Prof Dr. Yunyoung Nam | Medical Image Analysis | Best Researcher Award

Publications

A Novel Approach for High-Resolution Coastal Areas and Land Use Recognition from Remote Sensing Images based on Multimodal Network-Level Fusion of SRAN3 and Lightweight Four Encoders ViT

  • Authors: M.K. Bhatti, Muhammad Kashif; M.A. Khan, Muhammad Attique; S. Shaheen, Saima; S.A. Algamdi, Shabbab Ali; Y. Nam, Yunyoung
    Journal: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
    Year: 2025

Analysis of Near-Fall Detection Method Utilizing Dynamic Motion Images and Transfer Learning

  • Authors: J. Kim, Jungyeon; N. Mat, Nab; C. Kim, Chomyong; S. Jeon, Seob; Y. Nam, Yunyoung
    Journal: IEEE Access
    Year: 2025

Cooperative PPG/ECG Wearable System for Atrial Fibrillation Diagnosis

  • Authors: Y. Lee, Yonbin; S. Lee, Soyoung; S. Kim, Sang-kyu; Y. Nam, Yunyoung; J. Lee, Jinseok
    Journal: IEEE Sensors Journal
    Year: 2025

Energy-Efficient Discrete Cosine Transform Architecture Using Reversible Logic for IoT-Enabled Consumer Electronics

  • Authors: M. Awais, Muhammad; W. Khan, Wilayat; T. Akram, Tallha; Y. Nam, Yunyoung
    Journal: IEEE Access
    Year: 2025

Reliable Autism Spectrum Disorder Diagnosis for Pediatrics Using Machine Learning and Explainable AI

  • Authors: I. Jeon, Insoo; M. Kim, Minjoong; D. So, Dayeong; J. Kim, Joungmin; J. Moon, Jihoon
    Journal: Diagnostics
    Year: 2024

Dr. Sajid Ullah Khan | Medical Image Analysis | Best Researcher Award

Dr. Sajid Ullah Khan | Medical Image Analysis | Best Researcher Award

Doctorate at Prince Sattam Bin Abdulaziz University, Saudi Arabia

๐Ÿ‘จโ€๐ŸŽ“ Profiles

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Publications

Chat-GPT; validating Technology Acceptance Model (TAM) in education sector via ubiquitous learning mechanism

  • Authors: Naveed Saif, Sajid Ullah Khan, Imrab Shaheen, Faiz Abdullah ALotaibi, Mrim M Alnfiai, Mohammad Arif
  • Journal: Computers in Human Behavior
  • Year: 2024

Energy-efficient routing protocols for UWSNs: A comprehensive review of taxonomy, challenges, opportunities, future research directions, and machine learning perspectives

  • Authors: Sajid Ullah Khan, Zahid Ulalh Khan, Mohammed Alkhowaiter, Javed Khan, Shahid Ullah
  • Journal: Journal of King Saud University-Computer and Information Sciences
  • Year: 2024

Multimodal medical image fusion towards future research: A review

  • Authors: Sajid Ullah Khan, Mir Ahmad Khan, Muhammad Azhar, Faheem Khan, Youngmoon Lee, Muhammad Javed
  • Journal: Journal of King Saud University-Computer and Information Sciences
  • Year: 2023

Historical text image enhancement using image scaling and generative adversarial networks

  • Authors: Sajid Ullah Khan, Imdad Ullah, Faheem Khan, Youngmoon Lee, Shahid Ullah
  • Journal: Sensors
  • Year: 2023

A novel CT image de-noising and fusion based deep learning network to screen for disease (COVID-19)

  • Authors: Sajid Ullah Khan, Imdad Ullah, Najeeb Ullah, Sajid Shah, Mohammed El Affendi, Bumshik Lee
  • Journal: Scientific Reports
  • Year: 2023

Mr. Shuhuan Wang | Medical Image Analysis | Best Researcher Award

Mr. Shuhuan Wang | Medical Image Analysis | Best Researcher Award

Shuhuan Wang at Northeastern University, China

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Publications

DP-CLAM: A weakly supervised benign-malignant classification study based on dual-angle scanning ultrasound images of thyroid nodules

  • Authors: Wang, S., Zhang, S., Liao, L., Huang, L., Ma, H.
  • Journal: Medical Engineering and Physics
  • Year: 2025

A model fusion method based DAT-DenseNet for classification and diagnosis of aortic dissection

