Mr. Mingi Kwon | Computer Engineering | Best Researcher Award

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Mr. Mingi Kwon | Computer Engineering | Best Researcher Award

University of California San Diego, United States

Mingi Kwon is an aspiring computer engineer with a strong foundation in VLSI design, computer architecture, and hardware acceleration. 🎓 Currently pursuing an MS in Electrical and Computer Engineering at the University of California, San Diego, he previously earned his BS in Electrical Engineering from Hanyang University, South Korea. With a deep interest in optimizing hardware for AI acceleration, he has worked on advanced projects involving reconfigurable systolic arrays, low-power circuit design, and RISC-V processor architectures. His dedication to high-performance computing and low-power hardware systems is evident through his research contributions and hands-on experience with industry-standard tools. 🚀

Publication Profile

ORCID

🎓 Education:

Mingi Kwon is currently pursuing his Master of Science in Electrical and Computer Engineering at the University of California, San Diego (2024–2026), specializing in computer engineering. He completed his Bachelor of Science in Electrical Engineering from Hanyang University, South Korea (2019–2024), graduating with an impressive GPA of 3.97/4.5. 📚 His academic journey has been focused on advanced coursework, including computer architecture, low-power VLSI design, and deep learning accelerators, equipping him with a strong foundation in hardware and system design.

💼 Experience:

Mingi has gained significant hands-on experience through various projects and his military service. During his undergraduate studies, he developed a Cyclone IV GX-Based Reconfigurable 2D Systolic Array for AI Acceleration, optimizing power consumption and chip area. He also worked on a RISC-V 5-stage Pipeline Processor with an advanced branch predictor, significantly improving execution efficiency. 🔧 Additionally, he served as a cybersecurity specialist and squad leader in the Republic of Korea Army (2020–2022), where he managed encrypted communications and network security while leading a team of 20 soldiers, earning a Distinguished Service Award. 🏅

🏆 Awards and Honors:

Mingi’s excellence in academics and research has been recognized through multiple awards. He was named to the Dean’s List (2022) with a perfect GPA of 4.5/4.5. 🎖️ He also received the National Logic Chip Design Track Scholarship (2023–2024), awarded by the South Korean government for outstanding achievements in electrical engineering. His leadership and dedication in the military earned him a Distinguished Service Award (2021–2022) for enhancing work efficiency and team collaboration.

🔬 Research Focus:

Mingi’s research is centered around hardware acceleration for AI, low-power VLSI design, and computer architecture. 🖥️ His work on systolic arrays focuses on optimizing deep learning computations with reconfigurable architectures, improving efficiency in sparse neural networks. He has also explored low-power circuit design, reducing leakage power and optimizing combinational logic for improved energy efficiency. His expertise extends to processor architecture, particularly RISC-V pipeline design and branch prediction, enhancing execution speed and minimizing stalls.

🔚 Conclusion:

Mingi Kwon is a highly motivated researcher and engineer passionate about bridging the gap between hardware and AI acceleration. 🚀 With extensive experience in VLSI design, digital systems, and processor architecture, he is committed to advancing high-performance, energy-efficient computing systems. His technical expertise, research achievements, and leadership skills position him as a promising innovator in the field of computer engineering. 💡

📄 Publication:

Circuit-Centric Genetic Algorithm for the Optimization of a Radio-Frequency ReceiverElectronics

DOI: 10.3390/electronics14040770

Obsa Gilo Wakuma | Computer Science | Best Researcher Award

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Dr. Obsa Gilo Wakuma | Computer Science | Best Researcher Award

Ass. Prof, Wallaga University, Ethiopia

Dr. Obsa Gilo Wakuma is a dedicated computer scientist specializing in deep learning and domain adaptation. With extensive experience in academia, he has contributed significantly to the field through his research and teaching. Dr. Obsa has held various positions at Wallaga University, Ethiopia, and currently serves as a research scholar at the Indian Institute of Technology Patna, India. His expertise spans multiple programming languages and database management systems, making him a versatile and valuable contributor to the field of computer science.

