Prof. Dr. Yu-Chun Lie | Wireless Awards | Best Researcher Award

Prof. Dr. Yu-Chun Lie | Wireless Awards | Best Researcher Awardย 

Prof. Dr. Yu-Chun Lie, Texas Tech University, United States

Donald Y.C. Lie, Ph.D., is the K.S. Lu Regents Chair Professor in the Department of Electrical and Computer Engineering at Texas Tech University, where he also serves as an Adjunct Professor in the Department of Surgery at TTUHSC. He earned his degrees in Electrical Engineering from National Taiwan University and the California Institute of Technology. Dr. Lie has held prominent positions, including Chair Professor at National Yangming Chiao Tung University in Taiwan and leadership roles at various technology companies, such as Director of RFIC Design at Dynamic Research Corporation and Microtune Inc. His research focuses on the design of efficient power amplifiers for mm-wave 5G and 6G applications, with numerous publications in prestigious journals and conferences. Notable works include invited papers and chapters on energy efficiency in RF hardware design, as well as contributions to advancements in wireless communication technologies. Dr. Lie has received recognition for his work, including best paper awards and honors for his innovative research in the field.

Professional Profile:

SCOPUS

Suitability for the Award

Donald Y.C. Lieโ€™s groundbreaking research, sustained academic output, leadership in education, and contributions to advanced technologies align perfectly with the criteria for the Research for Best Researcher Award. His achievements not only demonstrate excellence in research but also reflect a commitment to community impact and scientific innovation, making him a highly deserving candidate.

๐ŸŽ“ Education

  • National Taiwan University
    Location: Taipei, Taiwan
    Major/Area of Study: Electrical Engineering (E.E.)
    Degree: Ph.D.
  • California Institute of Technology
    Location: Pasadena, CA, USA
    Major/Area of Study: Electrical Engineering (E.E.)
    Degree: M.S. & B.S.

๐Ÿ’ผ Work Experience

  1. K.S. Lu Regents Chair Professor, ECE Dept. & Adjunct Professor, Dept. of Surgery
    Texas Tech University, Lubbock, TX
  2. Chair Professor, College of Electrical Engineering
    National Yangming Chiao Tung University (NYCU), Hsin-Chu, Taiwan
  3. AFRL (Air Force Research Lab) Summer Faculty Fellowship Program
    Dayton, Ohio, USA
  4. K.S. Lu Regents Chair Associate Professor, ECE Dept.
    Texas Tech University (TTU), Lubbock, TX
  5. Director, RFIC Design and Test
    Dynamic Research Corp. (@ US NAVY SPAWAR, San Diego, CA)
  6. Director, SYS Technologies Inc. (@ US NAVY SPAWAR, San Diego, CA)
  7. Visiting Lecturer, ECE Dept.
    University of California, San Diego (UCSD)
  8. Director, RFIC Design and Applications
    Microtune Inc., San Diego, CA
  9. Manager, RFIC Design Group
    Lincom Wireless Corp., Los Angeles, CA
  10. Advisory RFIC Design Engineer
    Communications R&D Center, IBM, CA
  11. Member of Technical Staff
    Silicon Wave (Now Qualcomm Inc.), San Diego, CA
  12. Staff Engineer
    Rockwell International, Newport Beach, CA

๐ŸŒŸ Achievements

  1. Invited Papers and Publications:
    • Design of Broadband Highly Efficient Linear Power Amplifiers for mm-Wave 5G (Electronics, 2022)
    • A Highly Efficient 18 – 40 GHz Linear Power Amplifier in 40 nm GaN for mm-Wave 5G (IEEE MWCL, 2021)
    • A Review of 5G Power Amplifier Design at cm-Wave and mm-Wave Frequencies (Wireless Communications and Mobile Computing, 2018)
  2. Invited Book Chapter:
    • “Energy Efficiency Enhancement and Linear Amplifications: An Envelope-Tracking (ET) Approach” in RF and Mm-Wave Power Generation in Silicon (Elsevier, 2015)
  3. Best Student Poster Paper Competition Winner (IEEE Texas Symposium on Wireless and Microwave Circuits and Systems, 2022)
  4. Keynote Speaker:
    • โ€œRF Hardware Design for 5G mm-Wave and 6G Revolutions: Challenges and Opportunitiesโ€ (IEEE ICCE-TW, 2021)

๐Ÿ† Awards and Honors

  • AFRL Summer Faculty Fellowship
    Recognized for contributions in research and teaching.
  • Best Student Poster Paper Competition Winner
    Awarded for exceptional research presentation.

