research primarily focuses on artificial intelligence, computer vision, and large models. His recent work, “LVMUM: Toward Open-World Object Detection with Large Vision Models and Unsupervised Modeling,” explores novel AI techniques for enhancing object detection capabilities. He specializes in deep learning, unsupervised learning, and AI-driven automation. His research interests include developing robust AI models for real-world applications, advancing AI ethics, and improving AI interpretability. Yangyang actively collaborates with academia and industry to bridge the gap between theoretical AI research and practical applications. His contributions extend to consultancy projects, AI innovation, and scholarly publications, making him a key contributor to AI advancements. 🚀

Awards & Recognitions 🏅

Yangyang Huang has received recognition for his outstanding contributions to artificial intelligence and computer vision. His research on large vision models and open-world object detection has been widely cited, earning him academic recognition. He has been nominated for prestigious research awards, including Best Researcher Award and Excellence in Research. His work in AI has been acknowledged through various grants and funding for industry-academic collaborative projects. Yangyang’s active participation in international conferences has led to best paper nominations and accolades for his innovative contributions. He is a member of esteemed professional organizations, further cementing his reputation as an emerging AI researcher.

Publications 📚

Raveendra Pilli | Image Processing | Best Researcher Award

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Mr. Raveendra Pilli | Image Processing | Best Researcher Award

He mentored B.Tech. projects focused on the early detection of Alzheimer’s Disease. One project involved utilizing multi-modality neuroimaging techniques, where MRI and PET images were collected from the OASIS database, preprocessed, and robust features were extracted for classification. MATLAB and the SPM-12 toolbox were used for this task. Another project focused on the early detection of Alzheimer’s Disease using deep learning networks, where an MRI dataset from the ADNI database was collected, preprocessed, and the performance was compared with baseline algorithms. For this project, he used MATLAB and Python.

NIT-Silchar, India

Profile

Education

A dedicated research scholar with a Ph.D. in Electronics and Communication Engineering from the National Institute of Technology Silchar (Thesis Submitted, CGPA 9.0), specializing in brain age prediction and early detection of neurological disorders using neuroimaging modalities. With extensive teaching experience, a strong passion for research, and a proven ability to develop engaging curricula, deliver effective lectures, and guide students toward academic success, I am committed to contributing to the field through research, publications, and presentations. My academic journey includes an M.Tech. from JNTU Kakinada (76.00%, 2011) and a B.Tech. from JNTU Hyderabad (65.00%, 2007), along with a strong foundational background in science, having completed 10+2 (MPC) with 89.00% in 2003 and SSC with 78.00% in 2001.

Work experience

He worked as a Junior Research Fellow at the National Institute of Technology, Silchar, Assam, from July 2021 to June 2023, where he assisted professors with course delivery for Basic Electronics, conducted laboratory sessions, graded assignments, and provided office hours for student support. From July 2023 to December 2024, he served as a Senior Research Fellow at the same institute, taking on additional responsibilities, including mentoring B.Tech. projects and assisting with Digital Signal Processing laboratory duties. Prior to his research roles, he was an Assistant Professor at SRK College of Engineering and Technology, Vijayawada, Andhra Pradesh, where he taught courses such as Networks Theory, Digital Signal Processing, RVSP, SS, and LICA. He utilized innovative teaching methods, including active learning techniques, to enhance student engagement and learning outcomes. He also mentored undergraduate research projects in image processing and received positive student evaluations for his teaching effectiveness.

Publication

Nuo Yu | Radiomics | Best Researcher Award

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Ms. Nuo Yu | Radiomics | Best Researcher Award

Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College ,China

Nuo Yu is a Ph.D. candidate at the Cancer Institute and Hospital of the Chinese Academy of Medical Sciences, specializing in radiation oncology with a focus on esophageal squamous cell carcinoma (ESCC). His research primarily explores innovative chemoradiotherapy regimens to improve treatment outcomes for patients with locally advanced ESCC.

Yu has contributed to several peer-reviewed publications in SCI-indexed journals. Notably, he co-authored a study titled “Conversion Chemoradiotherapy Combined with Nab-Paclitaxel Plus Cisplatin in Patients with Locally Advanced Borderline-Resectable or Unresectable Esophageal Squamous Cell Carcinoma: A Phase I/II Prospective Cohort Study,” published in Strahlentherapie und Onkologie in August 2024. This research evaluated the efficacy and safety of a novel chemoradiotherapy regimen, demonstrating promising results in locoregional control and overall survival rates.

In March 2023, Yu co-authored another significant study, “Efficacy and Safety of Concurrent Chemoradiotherapy Combined with Nimotuzumab in Elderly Patients with Esophageal Squamous Cell Carcinoma: A Prospective Real-world Pragmatic Study,” published in Current Cancer Drug Targets. This research focused on treatment strategies for elderly patients with ESCC, highlighting the potential benefits of combining chemoradiotherapy with nimotuzumab.

Yu’s work has been recognized at international conferences, including presentations at the American Society for Radiation Oncology (ASTRO), the Federation of Asian Organizations for Radiation Oncology (FARO), and the Korean Society for Radiation Oncology (KOSRO). These engagements underscore his active participation in the global radiation oncology community and his commitment to advancing cancer treatment research.

While still in the early stages of his career, Yu’s focused research on ESCC and his contributions to the field of radiation oncology position him as a promising candidate for the Best Researcher Award. Continued efforts to expand his research scope, increase publication impact, and assume leadership roles in larger-scale studies will further strengthen his candidacy.

Profile

Scientific Publications