Postdoc, Perk Lab Perk Lab Laboratory for Percutaneous Surgery, Canada

🎓 Gabriella d’Albenzio is a talented researcher with a focus on biomedical engineering and medical imaging. Currently pursuing a Ph.D. in Informatics at the University of Oslo, she has an impressive background in clinical engineering and biomedical engineering. Gabriella has worked on cutting-edge projects related to image-guided therapies and deep learning for medical applications, contributing significantly to her field through both research and development.

Profile

Scopus

Education

📚 Gabriella d’Albenzio holds a Ph.D. in Informatics from the University of Oslo (2021-2024). She completed her M.Sc. in Biomedical Engineering and B.Sc. in Clinical Engineering at Sapienza University of Rome, Italy, reflecting a solid foundation in both engineering and medical sciences.

Experience

💼 Gabriella d’Albenzio has extensive experience as a Scientific Software Developer at The Intervention Centre in Oslo, Norway, and as a Research Assistant at NTNU. She has also interned at the Rehabilitation Bioengineering Lab in Rome, contributing to various research projects involving advanced medical imaging and deep learning technologies.

Research Interests

🧠 Gabriella’s research interests are centered around enhancing surgical planning and medical imaging through deep learning and advanced computational techniques. Her work focuses on developing algorithms for medical image segmentation and predictive models for surgical outcomes, aiming to improve patient-specific treatment strategies.

Awards

🏅 Gabriella d’Albenzio has been recognized with the Globalink Research Internship by Mitacs, Canada, and a Grant Research Stay Abroad by The Research Council of Norway. These awards highlight her outstanding contributions to research and her commitment to advancing biomedical engineering.

Publications

Optimizing Surgical Plans for Parenchyma-Sparing Liver Resections through Contour-Guided Resection and Surface Approximation

Using NURBS for Virtual Resections in Liver Surgery Planning: A Comparative Usability Study

Patient-Specific Functional Liver Segments Based on Centerline Classification of the Hepatic and Portal Veins

ALive: Analytics for Computation and Visualization of Liver Resections

Laparoscopic Parenchyma-Sparing Liver Resection for Large (≥50 mm) Colorectal Metastases

Lourdes Swentek | Artificial Intelligence | Best Researcher Award

Posted on 25/07/202425/07/2024 by Computer Scientists Awards

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

Ao Guo | Artificial Intelligence | Best Researcher Award

Posted on 22/07/202423/07/2024 by Computer Scientists Awards

Mr. Ao Guo | Artificial Intelligence | Best Researcher Award

Master’s student, Xinjiang University, China

📚 Ao Guo is a dedicated postgraduate researcher at Xinjiang University with a focus on the innovation, optimization, and application of object detection technology. Currently pursuing a master’s degree in Electronic Information, Ao Guo has a robust background in computer vision, deep learning, pattern recognition, and image processing. He is committed to enhancing the accuracy and efficiency of object detection algorithms, contributing to both academia and industry.

Profile

Google Scholar

Education

🎓 Master’s Degree in Electronic Information – Xinjiang University, Urumqi, China
Ao Guo is advancing his studies in Electronic Information, focusing on the intersection of computer vision and deep learning to address real-world problems.

Experience

Ao Guo has been deeply involved in research aimed at optimizing deep learning models for intelligent weed management in agricultural environments. His work on a lightweight weed detection model, which incorporates global contextual features, is recognized for its high detection speed and accuracy, particularly suited for resource-constrained edge devices.

Research Interests

Ao Guo’s research interests encompass weed detection, deep learning, YOLO (You Only Look Once) models, attention mechanisms, and the development of lightweight networks. His innovative approach to integrating global information capture mechanisms into detection algorithms stands out in his field.

Awards

Ao Guo’s contributions to the field have been acknowledged through his publications and patent. Notably, he has published a paper in the highly reputed journal “Engineering Applications of Artificial Intelligence,” and he holds a patent for a lightweight weed detection method and device.

Publications

A lightweight weed detection model with global contextual joint features. Engineering Applications of Artificial Intelligence, 136, 108903. Link – Cited by: Article on Engineering Applications of Artificial Intelligence.

Xiaohui Huang | Artificial Intelligence| Best Researcher Award

Posted on 20/07/202420/07/2024 by Computer Scientists Awards

Assoc Prof Dr. Xiaohui Huang | Artificial Intelligence| Best Researcher Award

Dean, East China jiaotong university, Japan

👨‍🏫 Dr. Xiaohui Huang is an Associate Professor at the School of Information Engineering, East China Jiaotong University. He earned his PhD from the School of Computer Science, Harbin Institute of Technology in November 2014. He has been a visiting scholar at the German Cancer Research Center and Nanyang Technological University. Dr. Huang has been leading several high-impact research projects funded by national and provincial bodies. He is an expert reviewer for various prestigious journals and a member of notable academic associations.

