Sikandar Ali | Artificial Intelligence Award | Best Researcher Award

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Dr. Sikandar Ali | Artificial Intelligence Award | Best Researcher Award

Postdoc Fellow, Inje University, South Korea

🎓 Sikandar Ali is a passionate AI researcher and educator specializing in Artificial Intelligence applications in healthcare. Currently pursuing a PhD at Inje University, South Korea, he has a strong academic background and extensive research experience in digital pathology, medical imaging, and machine learning. As a team leader of the digital pathology project, he develops innovative AI algorithms for cancer diagnosis while collaborating with a global team of researchers. Sikandar is a recipient of prestigious scholarships, accolades, and recognition for his contributions to AI and healthcare innovation.

Publication Profile

Google Scholar

Education

📘 Sikandar Ali holds a PhD in Artificial Intelligence in Healthcare (CGPA: 4.46/4.5) from Inje University, South Korea, where his thesis focuses on integrating pathology foundation models with weakly supervised learning for gastric and breast cancer diagnosis. He earned an MS in Computer Science from Chungbuk National University, South Korea (GPA: 4.35/4.5), with research on AI-based clinical decision support systems for cardiovascular diseases. His undergraduate degree is a Bachelor of Engineering in Computer Systems Engineering from Mehran University of Engineering and Technology, Pakistan, with a CGPA of 3.5/4.0.

Experience

💻 Sikandar is an experienced researcher and AI specialist. Currently working as an AI Research Assistant at Inje University, he focuses on cutting-edge projects in digital pathology, cancer detection, and medical imaging. Previously, he worked as a Research Assistant at Chungbuk National University, focusing on cardiovascular disease diagnosis using AI. His industry experience includes roles such as Search Expert at PROGOS Tech Company and Software Developer Intern at Hidaya Institute of Science and Technology.

Awards and Honors

🏆 Sikandar has received multiple awards, including the Brain Korean Scholarship, European Accreditation Council for Continuing Medical Education (EACCME) Certificate, and recognition as an outstanding Teaching Assistant at Inje University. He has also earned full travel grants for international conferences, extra allowances for R&D industry projects, and certificates for reviewing research papers in leading journals. Additionally, he is a Guest Editor at Frontiers in Digital Health.

Research Focus

🔬 Sikandar’s research focuses on developing AI algorithms for medical imaging, with expertise in weakly supervised learning, self-supervised learning, and digital pathology. His projects include designing AI systems for cancer detection, COVID-19 prediction, and IPF severity classification. He also works on object detection applications using YOLO models and wearable sensor-based activity detection for pets. His commitment to explainability and interpretability in AI models ensures their practical utility in healthcare.

Conclusion

🌟 Sikandar Ali is a dedicated AI researcher driving innovation in healthcare through artificial intelligence. With his strong educational foundation, diverse research experience, and impactful contributions, he aims to bridge the gap between AI and medicine, making healthcare more efficient and accessible.

Publications

Detection of COVID-19 in X-ray Images Using DCSCNN
Sensors 2022, IF: 3.4

A Soft Voting Ensemble-Based Model for IPF Severity Prediction
Life 2021, IF: 3.2

Metaverse in Healthcare Integrated with Explainable AI and Blockchain
Sensors 2023, IF: 3.4

Weakly Supervised Learning for Gastric Cancer Classification Using WSIs
Springer 2023

Classifying Gastric Cancer Stages with Deep Semantic and Texture Features
ICACT 2024

Computer Vision-Based Military Tank Recognition Using YOLO Framework
ICAISC 2023

Activity Detection for Dog Well-being Using Wearable Sensors
IEEE Access 2022

Cat Activity Monitoring Using Wearable Sensors
IEEE Sensors Journal 2023, IF: 4.3

Deep Learning for Algae Species Detection Using Microscopic Images
Water 2022, IF: 2.9

Comprehensive Review on Multiple Instance Learning
Electronics 2023

Hybrid Model for Face Shape Classification Using Ensemble Methods
Springer 2021

Cervical Spine Fracture Detection Using Two-Stage Deep Learning
IEEE Access 2024

 

Carolina Magalhães | Machine Learning | Best Researcher Award

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Dr. Carolina Magalhães | Machine Learning | Best Researcher Award

Investigadora, INEGI – Instituto de Ciência e Inovação em Engenharia Mecânica e Industrial, Portugal

👩‍🔬 Carolina Magalhães is a dedicated biomedical engineer and PhD candidate with expertise in applying AI and imaging technologies to healthcare challenges. Based in Porto, Portugal, she combines her passion for modern technology with a problem-solving mindset to develop innovative solutions in skin cancer diagnostics. Carolina has worked collaboratively with clinical experts to bridge research and practical applications, contributing significantly to advancing imaging-based decision support systems.

