Leyi Zhao | Computer Science | Best Researcher Award

Dr. Leyi Zhao | Computer Science | Best Researcher Award

Doctor, Beijing University of Chinese Medicine, China

Dr. Leyi Zhao is a dedicated clinical doctoral researcher in Integrative Medicine at the prestigious Beijing University of Chinese Medicine. With a keen interest in digestive tract diseases, Dr. Zhao specializes in studying precancerous lesions, tumors, and the intricate relationship between the immune environment and disease progression. Passionate about blending traditional medicine with modern computational techniques, Dr. Zhao integrates computer language and data analysis to establish innovative prognostic models, enhancing clinical applications. With multiple completed and ongoing research projects, Dr. Zhao’s contributions to the field of immunotherapy and colorectal cancer prognosis are highly impactful.

Publication Profile

ORCID

🎓 Education

Dr. Zhao is currently pursuing a doctorate in Integrative Medicine at Beijing University of Chinese Medicine, a renowned institution for traditional and modern medical research. This academic journey has equipped Dr. Zhao with a strong foundation in both traditional Chinese medical practices and cutting-edge clinical research methodologies.

💼 Experience

With extensive research experience, Dr. Zhao has led and contributed to multiple research projects focusing on colorectal cancer, immune microenvironments, and predictive modeling in oncology. Through a blend of experimental studies and computational approaches, Dr. Zhao has contributed significantly to understanding the impact of tertiary lymphoid structures (TLS) on tumor prognosis and immune response. In addition to academic research, Dr. Zhao has been involved in consultancy and industry-based projects, furthering the practical application of scientific findings.

🏆 Awards and Honors

Dr. Zhao’s research excellence has been recognized through publications in high-impact journals indexed in SCI and Scopus. The innovative work in colorectal cancer prognosis and immunotherapy has garnered citations and recognition within the scientific community. As an active contributor to the field, Dr. Zhao has been nominated for the prestigious Best Researcher Award at the Cryogenicist Global Awards.

🔬 Research Focus

Dr. Zhao’s primary research focus lies in immunotherapy for tumors, particularly in colorectal cancer. The groundbreaking research involves developing a TLS-based prognostic model that explores immune cell interactions within tumors. This model holds potential for predicting patient prognosis and treatment responsiveness, offering valuable insights into personalized medicine. Furthermore, Dr. Zhao’s interdisciplinary approach integrates network pharmacology, computational modeling, and traditional Chinese medicine, enhancing the precision and effectiveness of cancer treatments.

🔗 Publications

The Impact of Tertiary Lymphoid Structures on Tumor Prognosis and the Immune Microenvironment in Colorectal Cancer. Biomedicines, 2025; 13(3):539
🔗 DOI: 10.3390/biomedicines13030539

 Limonin ameliorates indomethacin-induced intestinal damage and ulcers through Nrf2/ARE pathway. Immun Inflamm Dis, 2023; 11(2):e787
🔗 DOI: 10.1002/iid3.787

Chinese patent herbal medicine (Shufeng Jiedu capsule) for acute upper respiratory tract infections: A systematic review and meta-analysis. Integr Med Res, 2021; 10(3):100726
🔗 DOI: 10.1016/j.imr.2021.100726

Deciphering the Mechanism of Siwu Decoction Inhibiting Liver Metastasis by Integrating Network Pharmacology and In Vivo Experimental Validation. Integr Cancer Ther, 2024; 23:15347354241236205
🔗 DOI: 10.1177/15347354241236205

🔚 Conclusion

Dr. Leyi Zhao’s research contributions are shaping the future of colorectal cancer treatment and immune microenvironment analysis. With a strong foundation in integrative medicine and a passion for computational research, Dr. Zhao continues to push the boundaries of medical science, making a profound impact on oncology and personalized medicine. As a nominee for the Best Researcher Award, Dr. Zhao’s work exemplifies innovation, dedication, and a commitment to improving patient outcomes worldwide. 🌍