Profile

Scopus

Education

🎓 PhD in Computer Science, Harbin Institute of Technology, November 2014, German Cancer Research Center, December 2010 – October 2011, School of Computer Science and Engineering, Nanyang Technological University, November 2017 – November 2018

Experience

💼 Associate Professor, School of Information Engineering, East China Jiaotong University, January 2018 – Present
Lecturer, School of Information Engineering, East China Jiaotong University, December 2014 – December 2017
Visiting Scholar, Nuclear Medicine Research Group, German Cancer Research Center, December 2010 – October 2011
Software Engineer, Yichun Branch, China Telecom, August 2008 – February 2010

🔬 Research Interests

Deep Learning. Remote Image Analysis. Intelligent Transportation

🏆 Awards

Principal Investigator for various prestigious research projects including the National Natural Science Foundation of China and Jiangxi Province Natural Science Foundation.

Publications

Multi-view dynamic graph convolution neural network for traffic flow prediction. Expert Systems With Applications, 2023 (SCI Zone 1 top)
Cited by: 15 articles

MAPredRNN: Multi-attention predictive RNN for traffic flow prediction by dynamic spatio-temporal data fusion. Applied Intelligence, 2023 (SCI Zone 2)
Cited by: 10 articles

SS-TMNet: Spatial–Spectral Transformer Network with Multi-Scale Convolution for Hyperspectral Image Classification. Remote Sensing, 2023 (SCI Zone 2, top)
Cited by: 8 articles

Multi-mode dynamic residual graph convolution network for traffic flow prediction. Information Sciences, 2022 (SCI Zone 1 top)
Cited by: 20 articles

A time-dependent attention convolutional LSTM method for traffic flow prediction.

JAINUL FATHIMA | Artificial Intelligence | Best Researcher Award

Posted on 26/06/202426/06/2024 by Computer Scientists Awards

Dr. JAINUL FATHIMA | Artificial Intelligence | Best Researcher Award

Associate Professor, Francis Xavier Engineering College, India

📘 Dr. A. Jainul Fathima, B.Tech., M.E., Ph.D., is an innovative professor with a strong passion for fostering academic development and success for every student. With 12 years of combined experience in teaching, research, and industry, she excels in implementing technology-based curriculum delivery and assessment tools.

Profile

Scopus

Education🎓

Dr. Fathima holds a Ph.D. in Computational Drug Discovery from Kalasalingam Academy of Research and Education, where her interdisciplinary research focused on developing anti-viral drugs for dengue targets using AI techniques. She earned her M.E. in Computer Science and Engineering from Anna University with an 83% aggregate and a B.Tech. in Information Technology from Anna University with a 75% aggregate.

Experience 🛠️

👩‍🏫 With 12 years of total experience, Dr. Fathima has 6 years of teaching experience, currently serving as an Assistant Professor at Francis Xavier Engineering College. She has previously worked at K.L.N. College of Information Technology, Sethu Institute of Technology, and Kalasalingam University. Her research experience includes 3 years as a UGC Research Fellow and 2 years of teaching and instructing in Qatar. She also has 1 year of industrial experience as a Research Assistant in Computer-Aided Drug Design.

Research Interests 🔍

🔬 Dr. Fathima’s research interests are in the areas of computational drug discovery, machine learning, artificial intelligence, and bioinformatics. Her work focuses on applying advanced computational techniques to predict protein interactions and develop therapeutic solutions for diseases like dengue and Alzheimer’s.

Awards 🏆

🏆 Dr. Fathima has received several accolades, including the “Research Associate Award” from the Anti-viral Research Society in 2022, “Best Paper Award” at INCODS ’17 and NCAC ’09, and the “Outstanding Student Award” from Mepco Schlenk Engineering College.

Publications 📚

A comprehensive review on heart disease prognostication using different artificial intelligence algorithms, Computer Methods in Biomechanics and Biomedical Engineering, February 2024. Cited by 1.5

Alzheimer’s Patients Detection using Support Vector Machine (SVM) with Quantitative Analysis, Neuroscience Informatics, 2021. Cited by 0.5

IoT-Based Intelligent System for Garbage Level Monitoring in Smart Cities, International Conference on IoT, Communication and Automation Technology, 2023. Scopus Indexed

Intelligent Deep Learning Framework for Breast Cancer Prediction using Feature Ensemble Learning, IEEE Global Conference for Advancement in Technology, 2023. Scopus Indexed

Compressing Biosignal for diagnosing chronic diseases, Journal of Physics: Conference Series, 2021. Scopus Indexed