Profile

Strengths for the Award:

  1. Extensive Research Background: Dr. Obsa Gilo has a robust academic background, culminating in a Ph.D. in Computer Science and Engineering with a focus on deep learning approaches for efficient domain adaptation. His research in domain adaptation, particularly in sensor data and image classification, showcases his innovative contributions to the field.
  2. Publications: Dr. Gilo has a significant number of publications in reputed journals and conference proceedings. Notable among them are:
    • “Kernel bures metric for domain adaptation in sensor data” in Expert System with Applications (2024)
    • “Subdomain adaptation via correlation alignment with entropy minimization for unsupervised domain adaptation” in Pattern Analysis and Applications (2024)
    • “Rdaot: Robust unsupervised deep sub-domain adaptation through optimal transport for image classification” in IEEE Access (2023)
  3. Teaching and Mentoring: His employment history includes roles such as Lecturer and Graduate Assistant at Wallaga University, demonstrating his commitment to education and mentoring the next generation of scholars.
  4. Skills and Competencies: Dr. Gilo possesses strong technical skills in various programming languages, databases, and web development technologies, along with proficiency in English, Afaan Oromoo, and Amharic. This multilingual ability enhances his capacity to engage with diverse communities.
  5. Community Service: His experience includes academic research, teaching, training, consultation, and community service, reflecting a well-rounded professional dedicated to both academic and societal contributions.

Areas for Improvement:

  1. Practical Community Impact: While Dr. Gilo has an impressive academic and research portfolio, there could be more emphasis on the practical application of his research directly benefiting local communities. Highlighting specific projects or initiatives where his work has directly impacted community development would strengthen his case.
  2. Collaboration with Local Institutions: Greater collaboration with local institutions and involvement in projects addressing community-specific issues could further enhance his profile. Establishing partnerships with local universities, NGOs, or governmental bodies to implement his research findings in real-world settings would be beneficial.
  3. Visibility and Outreach: Increasing the visibility of his work through public lectures, community workshops, or outreach programs can help in demonstrating the broader societal impact of his research. Engaging with the community through these platforms can showcase the practical benefits of his research.

 

Education: 🎓

Dr. Obsa Gilo Wakuma holds a Ph.D. in Computer Science and Engineering from the Indian Institute of Technology Patna, with a thesis on “Deep Learning Approaches for Efficient Domain Adaptation.” He earned his M.Sc. in Computer Science from Wallaga University, where he developed an Information Extraction Model for Afaan Oromo news texts. Dr. Obsa also holds a B.Sc. in Computer Science from Wallaga University and has a strong foundation from Sibu Sire Preparatory and High School.

Experience: 💼

Dr. Obsa’s professional journey includes roles such as Recorder and Laboratory Technician at Wallaga University. He progressed to become a Graduate Assistant, Lecturer, and finally a Research Scholar at IIT Patna. His career reflects a blend of administrative, technical, and academic responsibilities, showcasing his diverse skill set and commitment to the field.

Research Interests: 🔍

Dr. Obsa’s research interests lie in deep learning, domain adaptation, and unsupervised learning. He has focused on developing efficient methods for domain adaptation in sensor data and image classification, contributing to several high-impact publications. His work aims to enhance the applicability and robustness of machine learning models in diverse environments.

Awards: 🏆

Dr. Obsa has been recognized for his academic excellence and research contributions throughout his career. He has received accolades for his innovative work in domain adaptation and deep learning, highlighting his role as a prominent researcher in the field of computer science.

Publications

  1. Unsupervised Sub-Domain Adaptation Using Optimal Transport. Journal of Visual Communication and Image Representation, 94, 103857. Cited by: 1 article.
  2. Kernel Bures Metric for Domain Adaptation in Sensor Data. Expert System with Applications, 255(Part C), 124725. Cited by: 1 article.
  3. Subdomain Adaptation via Correlation Alignment with Entropy Minimization for Unsupervised Domain Adaptation. Pattern Analysis and Applications, 27(1), 13. Cited by: 1 article.
  4. RDAOT: Robust Unsupervised Deep Sub-Domain Adaptation through Optimal Transport for Image Classification. IEEE Access. Cited by: 1 article.
  5. Integration of Discriminate Features and Similarity Preserving for Unsupervised Domain Adaptation. In 2022 IEEE 19th India Council International Conference (INDICON), pp. 1–6. Cited by: 1 article.