Deep Learning-Enabled Skin Disease Diagnosis: A Systematic Review of Techniques and Trends
Published by
Scientific Reports (Under Review)
Summary
Conducted a systematic review of deep learning techniques and trends for skin disease diagnosis.
Highly accomplished Computer Engineer with over seven years of academic research and teaching experience, specializing in Data Science, Machine Learning, and Artificial Intelligence. Currently advancing biomedical engineering through deep learning model development for surface EMG-based upper limb movement control. Possesses a strong foundation in theoretical and scientific data science, poised to contribute innovative solutions in challenging research and development environments.
Researcher
Messina ME, Sicily, Italy
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Summary
Led a funded research project focused on developing advanced deep learning models for precise upper limb movement control using surface electromyographic (sEMG) signals.
Highlights
Led a funded research project to develop advanced deep learning (DL) models for upper limb movement control using surface electromyographic (sEMG) signals.
Designed and implemented innovative DL architectures, contributing to the advancement of biomedical engineering and rehabilitation systems.
Optimized sEMG data processing pipelines, improving model accuracy and real-time performance for critical applications.
Lecturer
Adama, Oromia, Ethiopia
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Summary
Contributed to the computer science and engineering department through teaching, research, student mentorship, and active participation in academic program development.
Highlights
Developed and delivered a diverse curriculum across 5+ computer science and engineering courses, including Mobile Computing and Embedded Systems, to undergraduate students.
Engaged in active research, publishing multiple papers in reputable journals and conferences, significantly contributing to academic knowledge.
Mentored and supervised over 15 undergraduate students on research projects, fostering their technical skills and academic growth.
Contributed to departmental initiatives, enhancing academic programs and curriculum development to meet evolving industry demands.
Lecturer
Arba Minch, SNNPR, Ethiopia
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Summary
Provided over five years of dedicated academic instruction, research, and student mentorship across diverse electrical and computer engineering disciplines.
Highlights
Taught a broad range of 10+ undergraduate courses in electrical and computer engineering over 5.5 years, impacting hundreds of students.
Conducted impactful research in AI, deep learning, NLP, and health monitoring systems, resulting in multiple publications and project collaborations.
Provided academic guidance and mentorship to students, supporting their career development and successful project completion.
Collaborated with colleagues on 3+ research projects and grant proposals, securing vital resources for academic initiatives.
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Master of Science
Computer Engineering
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Bachelor of Science
Electrical and Computer Engineering
Published by
Scientific Reports (Under Review)
Summary
Conducted a systematic review of deep learning techniques and trends for skin disease diagnosis.
Published by
Scientific Reports (Under Review)
Summary
Developed an efficient skin disease classification method using attention-enhanced CNN-Transformer fusion.
Published by
Scientific Reports (Under Review)
Summary
Proposed depth-wise separable deep networks with late fusion strategies for automated skin disease classification.
Published by
Scientific Reports (Under Review)
Summary
Explored innovative deep learning solutions for enhanced e-commerce recommendation systems, focusing on personalization, diversity, and real-time adaptability.
Summary
Explored the impact of normalizing and utilizing Amharic informal opinionated features for sentiment analysis.
Summary
Investigated sputum smear quality inspection through an ensemble feature extraction approach.
Summary
Authored research on accelerating deep neural network training using Field Programmable Gate Arrays.
Summary
Contributed to the design and implementation of a heart beat monitoring system utilizing a PIC microcontroller.
Issued By
NVIDIA Deep Learning Institute
Issued By
Great Learning
Issued By
NVIDIA Deep Learning Institute
Issued By
Stanford University
Issued By
Arba Minch University
Issued By
Arba Minch University
Issued By
Arba Minch University
Issued By
Arba Minch University
Issued By
Arba Minch University
Python, C++, PHP, HTML, JavaScript, CSS, MySQL.
Deep Learning, Machine Learning, Data Science, Artificial Intelligence (AI), Natural Language Processing (NLP), Data Analysis, Data Visualization, SQL, Databases.
Cloud Computing (AWS, IBM Cloud), Git, GitHub, Linux Commands, Shell Scripting, Software Engineering.
Embedded Systems, Robotics, PIC Microcontroller, Jetson Nano, Video Analytics.
Surface Electromyography (sEMG), Health Monitoring Systems, Heart Rate Monitoring, Oxygen Level (SpO2), Blood Pressure (BP), Rehabilitation Systems.
Academic Mentorship, Curriculum Development, Research Project Management, Grant Proposals, Scientific Publication, Peer Review.
Microsoft Word, Excel, PowerPoint, Access, Outlook.
Reading (books, scientific papers, newspapers), Sports, Nature admiration.
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Summary
As a Researcher, led a funded research grant project focusing on applying machine learning and EMG signal processing to develop rehabilitation systems.
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Summary
Collaborated as a co-author on a research project funded by Adama Science and Technology University (ASTU), focusing on the application of Artificial Neural Networks for hateful meme detection.
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Summary
Served as a Principal Investigator (PI) for a research project funded by Arba Minch University (AMU), focusing on developing a comprehensive health monitoring system.