  • Authors: He, L., Wang, S., Liu, R., Ma, H., Wang, X.
  • Journal: Physical and Engineering Sciences in Medicine
  • Year: 2024

SRT: Swin-residual transformer for benign and malignant nodules classification in thyroid ultrasound images

  • Authors: Huang, L., Xu, Y., Wang, S., Sang, L., Ma, H.
  • Journal: Medical Engineering and Physics
  • Year: 2024

DPAM-PSPNet: Ultrasonic image segmentation of thyroid nodule based on dual-path attention mechanism

  • Authors: Wang, S., Li, Z., Liao, L., Huang, L., Ma, H.
  • Journal: Physics in Medicine and Biology
  • Year: 2023

Prof Dr. Jinyuan Liao | Medical Image Analysis | Best Researcher Award

Prof Dr. Jinyuan Liao | Medical Image Analysis | Best Researcher Award

Jinyuan Liao at The First Affiliated Hospital of Guangxi Medical University, China

๐Ÿ‘จโ€๐ŸŽ“ Profiles

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Assoc Prof Dr. Zheng Wang | Medical Image Analysis | Best Researcher Award

Assoc Prof Dr. Zheng Wang | Medical Image Analysis | Best Researcher Award

Zheng Wang at Hunan First Normal University, China

๐Ÿ‘จโ€๐ŸŽ“ Profiles

Orcid

Publications

Artificial intelligence-empowered assessment of bile duct stone removal challenges

  • Author: Zheng Wang; Hao Yuan; Kaibin Lin; Yu Zhang; Yang Xue; Peng Liu; Zhiyuan Chen; Minghao Wu
  • Journal: Expert Systems with Applications
  • Year: 2024

Influence of hair presence on dermoscopic image analysis by AI in skin lesion diagnosis

  • Author: Zheng Wang; Yang Xue; Haonan Xi; Xinyu Tan; Kaibin Lin; Chong Wang; Jianglin Zhang
  • Journal: Computers in Biology and Medicine
  • Year: 2024

Author Correction: Radiomic and deep learning analysis of dermoscopic images for skin lesion pattern decoding

  • Author: Zheng Wang; Chong Wang; Li Peng; Kaibin Lin; Yang Xue; Xiao Chen; Linlin Bao; Chao Liu; Jianglin Zhang; Yang Xie
  • Journal: Scientific Reports
  • Year: 2024

AI fusion of multisource data identifies key features of vitiligo

  • Author: Zheng Wang
  • Journal: Scientific Reports
  • Year: 2024

Retrosynthetic analysis via deep learning to improve pilomatricoma diagnoses

  • Author: Zheng Wang
  • Journal: Computers in Biology and Medicine
  • Year: 2023

Dr. Vinniotsa Buzoianu Anguiano | Medical Image Analysis | Women Researcher Award

Dr. Vinniotsa Buzoianu Anguiano | Medical Image Analysis | Women Researcher Award

Doctorate at Hospital Nacional de Paraplรฉjicos, Spain

Profiles

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Summary

Dr. Vinnitsa Buzoianu Anguiano is an accomplished postdoctoral researcher at the Hospital Nacional de Paraplรฉjicos in Spain, specializing in neural regeneration and spinal cord injury. Her work integrates natural and health sciences to advance treatments for neural damage.

Education

  • PhD in Animal Production and Health Sciences โ€“ Universidad Nacional Autรณnoma de Mรฉxico, 2019
  • Masterโ€™s in Sciences โ€“ Universidad Nacional Autรณnoma de Mรฉxico, 2013
  • Bachelorโ€™s in Biology โ€“ Universidad Simรณn Bolรญvar, 2007

๐Ÿ’ผ Professional Experience

Dr. Buzoianu has held several research positions across Mexico and Spain, including junior researcher roles in projects like “Camina” and Universidad Anahuac. Since 2021, she has been contributing to neural regeneration research at the LRNI/Grupo Regeneraciรณn Neural.

๐Ÿ”ฌ Research Interests

Her research focuses on neural regeneration, spinal cord injuries, and innovative therapeutic strategies involving stem cells and biomaterials. She has contributed significantly to peer-reviewed publications and collaborative projects in these areas.