Mr. Mingi Kwon | Computer Engineering | Best Researcher Award

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

Qutaiba Alasad | Computer Engineering Security | Best Researcher Award

Assoc. Prof. Dr. Qutaiba Alasad | Computer Engineering Security | Best Researcher Award

Cybersecurity, previously at University of Central Florida in USA and now at Tikrit University in Iraq

Qutaiba Abdullah Hasan Alasad is an Associate Professor and Head of the Department of Control and Computer Engineering at the University of Tikrit, Iraq. With a Ph.D. in Computer Engineering from the University of Central Florida (UCF), USA, he has developed expertise in hardware security, particularly in the areas of logic encryption, obfuscation techniques, and secure design for emerging devices. His research work focuses on enhancing hardware protection, preventing side-channel attacks, and leveraging memory computing for secure and high-performance systems. He has also been involved in various presentations and has earned several prestigious awards for his contributions to computer engineering and cybersecurity. 📚🔒

Publication Profile

Google Scholar

Education

Dr. Alasad completed his Ph.D. in Computer Engineering from the University of Central Florida (UCF) in 2020, with a perfect GPA of 4.0/4.0. His dissertation, titled “Provably Trustworthy and Secure Hardware Design with Low Overhead,” was supervised by Prof. Yuan Jiann-Shiun. He also holds an M.Sc. in Computer Engineering from the University of Mosul, Iraq, where he designed a math pipeline processor using VHDL and implemented it on Spartan-3E. 🎓🇮🇶

Experience

Dr. Alasad has served in various prestigious positions, including the Head of the Department at the University of Tikrit’s College of Petroleum and Minerals Engineering and Dean of the College of Petroleum Systems Control Engineering. He was also involved in several roles at the University of Central Florida, where he worked under the supervision of Prof. Jiann-Shiun Yuan. His vast experience spans over teaching, research, and administrative roles. 💼👨‍🏫

Awards and Honors

Dr. Alasad has received several notable recognitions, including a Travel Award from the ICCD Conference in 2017 and a complimentary annual membership from Gabriele Kotsis, President of the ACM journal, in 2020. He has presented his research at various symposiums, covering topics such as Internet of Things (IoT) applications and power electronics systems simulation. 🏅🌍

Research Focus

Dr. Alasad’s research interests are centered around hardware security, particularly logic encryption and obfuscation techniques, side-channel attack prevention, and the application of emerging devices to enhance hardware security. He is also focused on designing secure memory systems using ReRAM and creating high-performance machine learning accelerators. Additionally, his work on big data security and cybersecurity protection based on machine learning is highly impactful in the domain. 🔐💻

Conclusion

Qutaiba Alasad’s interdisciplinary expertise and contributions to hardware security, especially in the realm of logic encryption and emerging devices, position him as a leader in the field. His academic achievements, coupled with his extensive work in cybersecurity, make him a prominent figure in the engineering community. 🏆👨‍💻

Publications

Design a Pipelined Math Processor, Doubling Its Speed and Implementing It on FPGA

Al-Rafidain Engineering Journal (AREJ), Volume 22, Issue 4, Pages 131-148, 2014

Cited by: 10+

E2LEMI: Energy-Efficient Logic Encryption Using Multiplexer Insertion

Electronics, vol. 6, issue 1, 2017

Cited by: 50+

Logic Locking Using Hybrid CMOS and Emerging SiNW FETs

Electronics, vol. 6, issue 3, 2017

Cited by: 30+

Ultra-Low-Power Design and Hardware Security Using Emerging Technologies for Internet of Things

Electronics, vol. 6, issue 3, 2017

Cited by: 40+

Logic Obfuscation against IC Reverse Engineering Attacks with Low Overhead

ACM Trans. TODAES, 2020

Cited by: 75+

Resilient and Secure Hardware Devices Using ASL

ACM journal on emerging technologies in computing systems, 2021

Cited by: 20+

Multi-Tier 3D IC Physical Design with Analytical Quadratic Partitioning Algorithm Using 2D P&R Tool

Electronics, 2021

Cited by: 15+

Mitigation of Black-Box Attacks on Intrusion Detection Systems-Based ML

MDPI Computers, 2022

Cited by: 25+