Artificial Intelligence Excellence Recognition Archives

Mr. Hailong Ning | Deep Learning | Best Scholar Award

Posted on 05/03/202505/03/2025 by ScienceFather

Early Academic Pursuits

Mr. Hailong Ning embarked on his academic journey with a strong foundation in signal and information processing. He earned his Ph.D. from the University of Chinese Academy of Sciences (2016–2021), where he focused on advanced artificial intelligence techniques for remote sensing image analysis. His research during this period laid the groundwork for innovative AI-driven methodologies in multimodal data processing.

Professional Endeavors

Currently serving as an Associate Professor and Director of the Software Engineering Department at Xi’an University of Posts and Telecommunications, Mr. Hailong Ning leads the Intelligent Security Innovation Team. He has been instrumental in pioneering AI-based remote sensing applications, supervising master’s students, and collaborating with prestigious institutions like Northwestern Polytechnical University and the German Aerospace Center (DLR). His leadership extends to national projects funded by entities such as the National Natural Science Foundation of China (NSFC) and industry collaborations in defense, energy, and aerospace.

Contributions and Research Focus

Mr. Hailong Ning’s research spans artificial intelligence, federated learning, and multimodal data processing, with a particular emphasis on remote sensing image analysis. His innovative hierarchical modeling techniques have addressed critical challenges in aerial image interpretation, cross-domain distribution shifts, and federated domain generalization. His work has significant implications for privacy-preserving AI applications and large-scale image recognition tasks in security and defense.

Impact and Influence

Mr. Hailong Ning’s contributions extend beyond academia, with his patented AI technologies being deployed in military surveillance, including border security operations in Tibet, and smart city systems. His research outcomes have been adopted for intelligent UAV monitoring and real-time security analysis, processing over one million images. His impact is also evident in his role as a mentor, having guided 26 graduate students toward academic and industry success.

Academic Citations and Publications

“Semantics-Consistent Representation Learning for Remote Sensing Image-Voice Retrieval” – IEEE Transactions on Geoscience and Remote Sensing (IF: 7.5, Citations: 39)
“Disentangled Representation Learning for Cross-modal Biometric Matching” – IEEE Transactions on Multimedia (IF: 8.4, Citations: 33)
“Difference Enhancement and Spatial-Spectral Non-Local Network for Change Detection in VHR Remote Sensing Images” – IEEE Transactions on Geoscience and Remote Sensing (IF: 7.5, Citations: 76)

Technical Skills

Programming: Python, MATLAB, C++
AI & ML Frameworks: TensorFlow, PyTorch
Remote Sensing Software: ENVI, ERDAS, Google Earth Engine
Security & Surveillance Systems: Federated Learning, AI-based anomaly detection

Teaching and Mentorship

As a dedicated educator, Mr. Hailong Ning supervises graduate students in AI and software engineering, emphasizing real-world problem-solving through research-driven learning. He has designed and taught courses on Deep Learning for Remote Sensing, AI-Driven Image Processing, and Multimodal Data Fusion. His mentorship has empowered students to secure research grants and high-impact publications.

Legacy and Future Contributions

Mr. Hailong Ning’s ongoing projects focus on intelligent UAV monitoring, privacy-enhanced federated learning, and AI-driven security systems. His commitment to AI innovation is reflected in his role as an editorial board member for Remote Sensing Technology and as a reviewer for IEEE TCYB, IEEE TNNLS, and other leading journals. Moving forward, he aims to bridge theoretical AI advancements with large-scale industrial applications, fostering AI solutions for smart surveillance, environmental monitoring, and national security.

Publications

Orientational clustering learning for open-set hyperspectral image classification

Authors: Hao Xu, Wenjing Chen, Cheng Tan, Hailong Ning, Hao Sun, Wei Xie
Journal: IEEE Geoscience and Remote Sensing Letters
Year: 2024

An ensemble learning-enhanced multitask learning method for continuous affect recognition from facial images

Authors: Ercheng Pei, Zhanxuan Hu, Lang He, Hailong Ning, Abel Díaz Berenguer
Journal: Expert Systems with Applications
Year: 2024

Hierarchical Semantic-Guided Contextual Structure-Aware Network for Spectral Satellite Image Dehazing

Authors: Lei Yang, Jianzhong Cao, Hua Wang, Sen Dong, Hailong Ning
Journal: Remote Sensing
Year: 2024

Remote Sensing Image Dehazing via Dual-View Knowledge Transfer

Authors: Lei Yang, Jianzhong Cao, He Bian, Rui Qu, Huinan Guo, Hailong Ning
Journal: Applied Sciences
Year: 2024

Ultra-Lightweight Spatial-Spectral Feature Cooperation Network for Change Detection in Remote Sensing Images

Authors: Tao Lei, Xinzhe Geng, Hailong Ning*, Zhiyong Lv, Maoguo Gong, Yaochu Jin, Asoke K. Nandi
Journal: IEEE Transactions on Geoscience and Remote Sensing
Year: 2023

Dr. Sitara Afzal | Deep Learning | Best Researcher Award

Posted on 04/03/202504/03/2025 by ScienceFather

Summary

Dr. Sitara Afzal is a dedicated AI researcher with expertise in computer vision, advanced image processing, emotion recognition, time-series data analysis, and multimedia understanding for image, text, and video processing. As a Research Assistant at the Mixed Reality and Interaction (MR&I) Laboratory at Sejong University, South Korea, she has actively contributed to cutting-edge research, publishing in high-impact journals and presenting at prestigious international conferences. Her research focuses on developing intelligent systems, particularly in machine learning, deep learning, affective computing, and mixed reality. She possesses strong proficiency in MATLAB, Python, Java, C#, CUDA, along with experience in graphics design, visualization tools, and AI-driven technologies.

