Li Wan | Electromagnetic Sensors | Best Researcher Award

Best Researcher Award

Li Wan
Anhui Medical University, China

Li Wan
Affiliation Anhui Medical University
Country China
Scopus ID 57204732623
Documents 10
Citations 44
h-index 3
Subject Area Psychology, Psychiatry, Electromagnetic Sensors,  Neuroscience, Neuromodulation
Event Global Sensor Awards
ORCID 0000-0002-3748-9087

Li Wan is a Chinese psychologist, neuroscientist, and academic leader recognized for her contributions to brain disorders research, neuromodulation technologies, and non-invasive therapeutic interventions. As Director of the Brain Disorders and Neuromodulation Research Center at Anhui Medical University, she has led multidisciplinary investigations involving electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), brain-computer interfaces (BCI), transcranial electrical stimulation (tES), and transcranial magnetic stimulation (TMS). Her research spans schizophrenia, major depressive disorder, addiction, cognitive control, and neurorehabilitation, contributing to the development of precision psychiatry and digital biomarkers.[1]

Abstract

Li Wan’s academic career is characterized by interdisciplinary research integrating neuroscience, psychiatry, psychology, artificial intelligence, and neuromodulation technologies. Her work focuses on understanding the neural mechanisms of psychiatric disorders and developing non-invasive therapeutic interventions. Through leadership of multiple provincial and institutional research projects, she has advanced translational neuroscience applications for schizophrenia, addiction, depression, and cognitive dysfunction. Her contributions include the development of EEG-based diagnostic systems, digital biomarkers, and personalized neuromodulation strategies designed to improve clinical outcomes and mental healthcare innovation.[2]

Keywords

Neuromodulation, Psychiatry, Neuroscience, EEG, fNIRS, Brain-Computer Interface, Transcranial Magnetic Stimulation, Transcranial Electrical Stimulation, Schizophrenia, Major Depressive Disorder, Addiction Research, Artificial Intelligence, Cognitive Control, Neuroimaging, Digital Biomarkers.

Introduction

Mental and neurological disorders continue to represent significant global healthcare challenges. Advances in neuroimaging, computational neuroscience, and non-invasive brain stimulation have created new opportunities for understanding and treating these conditions. Within this evolving scientific landscape, Li Wan has established a research program dedicated to identifying neural mechanisms associated with psychiatric disorders while translating laboratory findings into clinically relevant interventions. Her investigations combine neurophysiological measurements with advanced analytical approaches to support precision mental healthcare.[3]

Research Profile

Li Wan earned her Ph.D. in Psychology from Virginia Tech and currently serves as Professor and Director of the Brain Disorders and Neuromodulation Research Center. She has participated in major projects funded by the United States Department of Health and Human Services and the United States Department of Defense. As Principal Investigator, she has led more than ten competitive research projects focused on psychiatric disorders, cognitive neuroscience, neuromodulation technologies, and AI-assisted clinical applications.[4]

  • Director, Brain Disorders and Neuromodulation Research Center.
  • Professor and Principal Investigator.
  • Master’s Supervisor at Anhui Medical University and Wannan Medical College.
  • Editorial Board Member of Brain-X, Alpha Psychiatry, and Brain Science Advances.
  • Guest Editor, Frontiers in Psychiatry.
  • Member of the World Psychiatric Association (WPA).

Research Contributions

Her research portfolio demonstrates sustained contributions toward the understanding of neural circuit dysfunction and therapeutic neuromodulation in psychiatric conditions. Several notable projects include:

  • Brain-computer interface interventions for reducing alcohol craving relapse.
  • Artificial intelligence-based analysis of adolescent stress during the COVID-19 pandemic.
  • EEG frequency modulation approaches for schizophrenia symptom improvement.
  • Neural circuit investigations of voluntary inhibition deficits.
  • Targeted electrical stimulation approaches for drug dependence treatment.
  • Novel neurofeedback systems based on transcranial direct current stimulation.