 

Publications

Improved Efficacy of Delayed Treatment with Human Bone Marrow-Derived Stromal Cells Evaluated in Rats with Spinal Cord Injury

  • Authors: Aguado-Garrido, M., Garcรญa-Rama, C., Romero-Ramรญrez, L., Kramer, B.W., Mey, J.
  • Journal: International Journal of Molecular Sciences
  • Year: 2024

Use of Cells, Supplements, and Peptides as Therapeutic Strategies for Modulating Inflammation after Spinal Cord Injury: An Update

  • Authors: Garcia, E., Buzoianu-Anguiano, V., Silva-Garcia, R., Doncel-Pรฉrez, E., Ibarra, A.
  • Journal: International Journal of Molecular Sciences
  • Year: 2023

Role of aldynoglia cells in neuroinflammatory and neuroimmune responses after spinal cord injury

  • Authors: Buzoianu-Anguiano, V., Torres-Llacsa, M., Doncel-Pรฉrez, E.
  • Journal: Cells
  • Year: 2021

Recovery of motor function after traumatic spinal cord injury by using plasma-synthesized polypyrrole/iodine application in combination with a mixed rehabilitation scheme

  • Authors: Sรกnchez-Torres, S., Dรญaz-Ruรญz, A., Rรญos, C., Damiรกn-Matsumura, P., Salgado-Ceballos, H.
  • Journal: Journal of Materials Science: Materials in Medicine
  • Year: 2020

Use of a Combination Strategy to Improve Morphological and Functional Recovery in Rats With Chronic Spinal Cord Injury

  • Authors: Rodrรญguez-Barrera, R., Flores-Romero, A., Buzoianu-Anguiano, V., Juรกrez-Vignon Whaley, J.J., Ibarra, A.
  • Journal: Frontiers in Neurology
  • Year: 2020

Dr. Seyed Hani Hojjati | Medical Image Analysis | Best Researcher Award

Dr. Seyed Hani Hojjati | Medical Image Analysis | Best Researcher Award

Doctorate at Weill Cornell Medicine, United States

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๐Ÿ“‹ Summary

Dr. Seyed Hani Hojjati is an accomplished Instructor of Electrical Engineering in the Department of Radiology at Weill Cornell Medicine. With a robust background in mathematics, machine learning, signal processing, and image processing, Dr. Hojjati has significantly contributed to the field of neuroimaging, particularly in Alzheimer’s disease research. His innovative work integrates resting-state functional magnetic resonance imaging (rs-fMRI) to distinguish between healthy individuals and those progressing towards mild cognitive impairment (MCI) and Alzheimer’s Disease (AD). His research has also expanded to include advanced modalities like diffusion tensor imaging (DTI) and positron emission tomography (PET), with the goal of identifying reliable biomarkers for early neuropsychological changes.

Education

  • Ph.D. in Electrical Engineering (2018)
    Babol Noshirvani University of Technology, Babol, Mazandaran, Iran
    Dissertation: Identification of Effective Brain Areas to Predict Alzheimer’s Disease Using Resting-State fMRI and MRI
  • M.Sc. in Electrical Engineering (2013)
    Babol Noshirvani University of Technology, Babol, Mazandaran, Iran
    Dissertation: Energy Efficient Cooperative Spectrum Sensing by Multi-Antenna Sensor Network and Soft Computing Techniques
  • B.Sc. in Electrical Engineering (2011)
    University of Mazandaran, Babolsar, Mazandaran, Iran
    Dissertation: Harmonic Analysis on Relays

๐Ÿ’ผ Professionalย Experience

Currently, Dr. Hojjati is an Instructor of Electrical Engineering at Weill Cornell Medicine (WCM) in the Department of Radiology, Brain Health Imaging Institute. His work focuses on the underlying mechanisms of remote associations between amyloid-beta and tau depositions at preclinical stages of Alzheimer’s disease. He has contributed significantly to the harmonization and processing of multimodal imaging data and has played a pivotal role in various NIH-funded research projects. Prior to his current role, he served as a Postdoctoral Associate at WCM, where he designed neuropsychological tasks for fMRI scanners and developed novel preprocessing tools for PET data. Dr. Hojjati also held a Postdoctoral Fellow position at the University of Tennessee Health Science Center, where he focused on multimodal neuroimaging approaches to identify early neuropsychological changes in Alzheimer’s disease.