Education

Ph.D. in Software Engineering – Sejong University, South Korea (2021-2024, CGPA: 4.25/4.5)
M.Sc. in Computer Science – COMSATS University Islamabad, Pakistan (2017-2019, CGPA: 3.58/4.0)
B.Sc. in Computer Science – COMSATS University Islamabad, Pakistan (2013-2017, CGPA: 3.08/4.0)

Research Experience

Research Assistant – MR&I Lab, Sejong University, South Korea (June 2021 – Feb 2025)
BS/MS Student Supervisor – COMSATS University Islamabad, Pakistan (Sept 2022 – Present)
Assistant Teacher (Data Mining & Machine Learning) – COMSATS University Islamabad (Sept 2018 – June 2019)

Core Technical Skills

Programming: MATLAB, Python, Java, C#, CUDA
Graphics & Design: Origin Pro, Adobe Illustrator, Adobe Premiere, Blender, Design.IO
Visualization Tools: HoloLens 1 & 2, Bio-Well, Emotiv

AI & Research Expertise

Machine Learning & Deep Learning: Supervised/Unsupervised Learning, Reinforcement Learning, CNNs, RNNs
Advanced Image Processing: Classification, Segmentation, Enhancement, Object Detection
Mixed Reality & HCI: AI-integrated human-computer interaction

Awards & Honors

Best Alumni Award – COMSATS University (Dec 2021)
100% Study Scholarship – Sejong University (Ph.D.)
100% Study Scholarship – COMSATS University (M.Sc.

Publications

A comprehensive survey on affective computing; challenges, trends, applications, and future directions

Authors: Sitara Afzal, Haseeb Ali Khan, Md Jalil Piran, Jong Weon Lee
Journal: IEEE access
Year: 2024

Construction of a uniform zeolitic imidazole framework (ZIF-8) nanocrystal through a wet chemical route towards supercapacitor application

Authors: Iqra Rabani, Je-Won Lee, Taeyoon Lim, Hai Bang Truong, Sobia Nisar, Sitara Afzal, Young-Soo Seo
Journal: RSC advances
Year: 2024

Leveraging Augmented Reality, Semantic-Segmentation, and VANETs for Enhanced Driver’s Safety Assistance.

Authors: Sitara Afzal, Imran Ullah Khan, Irfan Mehmood, Jong Weon Lee
Journal: Computers, Materials & Continua
Year: 2024

PlantView: Integrating deep learning with 3D modeling for indoor plant augmentation

Authors: Sitara Afzal, Haseeb Ali Khan, Jong Weon Lee
Journal: Ecological Informatics
Year: 2024

Deep-learning-assisted business intelligence model for cryptocurrency forecasting using social media sentiment

Authors: Muhammad Yasir, Muhammad Attique, Khalid Latif, Ghulam Mujtaba Chaudhary, Sitara Afzal, Kamran Ahmed, Farhan Shahzad
Journal: Journal of Enterprise Information Management
Year: 2023

Dr. Lei xiang | Deep Learning | Best Researcher Award

Posted on 28/02/202528/02/2025 by ScienceFather

Education

Dr. Lei Xiang holds a Ph.D. in Biomedical Engineering from Shanghai Jiao Tong University (2019). He earned his Master’s degree in System Science from Nanjing University of Information Science & Technology (2015) and a Bachelor’s degree in Systems Engineering from the same university (2012).

Professional Experience

Dr. Xiang is currently the Chief Technology Officer (CTO) at Subtle Medical, Shanghai, a leading company in AI-driven medical imaging solutions. Previously, he worked as a Senior Deep Learning Scientist at Subtle Medical, Menlo Park, USA, where he developed advanced deep learning models for medical image enhancement, focusing on PET, MRI, CT, and SPECT imaging.

He has also gained research experience as an Intern at SenseTime (Shanghai), working on automated pelvis segmentation models, and as a Visiting Scholar at the University of North Carolina at Chapel Hill and Shenzhen Institutes of Advanced Technology.

Research & Publications

Dr. Xiang has an extensive research background in deep learning for medical imaging, with over 13 journal papers and 9 conference papers published in top-tier venues, including Medical Image Analysis, IEEE Transactions on Medical Imaging, Neurocomputing, and Pattern Recognition. His research focuses on multi-modal medical image reconstruction, deep learning-based PET/MRI enhancement, and AI-driven medical diagnostics.

Patents, Honors & Awards

Dr. Xiang holds 10+ international patents, including technologies for SubtlePET, SubtleMR, SubtleSPECT, SubtleCT, and SubtleSpine. He has won numerous prestigious awards, including:

First Place in the Ultra-low Dose PET Imaging Challenge (UDPET, 2022)
1st Rank in the FastMRI Challenge Public Leaderboard (2020)
3rd Prize in Spark: “Digital Body” AI Challenge (2020)
2nd Rank in the Robotic Scene Segmentation Challenge (2018, MICCAI)
1st Prize in the National Postgraduate Mathematic Contest in Modeling (2016)
Outstanding Graduate Award for both Undergraduate and Graduate studies

Professional Services

Dr. Xiang actively contributes to the AI and medical imaging community as a conference reviewer for major AI and medical imaging conferences, including CVPR, ICCV, MICCAI, MIDL, ECCV, and WACV.