A significant technological contribution includes the development of an artificial intelligence-assisted EEG medical diagnostic support system, protected under Chinese invention patent ZL 2024 1 0077209.1, demonstrating integration of neuroscience, machine learning, and clinical diagnostics.[5]

Publications

Li Wan has authored or co-authored more than 60 scholarly publications, including over 30 papers indexed in SCI journals. Selected representative publications include:

  1. Zhang Q., Wan L., et al. (2026). fNIRS identifies right prefrontal hemodynamic signatures for subclassifying alcohol use disorder. Cognitive Neurodynamics.
  2. Wan L., Chen Y., et al. (2026). EEG-based digital biomarker for personalizing transcranial magnetic stimulation in major depressive disorder. npj Digital Medicine.
  3. Liu W., Wan L., et al. (2025). The effect of bilateral high-definition γ-tACS on negative symptoms and mismatch negativity in schizophrenia. Journal of Psychiatric Research. DOI: 10.1016/j.jpsychires.2025.05.056
  4. Wan L., Pei P., Zhang Q., Gao W. (2024). Specificity in the commonalities of inhibition control. European Psychiatry. DOI: 10.1192/j.eurpsy.2024.1785
  5. Wu H., Zhang Q., Wan L., et al. (2024). Effect of γ-tACS on prefrontal hemodynamics in bipolar disorder. Journal of Psychiatric Research. DOI: 10.1016/j.jpsychires.2024.05.015

Research Impact

The impact of Li Wan’s research extends across neuroscience, psychiatry, clinical psychology, and biomedical engineering. Her studies contribute to improved understanding of cognitive control dysfunction, emotional regulation, and neural network abnormalities associated with psychiatric disorders. By integrating neuroimaging and neuromodulation techniques, her work supports the development of evidence-based personalized treatment strategies and enhances the translation of neuroscience discoveries into clinical practice.[3]

Award Suitability

Li Wan demonstrates strong qualifications for consideration under the Best Researcher Award category. Her record includes leadership of multiple competitive research projects, substantial peer-reviewed publication output, editorial responsibilities in international journals, intellectual property development through an authorized invention patent, and professional service within national and international scientific organizations. The interdisciplinary nature of her work and its translational relevance to mental health care further support recognition of her research achievements.[4]

Conclusion

Li Wan’s scientific career reflects a commitment to advancing knowledge in neuroscience and psychiatry through innovative methodologies and translational research. Her leadership in neuromodulation research, development of AI-assisted diagnostic technologies, and extensive publication record position her among active contributors to contemporary mental health research. Continued investigation of brain disorders and personalized interventions is expected to further strengthen the clinical and scientific significance of her work.

References

  1. ORCID. (n.d.). Li Wan Research Profile.
    https://orcid.org/0000-0002-3748-9087
  2. Research Project Portfolio and Award Nomination Documentation submitted by Li Wan (2026).
  3. Wan, L., et al. Publications in psychiatry, neuroscience, and neuromodulation research (2024–2026).
  4. Professional Biography and Academic Background, Anhui Medical University.
  5. China Invention Patent No. ZL 2024 1 0077209.1. Medical diagnostic assistance system based on EEG signals and artificial intelligence classification.

Assoc. Prof. Dr. Shunli Ma | Electromagnetic | Best Researcher Award

Assoc. Prof. Dr. Shunli Ma | Electromagnetic | Best Researcher Award 

Assoc. Prof. Dr. Shunli Ma, Fudan University, China

Shunli Ma is an Associate Professor at Fudan University, specializing in analog sensor circuit design, automotive millimeter-wave radar systems, and millimeter-wave imaging technology. Since joining Fudan University in 2017, he has held various roles including postdoctoral fellow, young associate researcher, and currently serves as an Associate Professor since 2022. Dr. Ma’s career spans both academia and industry, including his pivotal work at VIRTUS Lab, Nanyang Technological University (Singapore) from 2012 to 2014, where he contributed to the design of 60GHz communication chips that have since reached mass production. From 2016 to 2017, he was a founding engineer at Gatland Microelectronics Technology (Shanghai) Co., Ltd., where he led the development of 77GHz FMCW phase-locked loops and high-performance amplifiers, integral to China’s first mass-produced 77GHz CMOS automotive millimeter-wave radar chips. Dr. Ma has published over 50 high-impact papers, including 27 in prestigious journals such as IEEE TCAS-I/II and TMTT, and holds 13 invention patents. He has led and participated in numerous national and provincial research projects, and actively collaborates with academic institutions and industry partners to advance radar and semiconductor technologies.