๐Ÿ† Honors and Awards

  • Travel Scholarship, Human Amyloid Imaging (2023)
  • Winter Travel Stipend Award, University of Tennessee Health Science Center (2019)
  • Outstanding Abstract Award, University of Tennessee Health Science Center (2019)
  • Travel Stipend Award, Organization for Human Brain Mapping (2016)
  • Top Student Award, National Elites Foundation (2016)
  • Study Scholarship, Babol Noshirvani University of Technology (2014)

๐Ÿ”ฌ Research and Skillsย 

Dr. Hojjati’s research expertise spans multiple neuroimaging modalities, including rs-fMRI, task-fMRI, MRI, PET, and DTI. He is proficient in machine learning, signal processing, and image processing, with a focus on developing innovative techniques for feature integration and selection in multimodal neuroimaging data. His technical skills include programming in Python, MATLAB, and C++, as well as using neuroimaging tools like FreeSurfer, FSL, and SPM. He is also experienced in statistical analysis and neuropsychological test design.

Publications

Reduction in Constitutively Activated Auditory Brainstem Microglia in Aging and Alzheimer’s Disease

  • Authors: Butler, T., Wang, X., Chiang, G., Pascoal, T.A., Rosa-Neto, P.
  • Journal: Journal of Alzheimer’s Disease
  • Year: 2024

Remote Associations Between Tau and Cortical Amyloid-ฮฒ Are Stage-Dependent

  • Authors: Hojjati, S.H., Chiang, G.C., Butler, T.A., Devanand, D.P., Razlighi, Q.R.
  • Journal: Journal of Alzheimer’s Disease
  • Year: 2024
Seeing Beyond the Symptoms: Biomarkers and Brain Regions Linked to Cognitive Decline in Alzheimerโ€™s Disease
  • Authors: Hojjati, S.H., Babajani-Feremi, A.
  • Journal: Frontiers in Aging Neuroscience
  • Year: 2024

Prediction and Modeling of Neuropsychological Scores in Alzheimerโ€™s Disease Using Multimodal Neuroimaging Data and Artificial Neural Networks

  • Authors: Hojjati, S.H., Babajani-Feremi, A.
  • Journal: Frontiers in Computational Neuroscience
  • Year: 2022

Topographical Overlapping of the Amyloid-ฮฒ and Tau Pathologies in the Default Mode Network Predicts Alzheimer’s Disease with Higher Specificity

  • Authors: Hojjati, S.H., Feiz, F., Ozoria, S., Razlighi, Q.R.
  • Journal: Journal of Alzheimer’s Disease
  • Year: 2021

Mrs. Samreen Fiza | Medical Image Analysis | Best Researcher Award

Mrs. Samreen Fiza | Medical Image Analysis | Best Researcher Award

Samreen Fiza at Presidency University, Indiaย 

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Academic Background:

Dr. Samreen Fiza is a dedicated and accomplished academic professional with over nine years of experience in the field of Electronics and Communication Engineering. Currently serving as an Assistant Professor in the E.C.E Department at the School of Engineering, Presidency University, Bangalore, she has demonstrated excellence in teaching, research, and mentoring. She has published 14 international journal papers, presented 14 papers at international conferences, and has six patents to her name. Dr. Fiza has also been recognized with numerous awards, including the "Teaching Excellence Award" and multiple "Best Paper Awards."

Education:

Dr. Fiza is currently pursuing her Ph.D. at Presidency University, Bangalore, focusing on Image Fusion using Computer Vision and Machine Learning. She completed her MTech in Digital Communication and Networking from Dayananda Sagar College of Engineering, Bangalore, securing a First class with Distinction (82.29%) and earning a University 3rd Rank (Silver Medalist) from VTU Belgaum in 2014. She holds a BTech in Electronics and Communication Engineering from H.K.B.K. College of Engineering, Bangalore, where she also graduated with First class Distinction. Her earlier education includes completing her PUC from St. Anneโ€™s P.U. College and SSLC from St. Maryโ€™s Girls High School, both in Bangalore, Karnataka.

Professional Experience:

Dr. Fiza has a rich professional background, beginning her career as an Assistant Professor in the E.C.E Department at H.K.B.K. College of Engineering, Bangalore, where she worked from March 2015 to May 2018. Since July 2018, she has been serving as an Assistant Professor at Presidency University, Bangalore. In her current role, she has excelled in teaching a wide range of courses, coordinating research and development projects, and guiding undergraduate projects. She has also actively contributed to NAAC and NBA accreditation processes and organized numerous technical workshops, seminars, and industrial visits.

