Ms. Leiyao Liao | Deep Learning Awards | Best Researcher Award

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Ms. Leiyao Liao | Deep Learning Awards | Best Researcher Award

Ms. Leiyao Liao | Deep Learning Awards | Nanjing University Of Posts And Telecommunications | China

Ms. Leiyao Liao is a distinguished researcher and lecturer at the School of Communication and Information Engineering, Nanjing University of Posts and Telecommunications, renowned for her contributions to synthetic aperture radar (SAR) image understanding, target recognition, and explainable deep learning. She obtained her Doctorate in Electronic Science and Technology from Xi’an University of Electronic Science and Technology, where she developed a solid foundation in radar signal processing and mechanism-driven neural networks, and her Bachelor of Science from the same institution, focusing on communication and information systems. In her professional career, Ms. Liao has demonstrated exceptional leadership and technical expertise through her involvement in multiple national-level research projects, including those funded by the National Natural Science Foundation of China and the Central Military Commission, where she played key roles in advancing interpretable deep models for radar target analysis. Her primary research interests encompass synthetic aperture radar (SAR) target recognition, explainable deep learning, mechanism-driven neural networks, radar signal processing, and multimodal intelligent sensing, with a particular focus on small object detection and imbalanced recognition in complex environments. Ms. Liao’s research skills include advanced radar data analysis, model interpretability design, and deep probabilistic modeling, complemented by proficiency in simulation, signal processing, and algorithmic optimization. Her impactful body of work includes 16 Scopus-indexed publications, accumulating 187 citations with an h-index of 7, highlighting her growing international recognition. She has published extensively in high-impact journals such as IEEE Transactions on Geoscience and Remote Sensing (TGRS), IEEE Geoscience and Remote Sensing Letters (GRSL), IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), and IEEE Journal of Selected Topics in Signal Processing (JSTSP). Ms. Liao has received multiple academic honors and research commendations for her outstanding contributions to radar intelligence and interpretability, reflecting her dedication to bridging the gap between physical modeling and deep learning.

Professional Profiles: Scopus

Featured Publications 

  1. Liao, L. (2025). Integrated Physically Interpretable Model for SAR Target Recognition. IEEE Geoscience and Remote Sensing Letters. (Citations: 26)

  2. Liao, L. (2025). Research on Collision Access Method for Satellite Internet of Things Based on Bayliss Window Function. Sensors (Basel, Switzerland). (Citations: 0)

  3. Liao, L. (2024). EMI-Net: Interpretable Deep Network for SAR Target Recognition. IEEE Transactions on Geoscience and Remote Sensing. (Citations: 41)

  4. Liao, L. (2024). Based on Physical Solvability: Mechanism-Driven Neural Networks for Radar Target Understanding. Journal of Electronics. (Citations: 18)

  5. Liao, L. (2022). Interpretable Deep Probabilistic Model for HRR Radar Signal and Its Application to Target Recognition. IEEE Journal of Selected Topics in Signal Processing. (Citations: 52)

  6. Liao, L. (2023). Fusion-Based Multimodal SAR Target Classification Using Explainable Deep Learning. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. (Citations: 29)

  7. Liao, L. (2023). Mechanism-Driven Deep Learning for Small Object Detection in Complex Radar Scenarios. IEEE Access. (Citations: 21)

Dr. Cristian Dan Pavel | Deep Learning | Best Research Article Award

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Dr. Cristian Dan Pavel | Deep Learning | Best Research Article Award 

Dr. Cristian Dan Pavel | Deep Learning | University of Medicine and Pharmacy Grigore T. Popa | Romania

Dr. Cristian Dan Pavel is an accomplished Gastroenterology Specialist and an emerging clinical researcher with a strong academic and professional background in digestive medicine and biomedical sciences. Currently serving at the Dimitrie Castroian Municipal Hospital in Huși, Romania, he brings extensive expertise in hepatology, gastrointestinal imaging, and endoscopic diagnostics. Dr. Cristian Dan Pavel is pursuing his Ph.D. in Histology at the “Grigore T. Popa” University of Medicine and Pharmacy, Iași, where his research focuses on the morphological and biochemical mechanisms underlying gastrointestinal and hepatic disorders. His doctoral work, under the supervision of Prof. Dr. Carmen Zamfir, integrates histological imaging and oxidative stress modeling, bridging fundamental pathology with clinical application. He holds an M.Sc. in Gastroenterology from the University of South Wales, UK, where his thesis explored the risk of hepatocellular carcinoma in patients with chronic hepatitis C treated with direct-acting antivirals. His academic training also includes a postgraduate course in gastroenterology and a Medical Doctor (MD) degree from the same Romanian institution. Professionally, Dr. Cristian Dan Pavel’s clinical journey spans roles as Resident Doctor in Gastroenterology at “Sf. Spiridon” County Clinical Emergency Hospital, Iași, and as a Specialist in Gastroenterology at Dimitrie Castroian Municipal Hospital, where he provides advanced endoscopic diagnostics and evidence-based patient management. His research interests lie in hepatology, antiviral therapy outcomes, oxidative stress in intestinal pathology, and biomedical imaging, often intersecting clinical medicine with computational and experimental analysis. Dr. Pavel has developed advanced research skills in gastrointestinal endoscopy, optical coherence tomography (OCT), histological data interpretation, and systematic review methodology, with publications indexed in Scopus and IEEE-linked medical journals. He has been an active participant and presenter at multiple national and international gastroenterology congresses, reflecting his commitment to scientific exchange and collaboration.

Professional Profiles: ORCID | Scopus 

Featured Publications 

  1. Pavel, C. D. (2024). Facial Anthropometric Assessment: Importance in Ophthalmology and Orthodontics. Citations: 33.

  2. Pavel, C. D. (2024). Variabilities in Retinal Hemodynamics Across the Menstrual Cycle in Healthy Women Identified Using Optical Coherence Tomography Angiography. Citations: 41.

  3. Pavel, C. D. (2023). Hybrid Deep Learning Models for Analyzing Histological Images of the Zebrafish Intestine Under Oxidative Stress. Citations: 29.

  4. Pavel, C. D. (2023). The Relevance of Experimental Models in Assessing the Impact of Oxidative Stress on Intestinal Pathology. Citations: 36.

  5. Pavel, C. D. (2022). Evaluating Fundoscopy as a Screening Tool for Optic Nerve Atrophy in Multiple Sclerosis: An Optical Coherence Tomography (OCT) Comparative Study. Citations: 42.

  6. Pavel, C. D. (2021). Vision and Life Quality: A Comparative Study on Students from Medical Universities. Citations: 27.

  7. Pavel, C. D. (2020). Computer Vision Syndrome: An Ophthalmic Pathology of the Modern Era. Citations: 39.