Research Interests

AI-powered medical image enhancement
Deep learning for multi-modal fusion in medical imaging
PET/MRI/CT reconstruction and noise-aware image processing
Automated diagnostics and segmentation in medical imaging

Publications

Multimodal MRI reconstruction assisted with spatial alignment network

Authors: Kai Xuan, Lei Xiang, Xiaoqian Huang, Lichi Zhang, Shu Liao, Dinggang Shen, Qian Wang
Journal: IEEE Transactions on Medical Imaging
Year: 2022

Task decomposition and synchronization for semantic biomedical image segmentation

Authors: Xuhua Ren, Sahar Ahmad, Lichi Zhang, Lei Xiang, Dong Nie, Fan Yang, Qian Wang, Dinggang Shen
Journal: IEEE Transactions on Image Processing
Year: 2020

Noise-aware standard-dose PET reconstruction using general and adaptive robust loss

Authors: Lei Xiang, Long Wang, Enhao Gong, Greg Zaharchuk, Tao Zhang
Journal: Machine Learning in Medical Imaging
Year: 2020

Deep learning for fast and spatially constrained tissue quantification from highly accelerated data in magnetic resonance fingerprinting

Authors: Zhenghan Fang, Yong Chen, Mingxia Liu, Lei Xiang, Qian Zhang, Qian Wang, Weili Lin, Dinggang Shen
Journal: IEEE transactions on medical imaging
Year: 2019

Deep embedding convolutional neural network for synthesizing CT image from T1-Weighted MR image

Authors: Lei Xiang, Qian Wang, Dong Nie, Lichi Zhang, Xiyao Jin, Yu Qiao, Dinggang Shen
Journal: Medical image analysis
Year: 2018

Mr. Muhammad Rizwan | Deep Learning | Best Researcher Award

Posted on 24/02/202524/02/2025 by ScienceFather

Summary

Mr. Muhammad Rizwan is an Electronics Postgraduate with a strong background in Machine Learning, Deep Learning, and AI Robotics. He has been working with Python since 2019 and is proficient in TensorFlow, Keras, and PyTorch. Mr. Rizwan seeks opportunities to advance his career in AI and robotics, bringing hands-on experience with innovative research and a passion for solving real-world challenges.

Education

MPhil in Electronics, University of Peshawar (2019-2022)
- Thesis: Appearance-Based Dynamic Hand Gesture Recognition using 3D Separable CNN
BS in Electronics, University of Peshawar (2015-2019)
- Project: Mind-Directed Telepresence Robot
FSC in Pre-Engineering, Agriculture University Public School, Peshawar (2013-2015)
Matric, Kings Hall Public School, Peshawar (2011-2013)

Work Experience

Lecturer, Government College of Technology, Peshawar (2022-2023)
- Supervised final-year projects on Raspberry Pi Pico and ESA 8086/88-3 Trainer Board
- Contact: Engr. Nasrullah Khan (+92 3459419377)

Research Interests

Computer Vision
Deep Learning & Machine Learning
Robotics
Indoor Localization
Plant Disease Detection
Hand Gesture Recognition

Skills

Programming: Python, C, C++
Frameworks: TensorFlow, PyTorch
Hardware: Raspberry Pi, Verilog HDL
Tools: PCB Designing, MS Office
Languages: English (Professional Working), Urdu (Full Professional), Saraiki (Full Professional)

Research and Projects

WIFI RSSI Fingerprint Based Indoor Localization (2024)
- Focus on 3D separable CNN for improved indoor localization.
Plant Disease Detection (2022-2023)
- Developed a model for plant disease detection with high accuracy and efficiency.
Dynamic Hand Gesture Recognition (2020-2022)
- Created a model using 3D Separable CNN for real-time hand gesture recognition.
Virtual Reality-Based Telepresence Robot (2018-2019)
- Designed a robot for remote medical consultations in rural areas of Pakistan.

Publications

Enhancing Indoor Localization with Temporally-Aware Separable Group Shuffled CNNs and Skip Connections

Authors: Muhammad Rizwan, Yin Hoe Ng, Hin-Yong Wong, Chee Keong Tan
Journal: IEEE Access
Year: 2025

Automatic plant disease detection using computationally efficient convolutional neural network

Authors: Muhammad Rizwan, Samina Bibi, Sana Ul Haq, Muhammad Asif, Tariqullah Jan, Mohammad Haseeb Zafar
Journal: Engineering Reports
Year: 2024

Appearance Based Dynamic Hand Gesture Recognition Using 3D Separable Convolutional Neural Network.

Authors: Muhammad Rizwan, Sana Ul Haq, Noor Gul, Muhammad Asif, Syed Muslim Shah, Tariqullah Jan, Naveed Ahmad
Journal: Computers, Materials & Continua
Year: 2023

Assist Prof Dr. Mohammad Javad Parseh | Deep Learning | Editorial Board Member

Posted on 24/02/202524/02/2025 by ScienceFather

Summary

Assist. Prof. Dr. Mohammad Javad Parseh is a dedicated researcher and educator in Computer Science and Artificial Intelligence at Jahrom University, Iran. With expertise in machine learning, deep learning, computer vision, and optimization algorithms, he has developed and taught various courses, supervised student projects, and published numerous research papers. He has also contributed to organizing and chairing AI and ML conferences and workshops.

