Assoc. Prof. Dr. Gino Iannace | Acoustics Awards | Innovative Research Award

Assoc. Prof. Dr. Gino Iannace | Acoustics Awards | Innovative Research Award

Assoc. Prof. Dr. Gino Iannace, Univerersity of Campania, Italy

Dr. Iannace Gino is an Associate Professor at the University of Campania Luigi Vanvitelli, where he is qualified as a full professor in the field of environmental acoustics (9C2 ING-IND 11). With a Ph.D. in environmental acoustics, his research interests span various aspects of acoustics, particularly focusing on environmental acoustics and the acoustic properties of materials. He has published over 77 papers in indexed international scientific journals and contributed to 48 conference proceedings. Dr. Iannace has over 30 years of professional experience in acoustics, including conducting action plans, noise maps, and acoustic impact assessments. He has participated in several national and international projects and has served as a reviewer for multiple journals, as well as an editor for the International Journal of Environmental Research and Public Health. He has held numerous academic and scientific coordination roles, leading research units in several projects. His teaching activities are extensive, ranging from undergraduate to master’s levels, and he has taught in several international universities. He is also an active contributor to acoustics and environmental control education, with a strong track record of involvement in international teaching programs and conferences.

Professional Profile:

SCOPUS

ORCID

Summary of Suitability for Innovative Research Award conclusion

Dr. Gino Iannace stands out as an ideal candidate for the Innovative Research Award, based on his significant and diverse contributions to the field of Environmental Acoustics. His 30+ years of professional experience, including groundbreaking work on acoustic materials, environmental noise, and noise impact assessments, demonstrate his expertise and innovation.

🎓 Education:

  • 🎓 Ph.D. in Environmental Acoustics (1993)
    Thesis in Applied Acoustics, University of Naples “Federico II”

  • 🎓 Post-graduate scholarship from Fondazione “G. Donegani” awarded by Accademia Nazionale dei Lincei (1988)

  • 📘 Ph.D. Program in “Engineering of Thermomechanical Systems” at University of Naples “Federico II” (1990–1993)

💼 Work Experience:

  • 🏫 Associate Professor of Environmental Technical Physics (2001–present)
    University of Campania “Luigi Vanvitelli”

  • 👨‍🏫 University Researcher in Applied Acoustics (1994–2001)
    University of Naples “Federico II”

  • 👷‍♂️ Aeritalia S.a.i.p.A. (1988–1990) – Finite Element Numerical Modeling

  • 🧑‍🏫 Teaching experience includes courses at:

    • University of Sannio (2014)

    • University of Naples “Federico II” (1993–2001)

    • University of Campania “Luigi Vanvitelli” (2001–ongoing)

    • International lectures in Spain, Turkey, and Russia via Erasmus and Summer School

🏆 Achievements:

  • 📚 Over 131 documents indexed in Scopus

  • 📈 Citations: 1,591 | H-Index: 19 (as of April 2022)

  • ✍️ Author of 77+ international journal publications and 48+ conference proceedings

  • 🌐 Editor of the International Journal of Environmental Research and Public Health

  • 👨‍🔬 Reviewer for numerous scientific journals

  • 🔬 Coordinator and participant in multiple national and international research projects, including:

    • PRIN projects (1998–2017)

    • EU-funded SONORUS – Marie Curie ITN (2012)

    • Multiple applied acoustics and environmental agreements with local governments and private organizations

🏅 Awards & Honors:

  • 🏅 Post-doctoral scholarship (1994)

  • 🎖️ Fondazione “G. Donegani” postgraduate scholarship (1988)

  • 🌍 Recognized for more than 30 years of professional expertise in environmental acoustics including:

    • Acoustic zoning

    • Noise mapping

    • Acoustic impact assessments

Publication Top Notes:

Acoustic Investigations of Two Barrel-Vaulted Halls: Sisto V in Naples and Aula Magna at the University of Parma

Sound Absorption of Hydroponically Grown Plants

Discover the Acoustics of Vanvitelli Architecture in the Royal Palace of Caserta

Three Albanian cultural centers in comparison under an acoustic perspective

Optimizing Controlled-Resonance Acoustic Metamaterials with Perforated Plexiglass Disks, Honeycomb Structures, and Embedded Metallic Masses

The acoustic importance of velaria in Roman amphitheaters: Investigations on the effects of different coverage percentages in Durres and Capua

Through the history of the acoustic response within the theatre of Taormina: From Greek and Roman periods to our days

Prof. Shih-Hau Fang | Acoustic Awards | Outstanding Scientist Award

Prof. Shih-Hau Fang | Acoustic Awards | Outstanding Scientist Award 

Prof. Shih-Hau Fang, National Taiwan Normal University, Taiwan

Shih-Hau Fang is a distinguished professor in the Department of Electrical Engineering at National Taiwan Normal University (NTNU), specializing in AIoT, mm-wave radar applications, and acoustic signal sensing. He holds a Ph.D. in Communication Engineering from National Taiwan University and has a rich academic and industrial career, having previously served as a professor at Yuan-Ze University and a chief scientist at Far EasTone Telecom. Professor Fang’s research is interdisciplinary, focusing on the Internet of Things (IoT), indoor positioning, healthcare applications, and acoustic sensing technologies. He has authored numerous technical papers, holds multiple patents, and has been recognized as one of the top 2% scientists globally in networking and telecommunications. A fellow of the Institution of Engineering and Technology (IET) and a senior member of IEEE, he has received several prestigious awards, including the Outstanding Young Electrical Engineer Award and the Future Technology Award. His research team has made significant contributions to mobile computing, voice enhancement, and pathological voice analysis, with work featured in top IEEE journals and conferences. Prof. Fang’s groundbreaking work has garnered over 4000 citations, establishing him as a leading figure in his field.

