Prof Dr. David Parés Martinez | Healthcare Award | Best Researcher Award

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Prof Dr. David Parés Martinez | Healthcare Award | Best Researcher Award 

Prof Dr. David Parés Martinez, Hospital Germans Trias. Universitat Autònoma de Barcelona, Spain

Dr. David Parés is a distinguished specialist in General and Digestive Surgery with a robust career marked by both national and international contributions. With 152 articles indexed in PUBMED, Dr. Parés has garnered a significant impact factor of 253.576 and an H-index of 21, reflecting his extensive and influential research in the field. His publications are prominently featured in high-impact specialty journals, with 48.2% appearing in the 1st and 2nd quartiles. Currently, he serves as a Specialist Physician at the Germans Trias i Pujol Hospital in Badalona and is affiliated with the hospital’s research center (IGTP). Dr. Parés’ academic credentials include accreditation as an Associate Professor by AQU in 2011 and as a Full Professor of Surgery by ANECA in 2014. His mentorship has guided five doctoral theses, three of which are completed. His research focuses on Colorectal Emergencies, Colon Cancer, Proctology, Fecal Incontinence, and Quality of Care. In addition to authoring four book chapters, he has been involved in six research grants, including four FIS-ISCIII Grants.

 

Professional Profile:

 

Summary of Suitability for Best Researcher Award

Dr. David Parés is a distinguished specialist in General and Digestive Surgery at the Germans Trias i Pujol Hospital in Badalona and a prominent researcher at the Institut d’Investigació en Ciències de la Salut. His extensive career, including his recent roles in the United Kingdom and Spain, highlights his exceptional contributions to the field of colorectal surgery and research.

Education:

  1. Medical Degree:
    • Institution: [Name of Institution]
    • Location: [Location]
    • Year of Graduation: [Year]
  2. Specialization in General and Digestive Surgery:
    • Institution: [Name of Institution]
    • Location: [Location]
    • Year of Completion: [Year]
  3. Additional Training and Fellowships:
    • USA Training:
      • Institution: [Name of Institution]
      • Location: USA
      • Year: 2002

Professional Experience:

  1. Current Position:
    • Employing Entity: FUNDACIÓ INSTITUT D’INVESTIGACIÓ EN CIÈNCIES DE LA SALUT GERMANS TRIAS I PUJOL
    • Position: Specialist Physician
    • Start Date: 01/01/2016
  2. Previous Positions:
    • Hospital del Mar
      • Position: Specialist Physician
      • Start-End Date: 01/02/2004 – 30/09/2019
    • Royal London Hospital – Barts NHS Trust
      • Position: Senior Clinical Fellow
      • Start-End Date: 15/01/2016 – 15/07/2016
    • Portsmouth Hospitals NHS
      • Position: Consultant Surgeon
      • Start-End Date: 01/07/2014 – 15/01/2016
    • Parc Sanitari Sant Joan de Deu
      • Position: Head of General and Digestive Surgery Service
      • Start-End Date: 01/10/2009 – 30/06/2014
    • Hospital Universitari de Bellvitge
      • Position: Specialist Physician
      • Start-End Date: 01/01/2000 – 01/02/2004

Publication top Notes:

Predictive Power of the Trigger Tool for the detection of adverse events in general surgery: a multicenter observational validation study

Breast cancer treatment in octogenarian patients | Cáncer de mama en pacientes octogenarias

 

 

 

 

 

Mr. Fulin Cai | Patient Monitor Award | Best Researcher Award

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Mr. Fulin Cai | Patient Monitor Award | Best Researcher Award 

Mr. Fulin Cai, Arizona State University, United States

Fulin Cai is a dedicated Ph.D. student in Computer Engineering at Arizona State University (ASU) under the supervision of Teresa Wu, with a research focus on deep learning, medical signals, and healthcare. He earned his M.S. in Computer Engineering from ASU with a GPA of 3.86/4.0 in 2023. Prior to this, he completed an M.S. in Management Science and Engineering and a B.S. in Information Management and Information System from Shenzhen University (SZU), ranking high in his class. Fulin’s research has led to numerous publications in prestigious journals such as IEEE Sensors Journal and Frontiers in Physiology, with topics ranging from radar sensing to respiratory function monitoring. He has also presented his work at notable conferences like the Institute of Industrial and Systems Engineers (IISE) Annual Conference.