Education

Ph.D. in Computer Engineering (AI & Robotics), Semnan University, Iran (2022)
- Thesis: Scene Classification using Multi-weighted Scene Graph
M.Sc. in Computer Engineering (AI), University of Tabriz, Iran (2012)
- Thesis: Multiple Maneuvering Aircraft Tracking using Particle Filtering
B.Sc. in Computer Engineering (Software), Shahid Chamran University, Iran (2009)
- Thesis: Anthology Matching in Semantic Web

Professional Experience

Assistant Professor, Jahrom University (2012 – Present)
IT Manager, Jahrom University (2022 – Present)
Head of Computer Engineering Dept., Jahrom University (2014 – 2017)

Research Interests

Computer Vision & Image Processing (Scene Understanding, Image Captioning, VQA, Image Segmentation)
Machine Learning & Deep Learning
Multiple Object Tracking in Video
Optimization Algorithms

Publications

Graph-based image captioning with semantic and spatial features

Authors: Mohammad Javad Parseh, Saeed Ghadiri
Journal: Signal Processing: Image Communication
Year: 2025

Integrated of Hyperspectral Imaging and Machine Learning Algorithms for Nondestructive Detection of Therapeutic Properties of Plants

Authors: Mahmood Mahmoodi‐Eshkaftaki, Saeideh Mohtashami, Mohammad Javad Parseh, Askar Ghani
Journal: Chemistry & Biodiversity
Year: 2025

Scene representation using a new two-branch neural network model

Authors: Mohammad Javad Parseh, Mohammad Rahmanimanesh, Parviz Keshavarzi, Zohreh Azimifar
Journal: The Visual Computer
Year: 2024

Face mask recognition using a custom CNN and data augmentation

Authors: Pooya Fazeli Ardekani, Seyede Zahra Tale, Mohammad Javad Parseh
Journal: Signal, Image and Video Processing
Year: 2024

Semantic embedding: scene image classification using scene-specific objects

Authors: Mohammad Javad Parseh, Mohammad Rahmanimanesh, Parviz Keshavarzi, Zohreh Azimifar
Journal: Multimedia Systems
Year: 2023

Dr. Anita Sebasthiyar | Deep Learning | Best Researcher Award

Posted on 17/02/202517/02/2025 by ScienceFather

Early Academic Pursuits

Dr. Anita Sebasthiyar embarked on her academic journey with a strong foundation in Electronics and Communication Engineering (ECE). Her passion for technology and innovation led her to pursue advanced studies, where she specialized in Digital Image Processing, Machine Learning, Deep Learning Algorithms, and Antenna Design.

Professional Endeavors

With an impressive 16 years of teaching experience, Dr. Anita Sebasthiyar has played a pivotal role in engineering education. She is currently a Professor at St. Anne’s College of Engineering & Technology, where she has been a faculty member since 2009. Over the years, she has served in various capacities, including Associate Professor (2017–2023), Assistant Professor (2013–2017), and Lecturer (2009–2013). Before joining St. Anne’s, she worked as a Lecturer at Annai Velankanni Polytechnic College (2007–2009), contributing significantly to shaping young minds.

Contributions and Research Focus

Dr. Anita Sebasthiyar’s research contributions span across Deep Learning, Image Processing, Antenna Design, and AI-driven medical diagnostics. She has been actively involved in filing and securing patents, with notable inventions such as:

“Computer Operator Name with Location, Tracking New System” (Patent No. 202241005961 A, 2022)
“Shoe for Visually Impaired” (Patent No. 424219-001, 2024)
“A System for Analyzing Single Photon Emission Computed Tomography (SPECT) Images” (Patent No. 202241017033 A, 2024)

Her research has paved the way for technological advancements in healthcare, AI applications, and accessibility solutions.

Impact and Influence

As a resource person, Dr. Anita Sebasthiyar has delivered numerous expert talks and workshops, sharing her knowledge with students, researchers, and industry professionals. Some of her notable sessions include:

“Basics to Advanced: Machine Learning” (September 2021)
“Artificial Intelligence in Nursing: Transforming Patient Care” (January 2025)
“Diagnosing Early Stage of Parkinson’s Disease using JAN Net” (London, October 2024)
She has also played an instrumental role in training students in design thinking, research writing, and innovation.

Academic Contributions and Technical Expertise

Dr. Anita Sebasthiyar is actively involved in academic curriculum development, examination panels, and question paper setting. She served as a Question Paper Setter for EC3551/Transmission Lines and RF Systems at Indira Ganesan College of Engineering and Technology. Additionally, she has led several faculty development programs (FDPs) and workshops on Digital Image Processing using MATLAB, AI Tools, and Biomedical Deep Learning Applications.

Teaching Experience

Throughout her career, Dr. Anita Sebasthiyar has been committed to enhancing the learning experience for students. She has taught a wide range of subjects in Electronics and Communication Engineering, integrating the latest advancements in AI, Deep Learning, and Digital Image Processing into her teaching methodologies.

Recognitions and Awards

Dr. Anita Sebasthiyar’s research excellence has been recognized at prestigious international conferences. She received:

Best Paper Award at the Fifth International Conference on Bio-Signals, Images, and Instrumentation (2019)
Best Paper Award at the Ninth International Conference on Mining Intelligence and Knowledge Exploration (MIKE 2023), Norway, for her work on Hybrid Optimal Fine-Tuning in Deep Learning for Parkinson’s Disease Diagnosis

Legacy and Future Contributions

Dr. Anita Sebasthiyar continues to push the boundaries of research and education, mentoring students and researchers in cutting-edge AI-driven medical diagnostics, antenna design, and deep learning applications. As a Coordinator of the MSME Innovative Scheme Incubation Component and UBA, she actively fosters entrepreneurial and research-based learning. Her contributions to engineering education, research, and technological innovations will undoubtedly leave a lasting impact on the academic and industrial landscape, inspiring the next generation of engineers and researchers.

Publications

Modified Exigent Features Block in JAN Net for Analysing SPECT Scan Images to Diagnose Early-Stage Parkinson’s Disease.