Publicationย Top Notes

A Broadband Millimeter-Wave 5G Low Noise Amplifier Design in 22 nm Fully Depleted Silicon-on-Insulator (FD-SOI) CMOS

5G FR2-Band PA Performance Degradation in 40-nm GaN HEMTs with Potential Design Solutions

Broadband High-Efficiency Watt-Level Millimeter-Wave GaN Power Amplifier for Potential Robust and Cost-Effective 5G RF Front-End Design

Effective Digital Predistortion (DPD) on a Broadband Millimeter-Wave GaN Power Amplifier Using LTE 64-QAM Waveforms

The 2023 RFIC Symposium [IMS2023]

A Feasibility Study of Remote Non-Contact Vital Signs (NCVS) Monitoring in a Clinic Using a Novel Sensor Realized by Software-Defined Radio (SDR)

Dr. Fahman Saeed | Signal Distortion Awards | Best Researcher Award

Dr. Fahman Saeed | Signal Distortion Awards | Best Researcher Awardย 

Dr. Fahman Saeed, Imam Mohammad Ibn Saud Islamic University (IMSIU), Saudi Arabia

Dr. Fahman Saeed is an Assistant Professor in the College of Computer and Information Sciences at Imam Mohammad Ibn Saud Islamic University (IMSIU) in Riyadh, Saudi Arabia. With a Ph.D. in Computer Science from King Saud University, his research focuses on deep learning models, particularly for automatic diabetic retinopathy screening. He has contributed significantly to various research projects, including the development of fingerprint interoperability solutions and privacy-protected breast cancer screening systems, earning multiple ISI papers, patents, and conference presentations. Dr. Saeed also has extensive experience in machine learning, specializing in PyTorch, TensorFlow, and large language models. In addition to his academic achievements, he actively participates in professional activities, such as curriculum development and leading workshops on AI, NLP, and generative AI. His dedication to education and research, coupled with his expertise in artificial intelligence, continues to influence both his academic institution and the broader scientific community.

Professional Profile:

ORCID

Suitability for Best Researcher Award: Fahman Saeed

Fahman Saeed is exceptionally suited for the Best Researcher Award due to his outstanding contributions to the field of computer science, particularly in the areas of deep learning, machine learning, and artificial intelligence. With a robust academic background and extensive experience in both research and teaching, Dr. Saeed has demonstrated leadership in advancing the application of machine learning technologies in critical areas like medical diagnostics and data security.

Education ๐ŸŽ“

  • Ph.D. in Computer Science
    • Institution: King Saud University, Saudi Arabia ๐ŸŽ“
    • Graduation: November 2021 ๐Ÿ“…
    • Dissertation: Developing an auto deep learning model with less complexity and high performance for automatic diabetic retinopathy screening ๐Ÿง ๐Ÿ’ป
  • M.Sc. in Computer Science
    • Institution: King Saud University, Saudi Arabia ๐ŸŽ“
    • Graduation: May 2014 ๐Ÿ“…
  • B.Sc. in Computer Science
    • Institution: King Saud University, Saudi Arabia ๐ŸŽ“
    • Graduation: February 2007 ๐Ÿ“…

Academic Experience ๐Ÿ“š

  • Assistant Professor
    • Institution: College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia ๐Ÿซ
    • Duration: 2022 to Present โณ
    • Responsibilities: Teaching courses in Artificial Intelligence ๐Ÿค–, Natural Language Processing ๐Ÿ’ฌ, Algorithm Design and Analysis ๐Ÿ’ป, Image Processing ๐Ÿ–ผ๏ธ, and Computer Vision ๐Ÿ‘€
  • Lecturer (Part-time)
    • Institution: King Saud University, Riyadh, Saudi Arabia ๐ŸŽ“
    • Duration: 2017 to 2021 โณ
  • Researcher
    • Institution: King Saud University, Riyadh, Saudi Arabia ๐Ÿงช
    • Duration: March 2015 to 2021 โณ
    • Projects:
      • Automatic Diabetic Retinopathy Screening ๐Ÿฉบ๐Ÿ‘๏ธ
        • Achievements: Two ISI papers ๐Ÿ“„
      • Identification of Fingerprint Interoperability ๐Ÿง‘โ€โš–๏ธ
        • Achievements: One patent, one ISI paper, two conference papers ๐Ÿ“‘
      • Cloud-Based Privacy-Protected Computer-Aided Diagnosis System for Breast Cancer Screening ๐Ÿฉป
        • Achievements: One ISI paper ๐Ÿ“„

Publicationย Top Notes

Adaptive Renewable Energy Forecasting Utilizing a Data-Driven PCA-Transformer Architecture

Blockchain-Based Quality Assurance System for Academic Programs
Optimal Sizing and Placement of Distributed Generation under N-1 Contingency Using Hybrid Crow Searchโ€“Particle Swarm Algorithm
A Data-Driven Convolutional Neural Network Approach for Power Quality Disturbance Signal Classification (DeepPQDS-FKTNet)

Designing the Architecture of a Convolutional Neural Network Automatically for Diabetic Retinopathy Diagnosis