Publication Profile

ORCID

Education

🎓 Carolina holds a PhD in Biomedical Engineering from the Faculdade de Engenharia da Universidade do Porto (2020–2024). She also completed her MSc in Biomedical Engineering at the same institution (2016–2018) and earned her Bachelor’s in Bioengineering – Biomedical Engineering from Universidade Católica Portuguesa (2013–2016).

Experience

💼 Carolina has a rich research background, currently serving as a Graduate Research Fellow at INEGI, focusing on skin lesion diagnosis using multispectral imaging. Her work spans from leveraging machine learning models for skin cancer classification to thermal and UV imaging techniques. Previously, she contributed to projects on hyperhidrosis diagnosis, prosthetic device design, and thermal image analysis for musculoskeletal disorders, collaborating with leading hospitals and research centers in Portugal.

Research Interests

🔬 Carolina is passionate about exploring artificial intelligence, machine learning, and advanced imaging technologies for healthcare applications. Her interests include developing multispectral imaging systems, improving diagnostic tools for skin cancer, and advancing infrared thermography for clinical support systems.

Awards

🏆 Carolina’s innovative work has been recognized with prestigious research grants from the Foundation for Science and Technology (SFRH/BD/144906/2019) and other funding organizations. These awards have supported her impactful contributions to biomedical engineering and healthcare innovation.

Publications

“Systematic Review of Deep Learning Techniques in Skin Cancer Detection”
BioMedInformatics, 11/2024
Read here

“Skin Cancer Image Classification with Artificial Intelligence Strategies: A Systematic Review”
Journal of Imaging, 10/2024
Read here

“Use of Infrared Thermography for Abdominoplasty Procedures in Patients with Extensive Subcostal Scars: A Preliminary Analysis”
Plast Reconstr Surg Glob Open, 06/2023
Read here

“Classic Versus Scarpa-Sparing Abdominoplasty: An Infrared Thermographic Comparative Analysis”
J Plast Reconstr Aesthet Surg, 06/2023
Read here

“Towards an Effective Imaging-Based Decision Support System for Skin Cancer”
Handbook of Research on Applied Intelligence for Health and Clinical Informatics, 10/2022
Read here

Lourdes Swentek | Artificial Intelligence | Best Researcher Award

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Assist Prof Dr. Lourdes Swentek | Artificial Intelligence | Best Researcher Award

Academician/Research Scholar, UCI, United States

Dr. Lourdes Swentek is a highly accomplished trauma and critical care surgeon with extensive experience in surgical research and education. She completed her fellowship in Critical Care at the University of California, Irvine, and her residency in Surgery at Loma Linda University Health. Dr. Swentek has been recognized for her outstanding contributions to trauma and acute care surgery, earning numerous awards and accolades throughout her career. Her research interests focus on islet transplantation, oxidative stress in pancreatitis, and innovative surgical techniques.

Profile

Scopus

 

Education

🎓 Dr. Lourdes Swentek completed her Critical Care fellowship at the University of California, Irvine, and her Surgical Residency at Loma Linda University Health. She also served as a Research Resident in the Department of Surgery at the University of California, Irvine, where she focused on islet transplantation.

Experience

🔬 Dr. Lourdes Swentek’s professional journey includes a fellowship in Critical Care at the University of California, Irvine, and a surgical residency at Loma Linda University Health. She has significant research experience in islet transplantation and surgical innovation, having contributed to several impactful research projects and publications.

Research Interests

🧪 Dr. Lourdes Swentek’s research interests encompass islet transplantation, oxidative stress in pancreatitis, and the development of novel surgical techniques. Her work has contributed to advancing knowledge and improving practices in these areas, making a notable impact on the field of trauma and critical care surgery.

Awards

🏆 Dr. Lourdes Swentek has received numerous awards, including the East Oriens Award for her career in Trauma and Acute Care Surgery in 2018, the Highest Resident Absite Score at Loma Linda University Health in 2017, and the UCI School of Medicine Achievement Award for Clinical Science Lecturer in 2022. These accolades reflect her dedication and excellence in her field.

Publications

The Addition of a Nurse Practitioner to an Inpatient Surgical Team Results in Improved Utilization of Resources

Medium and Long-term Outcomes after Pneumatic Dilation or Laparoscopic Heller Myotomy for Achalasia: A Meta-analysis

Presentation, Diagnosis, and Treatment of Oesophageal Motility Disorders

Role of Oxidative Stress in the Pathogenesis of Pancreatitis: Effect of Antioxidant Therapy

Total Pancreatectomy and Islet Auto Transplantation for Chronic Pancreatitis