Professional Profile:

Summary of Suitability for the Outstanding Scientist Award: Prof. Shih-Hau Fang

Academic and Professional Credentials:

Prof. Shih-Hau Fang is an eminent scientist with a robust academic background and substantial contributions to the fields of AIoT, mm-wave radar applications, and acoustic signal processing. His educational journey, beginning with a Bachelor’s degree in Communication Engineering from National Chiao Tung University (1999), progressing through a Master’s and Ph.D. from National Taiwan University (2001 and 2009), reflects a strong foundation in communication and engineering. Prof. Fang has consistently advanced his career, holding prestigious positions such as Full Professor at National Taiwan Normal University, Chief Scientist for AIoT at Far EasTone Telecom, and Distinguished Professor at Yuan-Ze University.

🎓 EDUCATION

  • National Chiao Tung University | Bachelor (09/1995 – 06/1999) | Communication Engineering
  • National Taiwan University, Taiwan | Master (09/1999 – 06/2001) | Communication Engineering
  • National Taiwan University, Taiwan | Ph.D. (09/2003 – 02/2009) | Communication Engineering

💼 EMPLOYMENT

  • National Taiwan University, Taiwan | Postdoctoral Researcher (02/2009 – 07/2009) | Communication Engineering
  • Yuan-Ze University, Taiwan | Assistant Professor (08/2009 – 01/2013) | Networking
  • Yuan-Ze University, Taiwan | Associate Professor (02/2013 – 07/2016) | Data Science
  • Academia Sinica, Taiwan | Visiting Scholar (01/2015 – 02/2015) | Acoustic Signal Processing
  • Yuan-Ze University, Taiwan | Full Professor (08/2016 – 07/2024) | Data Science
  • Far EasTone Telecom, Taiwan | Chief Scientist (02/2020 – 12/2020) | Cross-domain AI Applications
  • AI Innovation Research Center, Yuan-Ze University, Taiwan | Director (02/2022 – 07/2024) | Cross-domain AI Applications
  • Research and Development Office, Yuan-Ze University, Taiwan | Vice President (02/2022 – 07/2024) | AIoT, Mm-Wave Radar Applications
  • Yuan-Ze University, Taiwan | Distinguished Professor (02/2022 – 07/2024) | AIoT, Mm-Wave Radar Applications
  • National Taiwan Normal University, Taiwan | Full Professor (08/2024 – Present) | AIoT, Mm-Wave Radar Applications

🏅 HONORS

  1. 2024 IET Fellow | [Institution of Engineering and Technology]
  2. 2023-2024 ESI Highly Cited Paper | [Web of Science]
  3. 2020-2024 Top 2% Scientists | [Elsevier]
  4. 2021 Most Cited Paper | [Journal of Voice]
  5. 2021 Top 100 Download Paper | [Scientific Report]

🔬 CONTRIBUTIONS TO SCIENCE

Prof. Fang has authored 2 book chapters, holds 13 patents, and published 60 journal articles. He has 58 international conference papers and has accumulated over 4000 citations on Google Scholar. His research breakthroughs include:

  • Indoor positioning: Eliminating multipath effects, published in IEEE ToWC with 263 citations.
  • Neural networks: Published in IEEE ToNN with 289 citations.
  • Mobile computing: Improving efficiency, published in IEEE ToMC.
  • Voice enhancement technology: Developed a commercially viable offline voice control module.

In 2020, Prof. Fang’s team achieved 3rd place in Track 6 and 1st place in Track 7 at the International Indoor Navigation Competition. Their work in pathological voice analysis ranks among the best globally, with their detection accuracy being one of the highest.

🌍 IMPACT & INNOVATIONS

  • Prof. Fang has pioneered voice enhancement technologies, receiving the Gold Award at the 2021 Taiwan Innovation Expo and the Future Technology Breakthrough Award (2019).
  • His team’s work on AI applications in healthcare has greatly improved pathological voice analysis through a fully annotated voice database in collaboration with Far Eastern Memorial Hospital.

🎯 Research Focus:

  • AIoT
  • mm-Wave Radar
  • Acoustic Signal Processing
  • Indoor Positioning Systems

Publication top Notes:

 

A Lightweight Learning Framework for Packet Loss Concealment and Speech Enhancement

Novel Human-Posture Recognition System Based on Advanced Graph Convolutional Network Using Skeletal Data

Novel Subject-Dependent Human-Posture Recognition Approach Using Tensor Regression

Prediction of Customer Behavior Changing via a Hybrid Approach

Unsupervised Face-Masked Speech Enhancement Using Generative Adversarial Networks With Human-in-the-Loop Assessment Metrics

Improved Speech Authenticity Detection in Chinese–English Bilingual Contexts