Changhwan Shin | Semiconductor | Research Excellence Award

Prof. Changhwan Shin | Semiconductor | Research Excellence Award

Prof. Changhwan Shin | Semiconductor | Professor at Korea University | South Korea

Semiconductor expertise defines the academic and professional profile of Prof. Changhwan Shin, a distinguished scholar and leader in nanometer-scale semiconductor circuits, devices, and technology. Prof. Changhwan Shin is currently a Professor in the School of Electrical Engineering at Korea University and serves as Vice Dean for Planning in the College of Engineering, bringing together deep academic insight and strategic leadership. He earned his Ph.D. in Electrical Engineering and Computer Sciences from the University of California, Berkeley, under the guidance of Prof. Tsu-Jae King Liu and Prof. Borivoje Nikolić, following a top-honors B.S. degree from Korea University. Prof. Changhwan Shin’s professional experience spans academia and industry, including senior roles at the University of Seoul, Sungkyunkwan University, SK hynix as an Independent Director, and industrial positions at Xilinx and IBM Microelectronics. His research interests focus on advanced electron device architectures for SoC memory and logic, steep-switching devices such as negative capacitance and feedback FETs, TCAD-based variability analysis of nanometer-scale devices, and low-level digital and analog circuit design methodologies. Prof. Changhwan Shin’s research skills integrate device physics, circuit–technology co-design, and semiconductor process modeling. His awards and honors include repeated leadership appointments such as Vice Dean roles and recognition for academic excellence and technological impact. In conclusion, Prof. Changhwan Shin exemplifies innovation, leadership, and sustained contribution to the advancement of semiconductor engineering and education worldwide.

Citation Metrics (Google Scholar)

5000

4000

3000

2000

1000

0

Citations
4820
i10index
106

h-index
38

🟦Citations      🟥Documents      🟩h-index

View Google Scholar Profile

Featured Publications

Feedback FET: A Novel Transistor Exhibiting Steep Switching Behavior at Low Bias Voltages
A. Padilla, C.W. Yeung, C. Shin, C. Hu, T.J.K. Liu
IEEE International Electron Devices Meeting, 2008
Citations: 249

Negative Capacitance Field Effect Transistor with Hysteresis-Free Sub-60 mV/decade Switching
J. Jo, C. Shin
IEEE Electron Device Letters, 2016
Citations: 240

Negative Capacitance in Organic/Ferroelectric Capacitor to Implement Steep Switching MOS Devices
J. Jo, W.Y. Choi, J.D. Park, J.W. Shim, H.Y. Yu, C. Shin
Nano Letters, 2015
Citations: 214

Study of Random Dopant Fluctuation Effects in Germanium-Source Tunnel FETs
N. Damrongplasit, C. Shin, S.H. Kim, R.A. Vega, T.J.K. Liu
IEEE Transactions on Electron Devices, 2011
Citations: 185

Negative Capacitance FinFET with Sub-20 mV/decade Subthreshold Slope and Minimal Hysteresis of 0.48 V
E. Ko, J.W. Lee, C. Shin
IEEE Electron Device Letters, 2017
Citations: 141

Vertical Tunnel FET: Design Optimization with Triple Metal-Gate Layers
E. Ko, H. Lee, J.D. Park, C. Shin
IEEE Transactions on Electron Devices, 2016
Citations: 124

Muhammad Tahir Naseem | Electronic Engineering | Best Research Article Award

Dr. Muhammad Tahir Naseem | Electronic Engineering | Best Research Article Award

Dr. Muhammad Tahir Naseem | Electronic Engineering | Research Professor at Yeungnam University | South Korea

Dr. Muhammad Tahir Naseem is a leading academic and researcher in the field of computer science, with a specialization in artificial intelligence, computer vision, and image processing. His work is recognized internationally for contributing to cutting-edge solutions in medical diagnostics, intelligent systems, and secure image communication. As a faculty member at Yeungnam University, Dr. Muhammad Tahir Naseem continues to advance knowledge through interdisciplinary research, impactful publications, and academic mentorship. With a strong foundation in theoretical and applied domains, he has consistently demonstrated excellence across various research activities and collaborative networks. His reputation for precision, innovation, and scholarly engagement reflects his commitment to both scientific inquiry and societal benefit.

Academic Profile:

Google Scholar

Education:

Dr. Muhammad Tahir Naseem completed his doctoral studies in Electrical and Computer Engineering, focusing on intelligent diagnostic systems and secure signal processing methodologies. His academic journey has been rooted in analytical depth and interdisciplinary orientation, combining core principles of artificial intelligence with real-world applications in healthcare technologies and multimedia systems. Prior to his doctoral research, he obtained strong foundational training in computing and electronics, equipping him with the technical competencies needed to work across a wide range of academic and industrial projects. His educational background laid the groundwork for a successful research career, which has since evolved through both theoretical development and experimental validations.

Experience:

Dr. Muhammad Tahir Naseem possesses extensive teaching and research experience in both national and international institutions. He has held academic roles that involve supervising graduate-level research, delivering specialized courses, and coordinating collaborative initiatives across departments and research labs. He has worked closely with multidisciplinary teams to execute research projects involving medical imaging, wireless communication, and intelligent systems. Dr. Muhammad Tahir Naseem’s academic service also includes peer reviewing for indexed journals and contributing to scientific program committees for international conferences. His experience has enabled him to develop and guide solutions that integrate AI models with practical outcomes in healthcare, communication systems, and data security.

Research Interest:

Dr. Muhammad Tahir Naseem’s primary research interests span artificial intelligence, computer vision, signal and image processing, and intelligent diagnosis. His current focus is on applying deep learning models to medical imaging for disease detection and prognosis, particularly in the areas of histopathology and pathological gait analysis. He is also exploring advancements in resource allocation for wireless communication systems using neural networks and fuzzy logic. Another area of interest includes secure image watermarking and digital authentication techniques using chaos theory and residue number systems. His interdisciplinary research is aimed at improving real-time diagnostic capabilities, data integrity, and resource efficiency in complex systems.

Award:

Dr. Muhammad Tahir Naseem has been consistently recognized for his academic excellence and research contributions in the field of intelligent systems. His work in medical image analysis and adaptive communication networks has earned appreciation from peers and international collaborators. He has been nominated for awards that acknowledge high-impact research, publication quality, and innovation in computing technologies. His leadership in collaborative projects and dedication to solving real-world problems through AI-driven solutions positions him as a strong candidate for academic and research-based honors. His research outputs not only contribute to academic knowledge but also deliver tangible benefits to healthcare and digital communication systems.

Selected Publications:

  • “Malignancy detection in lung and colon histopathology images using transfer learning with class selective image processing” – Published in 2022, with 241 citations

  • “Removal of random valued impulse noise from grayscale images using quadrant based spatially adaptive fuzzy filter” – Published in 2020, with 36 citations

  • “Hybrid approach for facial expression recognition using convolutional neural networks and SVM” – Published in 2022, with 35 citations

  • “Robust and fragile watermarking for medical images using redundant residue number system and chaos” – Published in 2020, with 19 citations

Conclusion:

Dr. Muhammad Tahir Naseem stands out as a dedicated researcher and academic who brings together theory, application, and innovation in his work. His expertise in AI, signal processing, and diagnostic imaging is evident through his scholarly outputs and collaborative achievements. Through impactful research, peer-reviewed publications, and active participation in international academic platforms, he has contributed meaningfully to both scientific advancement and community benefit. Dr. Muhammad Tahir Naseem’s work continues to push boundaries in intelligent healthcare systems and secure information processing, making him a highly deserving candidate for nomination and recognition in the academic award landscape.