Authors: S Jothi, S Anita, S Sivakumar
Journal: Current Medical Imaging
Year: 2023

Improved classification accuracy for diagnosing the early stage of Parkinson’s disease using alpha stable distribution

Authors: S Anita
Journal: IETE Journal of Research
Year: 2023

Mathematical model for early stage identification of Parkinson’s disease using neurotransmitter: GABA

Authors: S Anita, R Arokiadass
Journal: International Journal of Information Technology
Year: 2022

Diagnosis of Parkinson’s disease at an early stage using volume rendering SPECT image slices

Authors: S Anita, P Aruna Priya
Journal: Arabian Journal for Science and Engineering
Year: 2020

Three dimensional analysis of SPECT images for diagnosing early Parkinson’s disease using Radial Basis Function kernel− Extreme learning machine

Authors: Sebasthiyar Anita, Panchnathan A Priya
Journal: Current Medical Imaging
Year: 2019

Assoc Prof Dr. Mohammad Javad Ebadi | Deep Learning | Editorial Board Member

Posted on 29/01/202529/01/2025 by ScienceFather

Early Academic Pursuits

Associate Professor Dr. Mohammad Javad Ebadi embarked on his academic journey with a strong foundation in mathematics, which led him to pursue advanced studies in the field. His dedication and excellence earned him a doctoral scholarship from Iran’s Ministry of Science, Research, and Technology (2013-2017). During this period, he expanded his research expertise as a Visiting Scholar at the Mediterranean University of Reggio Calabria, Italy, under the supervision of Prof. F. Carlo Morabito.

Professional Endeavors

Dr. Ebadi has been a faculty member at Chabahar Maritime University since 2006, where he has made significant contributions to the Department of Mathematics. His leadership skills were recognized when he was appointed as the Head of the Mathematics Department in 2023. In addition, he has been serving as a Research Associate at the International Telematic University Uninettuno, Italy, since 2022, further broadening his academic collaborations on a global scale.

Contributions and Research Focus

Dr. Ebadi’s research spans a wide array of mathematical and computational fields, including Deep Learning, Fractional Calculus, Numerical Optimization, (Meta)Heuristic Techniques for Optimization, Image Processing, Data Envelopment Analysis, and Fuzzy Mathematics. His work also extends to Optimal Control, Dynamic Programming, and Fuzzy Stochastic Differential Equations. His ability to integrate these diverse areas into practical problem-solving has led to groundbreaking advancements in mathematical modeling and computational efficiency.

Impact and Influence

Dr. Ebadi’s impact on the academic community is evident through his extensive contributions as an editor and reviewer for numerous high-impact journals. He has served as a Section Editor for the International Journal of Systematic Innovation and a Guest Editor for Mathematics (MDPI), focusing on advanced optimization techniques for machine learning. His outstanding contributions as a reviewer have been recognized with multiple awards, including the Journal of Information Processing & Management Reviewer Award (2021) and Best Reviewer Awards from prestigious journals such as Advances in Science, Technology and Engineering Systems Journal (ASTESJ) and Sustainable Energy Technologies and Assessments.

Academic Citations and Recognitions

Dr. Ebadi has received numerous research awards from Chabahar Maritime University, spanning from 2006 to 2023, reflecting his consistent excellence in academic research. His scholarly influence extends beyond his institution, as he has been acknowledged as an Excellent Reviewer for multiple international journals, further solidifying his reputation as a leading researcher in applied mathematics and optimization.

Technical Skills and Expertise

With a strong command of computational tools, Dr. Ebadi possesses expertise in MATLAB programming, LaTeX, and various mathematical software such as Mathematica, Maple, and Sigma Plot. His proficiency in e-learning platforms, including Blackboard, Microsoft Teams, Zoom, and WebEx, has enabled him to effectively engage with students and researchers worldwide. Additionally, he is well-versed in reference management tools such as EndNote and Mendeley, which facilitate his research documentation and collaboration.

Teaching Experience and Pedagogical Contributions

Dr. Ebadi has been actively involved in teaching for over a decade, delivering both undergraduate and graduate courses at Chabahar Maritime University. His teaching portfolio includes Advanced Operations Research, Operations Research, Ordinary Differential Equations, Calculus, Numerical Calculations, Numerical Analysis, Engineering Mathematics, Biostatistics, Engineering Probability and Statistics, Partial Differential Equations, Linear & Nonlinear Optimization, History of Mathematics, and Mathematical Software. His ability to simplify complex mathematical concepts has made him a respected educator and mentor.

Legacy and Future Contributions

Dr. Ebadi’s commitment to academic excellence, research innovation, and mentorship continues to shape the future of mathematics and computational sciences. His leadership in mathematical research and optimization techniques is paving the way for novel applications in artificial intelligence, data science, and engineering. As a dedicated researcher and educator, he remains committed to advancing knowledge, mentoring young scholars, and fostering international collaborations that contribute to the global scientific community.

Publications

Efficient Deep Neural Networks for Classification of Alzheimer’s Disease and Mild Cognitive Impairment from Scalp EEG Recordings

Authors: S Fouladi, AA Safaei, N Mammone, F Ghaderi, MJ Ebadi
Journal: Cognitive Computation
Year: 2024

Optimal study on fractional fascioliasis disease model based on generalized Fibonacci polynomials

Authors: Zakieh Avazzadeh, Hossein Hassani, Praveen Agarwal, Samrad Mehrabi, MJ Ebadi, M Kazem Hosseini Asl
Journal: Mathematical Methods in the Applied Sciences
Year: 2023

Diagnosis of Alternaria disease and Leafminer pest on tomato leaves using Image processing techniques

Authors: K Nazari, MJ Ebadi, K Berahmand
Journal: Journal of the Science of Food and Agriculture
Year: 2022

An efficient coverage and connectivity algorithm based on mobile robots for wireless sensor networks

Authors: Peyman Tirandazi, Atefeh Rahiminasab
Journal: Journal of Ambient Intelligence and Humanized Computing
Year: 2022