Research Interests:

Dr. Fiza's research interests lie primarily in the fields of Digital Image and Video Processing and Machine Learning. Her ongoing Ph.D. work focuses on Image Fusion using Computer Vision and Machine Learning. She has been actively involved in presenting her research at various national and international conferences and has published multiple papers and book chapters in these areas. Her notable projects include "Plant Disease Classification using DL Techniques for Smart Agriculture" and "Fluorescein Angiography Retinal Image Registration using Coherent Pixel Correspondence."

ย Publications:

Multi-focus image fusion using edge discriminative diffusion filter for satellite images
  • Authors: Samreen Fiza, S Safinaz
  • Journal: Multimedia Tools and Applications
  • Year: 2024
Medical image registration with object deviation estimation through motion vectors using octave and level sampling
  • Authors: P Nagarathna, Azra Jeelani, Samreen Fiza, G Tirumala Vasu, Koteswararao Seelam
  • Journal: Automatika
  • Year: 2024
Improved chimp optimization algorithm (ICOA) feature selection and deep neural network framework for internet of things (IOT) based android malware detection
  • Authors: Samreen Fiza, ATA Kishore Kumar, V Sowmya Devi, Ch Niranjan Kumar, Afreen Kubra
  • Journal: Measurement: Sensors
  • Year: 2023
MACHINE LEARNING ALGORITHMS BASED SUBCLINICAL KERATOCONUS DETECTION
  • Authors: Koteswararao Seelam Samreen Fiza, G. Tirumala Vasu, Afreen Kubra, Ata. Kishore Kumar
  • Journal: NeuroQuantology
  • Year: 2022
Exploring Possibilities And Methodologies for Big Data and 5G Convergence
  • Authors: Intekhab Alam, Samreen Fiza, MP Sunil
  • Year: 2023

Mr. Spencer Upton | Medical Image Analysis | Best Researcher Award

Mr. Spencer Upton | Medical Image Analysis | Best Researcher Award

Spencer Upton at University of Missuour, United States

Profiles

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ย Academic Background:

Mr. Spencer Upton is a dedicated PhD student in Cognition and Neuroscience at the University of Missouri-Columbia (MU), with extensive academic and professional experience in the fields of psychology and neuroscience. His career spans a range of roles from research assistantships to project coordination, and he has actively engaged in teaching and mentoring throughout his academic journey. Spencer's commitment to the field is evident in his contributions to various scientific communities and his recognition through multiple scholarships and awards.

Education:

Mr. Spencer began his academic career at Butler County Community College (BC3) in 2014 before earning a BS in Psychology with a focus on neuroscience and philosophy from Slippery Rock University (SRU) in 2019. He then pursued an MS in Integrative Neuroscience at Georgetown University (GU) from 2019 to 2020. Spencer is currently working towards a PhD in Cognition and Neuroscience at MU, where he also completed his MA. His doctoral research is supervised by Dr. Brett Froeliger.

Professional Experience:

Mr. Spencerโ€™s professional journey includes roles such as a Research Specialist (Project Coordinator) at the Health Neuroscience Center, MU, where he managed research projects from 2020 to 2022. He has also worked in various capacities outside the academic realm, including as a landscaper and a front desk attendant. His early professional experiences include positions as a dishwasher, cashier, and warehouse attendant, reflecting a diverse work background.

ย Research Interests:

Mr. Spencerโ€™s research interests focus on understanding the cognitive and neural mechanisms underlying addiction and motivation. His work includes exploring the effects of nicotine and other substances on cognitive processes and neural functioning. This interest is reflected in his involvement with organizations such as the Society for Neuroscience (SFN) and the Society for Research on Nicotine and Tobacco (SRNT), as well as his contributions as an assistant reviewer for journals like Addictive Behaviors and Neuropsychopharmacology.

๐Ÿ’ฐย Honors and Scholarships:

He has received various honors and scholarships, such as the Biomedical Graduate Education Scholarship from GU (2019), and multiple scholarships from SRU, including the Rose and Dale Kaufman Scholarship (2018) and the Meiping Cheng Memorial Scholarship (2017). Notably, he received the Undergraduate Mentoring Award from MU in 2023.

๐Ÿ‘จโ€๐Ÿซย Teaching Experience:

Mr. Spencer has been involved in teaching as an assistant for courses such as Psych3351: Positive Motivation and Psych 3160: Perception and Thought in Fall 2022. He also contributed as a lecturer for an MRI Workshop Series at the Cognitive Neuroscience Systems Core Facility.