Professional Profile:

SCOPUS

🏆 Summary of Suitability for Best Researcher Award: Shunli Ma

Shunli Ma, currently an Associate Professor at Fudan University, stands out as a highly accomplished and impactful researcher in the fields of analog sensor circuits, millimeter wave radar technology, and millimeter wave imaging. With over a decade of academic, industrial, and research experience—including key contributions to commercialized technologies—Dr. Ma is an outstanding candidate for the Best Researcher Award.

🎓 Education & Research Training

  • 📍 Postdoctoral Fellow, Fudan University (2017–2018)

  • 🎓 Research Fellow, VIRTUS Lab, Nanyang Technological University, Singapore (2012–2014)

    • Focus: 60GHz communication chip design

💼 Work Experience

  • 👨‍🏫 Associate Professor, Fudan University (2022–Present)

    • Research Areas: Analog sensor circuit design, automotive millimeter-wave radar, and millimeter-wave imaging technology

  • 👨‍🔬 Young Associate Researcher, Fudan University (2018–2022)

  • 🧪 Postdoctoral Fellow, Fudan University (2017–2018)

  • 🛠️ Founding Engineer, Gatland Microelectronics, Shanghai (2016–2017)

    • Led design of 77GHz FMCW phase-locked loops and high-performance amplifiers

    • Key contributor to the first domestic mass-produced 77GHz CMOS car-mounted millimeter-wave radar

  • 🌐 Researcher, VIRTUS Lab, Nanyang Technological University, Singapore (2012–2014)

    • Worked on mass-producible 60GHz communication chips

🏆 Achievements

  • 📄 Published over 50 papers in top-tier journals (e.g., TCAS-I/II, TMTT)

  • 📘 Total of 27 high-level academic publications

  • 🔬 Granted 13 national invention patents

  • 📊 Involved in multiple national, provincial, and ministerial-level research projects

  • 🤝 Collaborates with various research institutions and industry partners

🏅 Awards & Honors

  • 🧠 Recognized as a leading expert in millimeter-wave circuit design

  • 🥇 Contributions led to mass production of China’s first 77GHz CMOS automotive radar module

  • 🛡️ Key innovator in high-performance analog and RF IC design

Publication Top Notes:

A Harmonic-Suppressed GaN Power Amplifier Using Artificial Coupled Resonator

High drain field impact ionization transistors as ideal switches

Long-Range Epitaxial MOF Electronics for Continuous Monitoring of Human Breath Ammonia

Multi-Sampling Mode CDAC Design for a 12-Bit 200MS/s Pipelined-SAR ADC

A 3-to-78-GHz Distributed Low-Noise Amplifier Incorporating High-Gain Differential gm Cells and Balanced Active Balun in a 65-nm CMOS

A 140- and 220-GHz Dual-Band Amplifier in 130-nm SiGe BiCMOS Process

A millimeter-wave broadband power amplifier with a tree-like transistor structure using 0.15-μm GaAs technology

Hybrid neuromorphic hardware with sparing 2D synapse and CMOS neuron for character recognition

A 40nm 2TOPS/W Depth-Completion Neural Network Accelerator SoC With Efficient Depth Engine for Realtime LiDAR Systems

A 124-to-152-GHz Power Amplifier Exploiting Chebyshev-Type Two-Section Wideband and Low-Loss Power-Combining Technique in 28-nm CMOS

 

 

Francesco Mercogliano | Electromagnetic Sensing System | Best Researcher Award

Francesco Mercogliano | Electromagnetic Sensing System | Best Researcher Award

Dr. Francesco Mercogliano, University of Naples Parthenope , Italy.

