AI engineer and PhD candidate specializing in vision-based AI, passionate about driving innovation and solving real-world challenges.
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Professional Experience and Academic Achievements.
Doctoral dissertation work focuses on medical data analysis for early identification and diagnosis of Alzheimer's disease and Parkinson's disease through the application of machine learning, deep learning, information fusion, and multitasking analysis. A trustworthy clinical decision support system is the target of my research. The research employs cutting-edge technologies such as explainability, interpretability, fairness, robustness, generalization, data privacy, and security. I secured a GPA of 4.27 out of 4.5.
My dissertation project, “Electroencephalography (EEG) based Brain-Computer-Interface (BCI) for Controlling Real-time 2D Robot Arm,” examines the sustain and development of a disable person having abnormal motor functions to do their daily task themselves by taking signals form their brains. Built a 2R Manipulator Prototype, worked with Arduino for signals transferred, Matlab SSVEP Tool Programming and signal processing Tool, Python Programming for receive signals from brain by Emotiv EPOC device.
Bachelor's degree final project entitled "Cyclic Grass Cutter with Shaft-Gear Mechanism". A shaft-gear driven cycle was assembled that is cost-effective and also drive a cutter. A grass cutter is attached to cut the leaves when shortage of power. As a team leader, worked on mechanical components designed, manufacturing them, and prepared the first draft of the thesis.
Showcasing key milestones and professional accreditations that demonstrate a commitment to excellence and ongoing development in the field.
Professional Skillset and Core Competencies.
Explore my projects showcasing innovative AI solutions, from vision-based musical instrument to smart factory development.
Stay updated with the latest advancements in AI-driven research, cutting-edge projects, and insightful discussions on emerging technologies in my blog and news section.
Successful implementation of two groundbreaking A.I. solutions at the Hyundai Steel Factory in Dangjin city, Korea, in collaboration with KIA Motors Korea in enhancing safety measures and predicting defects early on.
A interview is posted in the official webzine of Sungkyunkwan University. It is a combination of SKKU of Sungkyunkwan University and webzine, which means internet magazine. Sungkyun Webzine, which has been officially published since 2001, contains various news and interesting and useful content from Sungkyunkwan University.
E-Forest Tech Day is an event where Hyundai Motor Company, Kia Manufacturing Solutions Headquarters and partners share the results of their research and development to accelerate software-centric factories implementation through manufacturing technology innovation.
Offering freelance expertise in AI, computer vision, and data science to help bring innovative solutions to your projects—let's work together to turn your ideas into reality!
Feel free to reach out with any inquiries or collaboration ideas—I am always open to discussing new projects and opportunities to connect.