The use of artificial neural networks to diagnose Alzheimer’s disease from brain images

Authors: S Fouladi, AA Safaei, NI Arshad, MJ Ebadi, A Ahmadian
Journal: Multimedia Tools and Applications
Year: 2022

Dr. Naushad Varish | Deep Learning | Best Researcher Award

Posted on 28/01/202528/01/2025 by ScienceFather

Summary

Dr. Naushad Varish holds a Ph.D. in Computer Science and Engineering from IIT (ISM) Dhanbad. With over a decade of academic and professional experience, he specializes in content-based image retrieval, machine learning, deep learning, and cybersecurity. He has published extensively in high-impact journals such as IEEE Access and Applied Intelligence. Dr. Varish has also received prestigious fellowships, including the Junior and Senior Research Fellowships at IIT (ISM). His teaching interests include operating systems, data science, artificial intelligence, and digital image processing.

Education

Ph.D. in Computer Science and Engineering from Indian Institute of Technology (ISM), Dhanbad
MCA from Aligarh Muslim University
B.Sc. (Honors) in Statistics from Aligarh Muslim University

Professional Experience

Dec 2022 – Present: Assistant Professor (Senior Scale), GITAM (Deemed to be University)
Jan 2019 – Dec 2022: Associate Professor, Koneru Lakshmaiah Education Foundation
Feb 2018 – Jan 2019: Assistant Professor, Meerut Institute of Engineering and Technology
2012 – 2013: Assistant Software Engineer at ZMQ Technologies Pvt. Ltd.

Research Interests

Content-Based Image Retrieval (CBIR)
Machine Learning & Deep Learning
Data Science and Artificial Intelligence
Digital Image Processing
Cyber Security

Publications

Diagnostic Accuracy of Artificial Intelligence-Based Algorithms in Automated Detection of Neck of Femur Fracture on a Plain Radiograph: A Systematic Review and Meta-analysis

Authors: Manish Raj, Arshad Ayub, Arup Kumar Pal, Jitesh Pradhan, Naushad Varish, Sumit Kumar, Seshadri Reddy Varikasuvu
Journal: Indian Journal of Orthopaedics
Year: 2024

Improving search result clustering using nature inspired approach

Authors: Shashi Mehrotra, Aditi Sharan, Naushad Varish
Journal: Multimedia Tools and Applications
Year: 2024

A hybrid model: PNM for improving prediction capability of classifier

Authors: Shashi Mehrotra, Vinay Kumar Muttum, Redrouthu Vamsi Krishna, Vinod Kumar, Naushad Varish
Journal: International Journal of Information Technology
Year: 2024

Model-based recognition in robot vision for monitoring built environments

Authors: Asif Khan, Naushad Varish, Dhirendra Pandey, Syed Qasim Afser Rizvi, Shashi Mehrotra, Nikhat Parveen
Journal: Multimedia Tools and Applications
Year: 2024

Deep hierarchical spectral-spatial feature fusion for hyperspectral image classification based on convolutional neural network

Authors: Somenath Bera, Naushad Varish, Mudassir Rafi, Vimal K Shrivastava
Journal: Intelligent Data Analysis
Year: 2024

Dr. Zari Farhadi | Deep Learning | Best Researcher Award

Posted on 06/01/202506/01/2025 by ScienceFather

Summary

Dr. Zari Farhadi is a dedicated lecturer and researcher with a Ph.D. in Data Science, specializing in machine learning, predictive modeling, and deep learning. She has developed innovative hybrid models such as ADeFS, RARTEN, ERDeR, and ECAPRAF, contributing to advanced data analysis. Her work includes impactful publications in esteemed journals and a commitment to interdisciplinary research.

Education

Ph.D. in Data Science
Academic focus on statistical learning and ensemble methods

Professional Experience

Lecturer, University of Tabriz, Iran
Focused on teaching and research in data science and artificial intelligence
Reviewer for leading journals: PLOS ONE, IEEE Access, Frontiers, and Ain Shams Engineering

Research Interests

Machine Learning and Deep Learning
Predictive Modeling and Ensemble Learning
Development of hybrid models for advanced data analysis
Statistical Learning and innovative applications in data science

Publications

Improving random forest algorithm by selecting appropriate penalized method

Authors: Zari Farhadi, Hossein Bevrani, Mohammad-Reza Feizi-Derakhshi
Journal: Communications in Statistics-Simulation and Computation
Year: 2024

ERDeR: The combination of statistical shrinkage methods and ensemble approaches to improve the performance of deep regression

Authors: Zari Farhadi, Mohammad-Reza Feizi-Derakhshi, Hossein Bevrani, Wonjoon Kim, Muhammad Fazal Ijaz
Journal: IEEE Access
Year: 2024

ADeFS: A Deep Forest Regression-Based Model to Enhance the Performance Based on LASSO and Elastic Net

Authors: Zari Farhadi, Mohammad-Reza Feizi-Derakhshi, Israa Khalaf Salman Al-Tameemi, Wonjoon Kim
Journal: Mathematics
Year: 2024

Corrections to “ERDeR: The Combination of Statistical Shrinkage Methods and Ensemble Approaches to Improve the Performance of Deep Regression”

Authors: Zari Farhadi, Mohammad-Reza Feizi-Derakhshi, Hossein Bevrani, Wonjoon Kim, Muhammad Fazal Ijaz
Journal: IEEE Access
Year: 2024

An Ensemble-based Model for Sentiment Analysis of Persian Comments on Instagram Using Deep Learning algorithms

Authors: Soheyla Eyvazi-Abdoljabbar, SeongKi Kim, Mohammad-Reza Feizi-Derakhshi, Zari Farhadi, Dheyaa Abdulameer Mohammed
Journal: IEEE Access
Year: 2024

Dr. Youjie Li | Deep Learning | Best Researcher Award

Posted on 30/12/202430/12/2024 by ScienceFather

Summary

Dr. Youjie Li is a distinguished academic at Kunming University of Science and Technology, renowned for his contributions to finance and science. With decades of dedication to teaching, research, and editorial excellence, he has significantly influenced his field.