Dr. Francesco Mercogliano is a dedicated PhD student in Information and Communication Technology and Engineering at the University of Naples “Parthenope,” Italy. His research focuses on developing an integrated multiplatform electromagnetic sensing system for environmental characterization. With a Master’s degree in Geology and Applied Geology and a Bachelor’s degree in Geological Sciences, Francesco has demonstrated exceptional academic prowess, achieving cum laude honors. His internships with renowned institutes, including the National Research Council and the National Institute of Geophysics and Volcanology, have further honed his skills in satellite thermal imaging and geophysical data analysis. 🌍📚💻

Publication Profile

Googlescholar

Education and Experience

  • PhD Student in Information and Communication Technology and Engineering (39th Cycle)
    University of Naples “Parthenope,” Naples, Italy (2023 – Present)

    • Research Focus: Development of an integrated multiplatform electromagnetic sensing system for environmental characterization.
  • Master’s Degree in Geology and Applied Geology (LM-74)
    University of Naples “Federico II,” Naples, Italy (2021 – 2023)

    • Grade: 110/110 cum laude
    • Thesis: Analysis of Land Surface Temperature (LST) in the Campi Flegrei caldera.
  • Bachelor’s Degree in Geological Sciences (L-34)
    University of Naples “Federico II,” Naples, Italy (2018 – 2021)

    • Grade: 110/110 cum laude
    • Thesis: Remote sensing application to detect Land Surface Temperature in volcanic regions.
  • Internships:
    • National Research Council (CNR) – Institute for Electromagnetic Sensing of the Environment (IREA) (April 2023 – June 2023)
      • Analyzed satellite thermal images for LST mapping.
    • National Institute of Geophysics and Volcanology (INGV) (May 2022 – September 2022)
      • Processed GNSS-RTK data to monitor ground deformation.
    • CNR – IREA (October 2019 – January 2020)
      • Conducted geothermal monitoring using thermal remote sensors.

Suitability For The Award

Dr. Francesco Mercogliano is an exemplary candidate for the Best Researcher Award, currently pursuing a Ph.D. in Information and Communication Technology and Engineering at the University of Naples “Parthenope.” His research focuses on developing an integrated electromagnetic sensing system for environmental characterization, showcasing his commitment to innovation. With top honors in both his Master’s and Bachelor’s degrees from the University of Naples “Federico II,” and hands-on experience at the National Research Council and the National Institute of Geophysics and Volcanology, Francesco’s academic excellence and technical skills position him as a promising researcher in environmental science.

Professional Development

Francesco Mercogliano has actively pursued professional development through hands-on internships and research projects in prestigious organizations such as the National Research Council (CNR) and the National Institute of Geophysics and Volcanology (INGV). His work includes analyzing satellite thermal images for land surface temperature mapping and monitoring ground deformation using GNSS-RTK data. Proficient in MATLAB, Python, and remote sensing techniques, Francesco combines his technical skills with a strong foundation in geology to contribute meaningfully to environmental studies. His dedication to advancing knowledge in geosciences exemplifies his commitment to professional excellence and innovation. 🌱🔍📊

Research Focus

Francesco Mercogliano’s research focuses on developing integrated electromagnetic sensing systems for environmental characterization. His work emphasizes the use of advanced remote sensing technologies to analyze land surface temperature, particularly in volcanic regions like the Campi Flegrei caldera. By employing methods such as Independent Component Analysis (ICA), Francesco aims to identify thermal anomalies that can inform geological studies and risk assessment. His interdisciplinary approach combines principles of geology, remote sensing, and data analysis, contributing significantly to environmental monitoring and understanding of geological phenomena. 🌋📈💡

Awards and Honors

  • Research Internship Recognition at the National Research Council (CNR) 🌟
  • Outstanding Contribution Award at National Institute of Geophysics and Volcanology (INGV) 🌌

Publication Top Notes

  • Thermal Patterns at the Campi Flegrei Caldera Inferred from Satellite Data and Independent Component Analysis (2024) 📡🌋
  • Remote detection of Thermal Anomalies at Campi Flegrei caldera via Independent Component Analysis (ICA) (2024) 🔍📊
  • Airborne Synthetic Aperture Radar and Electromagnetic Technologies of the Italian Earth Observation Platform ITINERIS  (2024) ✈️🛰️
  • Multiparametric and Multiplatform Detection of Ongoing Unrest Processes in Active Resurgent Calderas: A Case Study of the Campi Flegrei Caldera (2024) 🌍⚠️