Professional Profile:

ORCID

Education 🎓

  • Arizona State University (ASU), Tempe, USA
    • Ph.D. Student in Computer Engineering (08/2020 – Present)
    • Supervisor: Teresa Wu
    • Research Interests: Deep Learning, Medical Signals, Healthcare
  • Arizona State University (ASU), Tempe, USA
    • M.S. in Computer Engineering, GPA: 3.86/4.0 (05/2023)
  • Shenzhen University (SZU), Shenzhen, China
    • M.S. in Management Science and Engineering, GPA: 86/100 (Rank 3) (06/2019)
    • Supervisors: Li Li and Xianghua Chu
    • Research Interests: Meta Learning, Reinforcement Learning, Optimization
  • Shenzhen University (SZU), Shenzhen, China
    • B.S. in Information Management and Information System, GPA: 3.56/4.0 (Rank 4) (06/2016)

Teaching Experience 👨‍🏫

  • Arizona State University, Tempe, USA
    • Information Systems Engineering (Spring 2024)
  • Shenzhen University (SZU), Shenzhen, China
    • Lecturer, College of Continuing Education:
      • Management Information System Analysis and Design (03/2017-06/2017)
      • Website Construction and Management (09/2017-12/2017)
      • E-commerce Technology (03/2018-06/2018)
      • Management Information System (03/2019-06/2019)
    • TA, Online Course: Living with Etiquette (03/2017-06/2018)

Working Experience 💼

  • Arizona State University, Tempe, USA (08/2020-Present)
    • Position: Graduate Research Assistant
    • Research Topic: Enhanced representation learning for human biosensing applications
    • Responsibilities:
      • Apply computer vision models to human biosensing applications (e.g., ECG for sleep apnea, radar data for physiological measurement and motion detection).
      • Improve representation learning of DL models from time and frequency perspectives when bio signal is treated as a spectrogram (1-channel image).
  • Huawei Technologies Co., Ltd, Shenzhen, China (07/2019-07/2020)
    • Position: Algorithm Engineer
    • Responsibilities:
      • Implementation of automatic channel selection algorithm.
      • Development of channel simulation software based on NS-3.

Academic Services 📝

  • Journal Reviewer:
    • Computers in Biology and Medicine
    • Biomedical Signal Processing and Control
    • Computers & Industrial Engineering
    • International Journal of Production Research
    • Quality and Reliability Engineering International

Publication top Notes:

E-BDL: Enhanced Band-Dependent Learning Framework for Augmented Radar Sensing

Corrections to “STRIDE: Systematic Radar Intelligence Analysis for ADRD Risk Evaluation With Gait Signature Simulation and Deep Learning” [May 23 10998-11006]

STRIDE: Systematic Radar Intelligence Analysis for ADRD Risk Evaluation With Gait Signature Simulation and Deep Learning

Cross-Trained Worker Assignment Problem in Cellular Manufacturing System Using Swarm Intelligence Metaheuristics

Mr. Mohammad Ahmadi | physiological Sensors | Best Researcher Award

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Mr. Mohammad Ahmadi | physiological Sensors | Best Researcher Award 

Mr. Mohammad Ahmadi, University of Auckland, New Zealand

Ted Ahmadi is a seasoned game developer based in Toronto, with a strong focus on designing Mixed/Augmented/Virtual Reality (MR/AR/VR) games using Unity3D and C#. With over 6 years of experience, he is proficient in utilizing the Microsoft Mixed Augmented Reality Toolkit (MRTK) and has expertise in designing Mixed Reality games for platforms such as Magic Leap, Vive/Vive Pro Eye, Oculus Quest/Quest 2&3/Quest Pro, HP Omnicept, Hololens 2, and Apple Vision Pro. Ted’s career spans across various aspects of game development, including 2D game design for Android using Unity3D, game networking with Photon and Ubiq, and integrating technologies like OpenGL, Blender, and iClone 3D animation toolkit. He is also skilled in using Leap Motion for enhancing interactive experiences in game applications. Beyond game development, Ted is proficient in C++/C# programming across different applications and has experience in Agile/Rapid development methodologies, Waterfall, and Continuous Integration. His expertise extends to embedded systems such as ROS in Linux/Windows, particularly in VR applications for robotics, and enterprise web server applications where he excels in Java programming, software optimization, debugging, and troubleshooting.

Professional Profile:

ORCID

 

Education

University of Auckland

  • Bachelor of Science in Computer Science
    Date: Graduated in 2018

Work Experience

Design School, University of Auckland
Teaching and Tutoring Assistant
July 2022 – Nov 2022

  • Responsibilities: Assisted in teaching and tutoring the course “Designing Mix Realities” at the School of Design.
  • Skills: Unity3D, Blender (3D modeling and animation for rapid prototyping), Adobe Aero (3D modeling).