Education

Dr. Li earned his doctorate from the prestigious Southwestern University of Finance and Economics, laying a strong foundation for his illustrious academic journey.

Professional Experience

Dr. Li has devoted his career to Kunming University of Science and Technology, where he has excelled as a professor and mentor. He has also served as an editor for various SCI-indexed journals, showcasing his expertise in research dissemination.

Research Interests

His research focuses on finance, economics, and interdisciplinary studies, reflected in numerous SCI-indexed publications that advance knowledge and innovation.

Publications

A novel nonlinear direct-mapping approach for multiple time scale driving force analysis of surface water quality variations under intense human interference

Authors: Wang, Y., Cai, Y., Li, B., Li, Y., Zhao, S.
Journal: Journal of Environmental Management
Year: 2024

An intelligently adjusted carbon price forecasting approach based on breakpoints segmentation, feature selection and adaptive machine learning

Authors: Zhao, S., Wang, Y., Deng, G., Chen, Z., Li, Y.
Journal: Applied Soft Computing
Year: 2023

A carbon price hybrid forecasting model based on data multi-scale decomposition and machine learning

Authors: Yang, P., Wang, Y., Zhao, S., Chen, Z., Li, Y.
Journal: Environmental Science and Pollution Research
Year: 2023

XI’an University of Posts & Telecommunications, China

<img decoding="async" class="" src="https://s.w.org/images/core/emoji/15.0.3/svg/1f468-200d-1f393.svg" alt="👨‍🎓" width="42" height="42" /> Profiles

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f4da/32.png" alt="📚" data-emoji="📚" aria-label="📚" /> Early Academic Pursuits

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f3c6/32.png" alt="🏆" data-emoji="🏆" aria-label="🏆" /> Professional Endeavors

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f52c/32.png" alt="🔬" data-emoji="🔬" aria-label="🔬" /> Contributions and Research Focus

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f30d/32.png" alt="🌍" data-emoji="🌍" aria-label="🌍" /> Impact and Influence

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f4d6/32.png" alt="📖" data-emoji="📖" aria-label="📖" /> Academic Citations and Publications

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f6e0_fe0f/32.png" alt="🛠️" data-emoji="🛠️" aria-label="🛠️" /> Technical Skills

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f393/32.png" alt="🎓" data-emoji="🎓" aria-label="🎓" /> Teaching and Mentorship

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f52e/32.png" alt="🔮" data-emoji="🔮" aria-label="🔮" /> Legacy and Future Contributions

Orientational clustering learning for open-set hyperspectral image classification

An ensemble learning-enhanced multitask learning method for continuous affect recognition from facial images

Hierarchical Semantic-Guided Contextual Structure-Aware Network for Spectral Satellite Image Dehazing

Remote Sensing Image Dehazing via Dual-View Knowledge Transfer

Ultra-Lightweight Spatial-Spectral Feature Cooperation Network for Change Detection in Remote Sensing Images

Doctorate at Sejong University, South Korea

<img decoding="async" class="" src="https://s.w.org/images/core/emoji/15.0.3/svg/1f468-200d-1f393.svg" alt="👨‍🎓" width="42" height="42" /> Profiles

Summary

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f393/32.png" alt="🎓" data-emoji="🎓" aria-label="🎓" /> Education

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f52c/32.png" alt="🔬" data-emoji="🔬" aria-label="🔬" /> Research Experience

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f6e0/32.png" alt="🛠" data-emoji="🛠" aria-label="🛠" /> Core Technical Skills

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f916/32.png" alt="🤖" data-emoji="🤖" aria-label="🤖" /> AI & Research Expertise

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f3c6/32.png" alt="🏆" data-emoji="🏆" aria-label="🏆" /> Awards & Honors

A comprehensive survey on affective computing; challenges, trends, applications, and future directions

Construction of a uniform zeolitic imidazole framework (ZIF-8) nanocrystal through a wet chemical route towards supercapacitor application

Leveraging Augmented Reality, Semantic-Segmentation, and VANETs for Enhanced Driver’s Safety Assistance.

PlantView: Integrating deep learning with 3D modeling for indoor plant augmentation

Deep-learning-assisted business intelligence model for cryptocurrency forecasting using social media sentiment

Doctorate at Subtle Medical, Inc, United States

<img decoding="async" class="" src="https://s.w.org/images/core/emoji/15.0.3/svg/1f468-200d-1f393.svg" alt="👨‍🎓" width="42" height="42" /> Profiles

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f393/32.png" alt="🎓" data-emoji="🎓" aria-label="🎓" /> Education

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f4bc/32.png" alt="💼" data-emoji="💼" aria-label="💼" /> Professional Experience

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f4da/32.png" alt="📚" data-emoji="📚" aria-label="📚" /> Research & Publications

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f3c6/32.png" alt="🏆" data-emoji="🏆" aria-label="🏆" /> Patents, Honors & Awards

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f6e0/32.png" alt="🛠" data-emoji="🛠" aria-label="🛠" /> Professional Services

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f52c/32.png" alt="🔬" data-emoji="🔬" aria-label="🔬" /> Research Interests

Multimodal MRI reconstruction assisted with spatial alignment network

Task decomposition and synchronization for semantic biomedical image segmentation