ย Publications:

Mesocorticolimbic system reactivity to alcohol use-related visual cues as a function of alcohol sensitivity phenotype: A pilot fMRI study
  • Authors: Roberto U Cofresรญ, Spencer Upton, Alexander A Brown, Thomas M Piasecki, Bruce D Bartholow, Brett Froeliger
  • Journal: Addiction Neuroscience
  • Year: 2024
Spencer Upton, Alexander A. Brown, Mojgan Golzy, Eric L. Garland and Brett Froeliger
  • Authors: S Upton
  • Journal: Addiction and the Brain: Current Knowledge, Methods, and Perspectives
  • Year: 2024
Toward Concurrent Identification of Human Activities with a Single Unifying Neural Network Classification: First Step
  • Authors: Andrew Smith, Musa Azeem, Chrisogonas O Odhiambo, Pamela J Wright, Hanim E Diktas, Spencer Upton, Corby K Martin, Brett Froeliger, Cynthia F Corbett, Homayoun Valafar
  • Journal: Sensors
  • Year: 2024
Associations between right inferior frontal gyrus morphometry and inhibitory control in individuals with nicotine dependence
  • Authors: Alexander A Brown, Spencer Upton, Stephen Craig, Brett Froeliger
  • Journal: Drug and alcohol dependence
  • Year: 2023
Effects of hyperdirect pathway theta burst transcranial magnetic stimulation on inhibitory control, craving, and smoking in adults with nicotine dependence: A double-blindย โ€ฆ
  • Authors: Spencer Upton, Alexander A Brown, Muaid Ithman, Roger Newman-Norlund, Greg Sahlem, Jim J Prisciandaro, Erin A McClure, Brett Froeliger
  • Journal: Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
  • Year: 2023

Dr. Jianqi Yan | Medical Image Analysis | Best Researcher Award

Dr. Jianqi Yan, Medical Image Analysis, Best Researcher Award

Doctorate at Macau University of Science and Technology, Macau

Professional Profile

๐ŸŒŸ Summary:

Dr. Jianqi Yan is a dedicated researcher and scientist currently pursuing a Doctor of Science degree at Macau University of Science and Technology. He completed his Master’s in Applied Mathematics and Data Science from the same institution in 2021.

๐ŸŽ“ Education:

  • Master of Applied Mathematics and Data Science, Macau University of Science and Technology, 2019.09-2021.07
  • Doctor of Science (in progress), Macau University of Science and Technology, 2021.09-Present

Academic Project Experience:

  • Improving the Performance of High Resolution Spectrogram Classification using Generative Adversarial Networks (GAN), 2020.06-2022.06
  • Predictions of the Magnetocaloric Performance in Mn-Fe-P-Si Compounds using Machine Learning, 2020.07-2022.03
  • Autoregressive Search of Gravitational Waves (GWs), 2022.06 – 2024.02

Industry Project Experience:

  • Enhanced Object Detection in Bronchoscopy Images, 2022.01- Present, R&D department, Quanbao Technologies Co. Ltd
  • Artificial Intelligence Based Recognition of Hysteromyoma, 2023.01- Present, R&D department, Kaiyun Technologies Co. Ltd
  • Artificial Intelligence Based Recognition of Middle ear structure, 2023.03- Present, R&D department, Kaiyun Technologies Co. Ltd

๐Ÿ“– Publications Top Noted:

Paper Title: Autoregressive search of gravitational waves: Denoising
  • Authors: Kim, S.; Hui, C.Y.; Yan, J.; Lin, L.C.-C.; Li, K.-L.
  • Journal: Physical Review D
  • Volume: 109
  • Issue: 10
  • Pages: 102003
  • Year: 2024
Paper Title: On improving the performance of glitch classification for gravitational wave detection by using Generative Adversarial Networks
  • Authors: Yan, J.; Leung, A.P.; Hui, C.Y.
  • Journal: Monthly Notices of the Royal Astronomical Society
  • Volume: 515
  • Pages: 4606-4621
  • Issue: 3
  • Year: 2022
  • Citations: 5
Paper Title: Accelerated design for magnetocaloric performance in Mn-Fe-P-Si compounds using machine learning
  • Authors: Tu, D.; Yan, J.; Xie, Y.; Li, J.; Leung, A.P.
  • Journal: Journal of Materials Science and Technology
  • Volume: 96
  • Pages: 241-247
  • Year: 2022
  • Citations: 16