Skills

  • Game Design: Unity3D, MRTK and XR SDK, AR Kit, AR Core, Leap Motion, OpenGL, Vuforia, Blender, iClone 7.
  • Programming: C++/C#, Java, JavaScript, PHP/CSS/HTML, jQuery, mySQL, JSON/XML, Matlab.
  • HMD: Vive/Vive Pro Eye, Oculus Quest/Quest 2/Quest 3/Quest Pro, HP Omnicept, Magic Leap, Hololens 2, Apple Vision Pro.
  • API: WebGL, OpenGL.
  • Web API: .Net/ASP.Net MVC.
  • J2EE API: Java Servlet and EJB.
  • Version Control: git and GitHub.
  • OS: Linux, Windows.
  • Embedded Systems: ROS.

Employment History

🏫 Design School, University of Auckland
Teaching and Tutoring Assistant (July 2022 – Nov 2022)

  • Teaching and tutoring assistant for the course “Designing Mix Realities” at the school of design.
  • Skills: Unity3D, Blender (3D modeling and animation for rapid prototyping), Adobe Aero (3D modeling).

Publication top Notes:

EEG, Pupil Dilations, and Other Physiological Measures of Working Memory Load in the Sternberg Task

Cognitive Load Measurement with Physiological Sensors in Virtual Reality during Physical Activity

Comparing Performance of Dry and Gel EEG Electrodes in VR using MI Paradigms

PlayMeBack – Cognitive Load Measurement using Different Physiological Cues in a VR Game

Prof. Shing-Hong Liu | Biomedical Award | Best Researcher Award

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Prof. Shing-Hong Liu | Biomedical Award | Best Researcher Award 

Prof. Shing-Hong Liu, Chaoyang University of Technology, Taiwan

Shing-Hong Liu is an esteemed academic and researcher in the field of biomedical engineering and computer science. He obtained his B.S. degree in Electronic Engineering from Feng-Jia University, Taiwan, in 1990, followed by an M.S. degree in Biomedical Engineering from National Cheng-Kung University in 1992. In 2002, he earned his Ph.D. from the Department of Electrical and Control Engineering at National Chiao-Tung University, Taiwan. Since August 1994, Dr. Liu has been actively involved in academia, initially as a Lecturer in the Department of Biomedical Engineering at Yuanpei University, Taiwan. He progressed to become an Associate Professor from 2002 to 2008. Currently, he holds the position of Distinguished Professor in the Department of Computer Science and Information Engineering at Chaoyang University of Technology. Dr. Liu’s research focuses on biomedical signal processing, artificial intelligence applications in mobile health (mHealth), and the design of biomedical instruments. He has been recognized for his contributions, being named one of the World’s Top 2% Scientists in 2020. His research projects have received substantial funding, totaling NT$36,329,914, and he has authored 59 papers in SCI journals.

 

Professional Profile:

ORCID

 

Education:

  • B.S. in Electronic Engineering
    • Feng-Jia University, Taizhong, Taiwan, R.O.C.
    • Year of Completion: 1990
  • M.S. in Biomedical Engineering
    • National Cheng-Kung University, Tainan, Taiwan, R.O.C.
    • Year of Completion: 1992
  • Ph.D. in Electrical and Control Engineering
    • National Chiao-Tung University, Hsinchu, Taiwan, R.O.C.
    • Year of Completion: 2002

Work Experience:

  • Lecturer
    • Department of Biomedical Engineering, Yuanpei University, Hsinchu, Taiwan, R.O.C.
    • August 1994 – 2002
  • Associate Professor
    • Department of Biomedical Engineering, Yuanpei University, Hsinchu, Taiwan, R.O.C.
    • 2002 – 2008
  • Distinguished Professor
    • Department of Computer Science and Information Engineering, Chaoyang University of Technology, Taiwan, R.O.C.
    • 2020 – Present

Achievements:

Shing-Hong Liu has been recognized as one of the World’s Top 2% Scientists in 2020. His research interests focus on biomedical signal processing, artificial intelligence for mHealth applications, and the design of biomedical instruments. He has successfully led projects with a total budget of NT 36,329,914 and has published 59 papers in SCI journals.

Publication top Notes:

Predicting Gait Parameters of Leg Movement with sEMG and Accelerometer Using CatBoost Machine Learning

Human Activity Recognition Based on Deep Learning and Micro-Doppler Radar Data

Estimation of Gait Parameters for Adults with Surface Electromyogram Based on Machine Learning Models

A Wearable Assistant Device for the Hearing Impaired to Recognize Emergency Vehicle Sirens with Edge Computing

A Wearable Assistant Device for Hearing Impaired to Recognize Emergency Vehicle Sirens with Edge Computing