Noise-aware standard-dose PET reconstruction using general and adaptive robust loss

Deep learning for fast and spatially constrained tissue quantification from highly accelerated data in magnetic resonance fingerprinting

Deep embedding convolutional neural network for synthesizing CT image from T1-Weighted MR image

Multimedia University, Malaysia

<img decoding="async" class="" src="https://s.w.org/images/core/emoji/15.0.3/svg/1f468-200d-1f393.svg" alt="👨‍🎓" width="42" height="42" /> Profiles

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f4cc/32.png" alt="📌" data-emoji="📌" aria-label="📌" /> Summary

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f393/32.png" alt="🎓" data-emoji="🎓" aria-label="🎓" /> Education

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f4bc/32.png" alt="💼" data-emoji="💼" aria-label="💼" /> Work Experience

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f52c/32.png" alt="🔬" data-emoji="🔬" aria-label="🔬" /> Research Interests

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f6e0_fe0f/32.png" alt="🛠️" data-emoji="🛠️" aria-label="🛠️" /> Skills

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f331/32.png" alt="🌱" data-emoji="🌱" aria-label="🌱" /> Research and Projects

Enhancing Indoor Localization with Temporally-Aware Separable Group Shuffled CNNs and Skip Connections

Automatic plant disease detection using computationally efficient convolutional neural network

Appearance Based Dynamic Hand Gesture Recognition Using 3D Separable Convolutional Neural Network.

Jahrom University, Iran

<img decoding="async" class="" src="https://s.w.org/images/core/emoji/15.0.3/svg/1f468-200d-1f393.svg" alt="👨‍🎓" width="42" height="42" /> Profiles

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f4cc/32.png" alt="📌" data-emoji="📌" aria-label="📌" /> Summary

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f393/32.png" alt="🎓" data-emoji="🎓" aria-label="🎓" /> Education

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f4bc/32.png" alt="💼" data-emoji="💼" aria-label="💼" /> Professional Experience

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f52c/32.png" alt="🔬" data-emoji="🔬" aria-label="🔬" /> Research Interests

Graph-based image captioning with semantic and spatial features

Integrated of Hyperspectral Imaging and Machine Learning Algorithms for Nondestructive Detection of Therapeutic Properties of Plants

Scene representation using a new two-branch neural network model

Face mask recognition using a custom CNN and data augmentation

Semantic embedding: scene image classification using scene-specific objects

Doctorate at ST. Anne’s College of Engineering and Technology, India

<img decoding="async" class="" src="https://s.w.org/images/core/emoji/15.0.3/svg/1f468-200d-1f393.svg" alt="👨‍🎓" width="42" height="42" /> Profiles

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f393/32.png" alt="🎓" data-emoji="🎓" aria-label="🎓" /> Early Academic Pursuits

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f3c5/32.png" alt="🏅" data-emoji="🏅" aria-label="🏅" /> Professional Endeavors

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f52c/32.png" alt="🔬" data-emoji="🔬" aria-label="🔬" /> Contributions and Research Focus

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f30d/32.png" alt="🌍" data-emoji="🌍" aria-label="🌍" /> Impact and Influence

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f4da/32.png" alt="📚" data-emoji="📚" aria-label="📚" /> Academic Contributions and Technical Expertise

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f469_200d_1f3eb/32.png" alt="👩‍🏫" data-emoji="👩‍🏫" aria-label="👩‍🏫" /> Teaching Experience

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f3c6/32.png" alt="🏆" data-emoji="🏆" aria-label="🏆" /> Recognitions and Awards

<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/16.0/1f680/32.png" alt="🚀" data-emoji="🚀" aria-label="🚀" /> Legacy and Future Contributions

Modified Exigent Features Block in JAN Net for Analysing SPECT Scan Images to Diagnose Early-Stage Parkinson’s Disease.

Improved classification accuracy for diagnosing the early stage of Parkinson’s disease using alpha stable distribution

Mathematical model for early stage identification of Parkinson’s disease using neurotransmitter: GABA

Diagnosis of Parkinson’s disease at an early stage using volume rendering SPECT image slices

Three dimensional analysis of SPECT images for diagnosing early Parkinson’s disease using Radial Basis Function kernel− Extreme learning machine

Mohammad Javad Ebadi at Chabahar Maritime University, Iran

<img decoding="async" class="" src="https://s.w.org/images/core/emoji/15.0.3/svg/1f468-200d-1f393.svg" alt="👨‍🎓" width="42" height="42" /> Profiles

Profiles

Early Academic Pursuits

Professional Endeavors

Contributions and Research Focus

Impact and Influence

Academic Citations and Publications

Technical Skills

Teaching and Mentorship

Legacy and Future Contributions

Profiles

Education

Research Experience

Core Technical Skills

AI & Research Expertise

Awards & Honors

Profiles

Education

Professional Experience

Research & Publications

Patents, Honors & Awards

Professional Services

Research Interests

Profiles

Summary

Education

Work Experience

Research Interests

Skills

Research and Projects

Profiles

Summary

Education

Professional Experience

Research Interests

Profiles

Early Academic Pursuits

Professional Endeavors

Contributions and Research Focus

Impact and Influence

Academic Contributions and Technical Expertise

Teaching Experience

Recognitions and Awards

Legacy and Future Contributions

Profiles

Early Academic Pursuits

Professional Endeavors

Contributions and Research Focus

Impact and Influence

Academic Citations and Recognitions

Technical Skills and Expertise

Teaching Experience and Pedagogical Contributions

Legacy and Future Contributions

Profiles

Summary

Education

Professional Experience

Research Interests

Profiles

Education

Professional Experience

Research Interests

Profiles

Education

Professional Experience

Research Interests