Dr. Longbin Jin | Signal Processing Awards | Best Researcher Award

Posted on by ScienceFather

Dr. Longbin Jin | Signal Processing Awards | Best Researcher Award 

Dr. Longbin Jin, Konkuk University, South Korea

Longbin Jin, is a Ph.D. candidate in Computer Science at Konkuk University, Korea, with an expected graduation in February 2025. His research focuses on adaptive visual prompting for video action recognition in vision-language models under the guidance of Professor Eun Yi Kim. He holds a Master’s degree in Smart ICT Convergence and a Bachelor’s degree in Mechanical Engineering & Automation from Shanghai University, China. Throughout his academic career, Longbin has received numerous accolades, including winning the ICASSP 2023 SPGC Challenge and multiple Excellence and Encouragement Prizes at the Korea Software Congress. Currently, he serves as an AI Researcher at Voinosis in Seoul, where he develops AI models for early detection of hearing loss and cognitive impairment in the elderly. He is also an instructor at Konkuk University, teaching courses on Artificial Intelligence, Computer Vision, and Machine Learning. His project experience includes collaborations on medical imaging and virtual reality, demonstrating his expertise in applying AI technologies across diverse fields. Longbin is proficient in English, Chinese, and Korean, reflecting his international background and commitment to advancing technology in healthcare and education.

Professional Profile:

GOOGLE SCHOLAR

Research for Community Impact Award: Longbin Jin’s Suitability

Longbin Jin is a highly qualified candidate for the Research for Community Impact Award due to his significant contributions in the fields of artificial intelligence and healthcare, particularly in projects that directly benefit the community.

📚 Education

  • Ph.D. in Computer Science
    Konkuk University, Korea
    Expected: February 2025
    Thesis: Adaptive Visual Prompting for Video Action Recognition in Vision-Language Models
    Advisor: Prof. Eun Yi Kim
  • M.S. in Smart ICT Convergence
    Konkuk University, Korea
    Graduated: August 2020
    Thesis: E-EmoticonNet: EEG-based Emotion Recognition with Context Information
    Advisor: Prof. Eun Yi Kim
  • B.S. in Mechanical Engineering & Automation
    Shanghai University, China
    Graduated: August 2018

💼 Work Experience

  • AI Researcher
    Voinosis, Seoul, Korea
    December 2022 – Present

    • Researcher on AI models for early detection of hearing loss and cognitive impairment based on voice analysis for the elderly (VoiceCheck & BrainGuardDoctor Apps).
  • Instructor
    Konkuk University, Seoul, Korea
    March 2022 – Present

    • Teaching courses on Computer Vision, Artificial Intelligence, and Machine Learning.
  • AI Engineer
    Lulla, Seoul, Korea
    October 2022 – November 2022

    • Main researcher for an AI model for a child face-matching system to assist kindergarten teachers (Lulla App).

🏆 Achievements, Awards, and Honors

  • Winner of ICASSP 2023 SPGC Challenge: Multilingual Alzheimer’s Dementia Recognition through Spontaneous Speech (First Author) 🥇
  • Excellence Prize, Korea Software Congress 2023 🥇
  • Encouragement Prize, ACM Student Research Competition, Computer Human Interaction 2020 (First Author) 🎖️
  • Excellence Prize, Korea Software Congress 2019 (First Author) 🏅
  • Encouragement Prize, Korea Software Congress 2019 (First Author) 🎖️
  • Excellent Presentation, International Conference on Culture Technology 2018 🌟

Publication Top Notes:

Interpretable Cross-Subject EEG-Based Emotion Recognition Using Channel-Wise Features†

CITED:29

Consen: Complementary and simultaneous ensemble for alzheimer’s disease detection and mmse score prediction

CITED:15

Eeg-based user identification using channel-wise features

CITED:7

E-EmotiConNet: EEG-based emotion recognition with context information

CITED:2

Emotion Recognition based BCI using Channel-wise Features

CITED:1

 

Dr. Liu Gaohua | Signal Processing Awards | Best Researcher Award

Posted on by ScienceFather

Dr. Liu Gaohua | Signal Processing Awards | Best Researcher Award 

Dr. Liu Gaohua, Tianjin University, China

Gaohua Liu is a dedicated engineer and researcher at the School of Electronic and Information Engineering at Tianjin University, where she has been engaged in teaching and motion recognition research since March 2013. She earned her Master of Engineering degree in Electromagnetic Field and Microwave from Tianjin University in 2013, where her thesis focused on downlink logical channel design and algorithm research in LTE under the supervision of Prof. HanSong Su. Prior to that, she completed her Bachelor of Engineering in Communication Engineering at Qingdao University of Science & Technology in 2010. Currently, Gaohua is pursuing her Ph.D. in Information and Communication Engineering, specializing in motion recognition based on multimodal signals, under the guidance of Prof. Jie Jin. Her contributions to the field have been recognized with several awards, including the “Shen-Zhikang Award” for outstanding young teachers at Tianjin University in June 2019 and a National First Prize in the fifth “Dingyang Cup” National Electrical and Electronic Teaching Case Design Competition in May 2018.

Professional Profile:

SCOPUS

Suitability for the Best Researcher Award

Gaohua Liu holds a Master’s degree in Electromagnetic Field and Microwave from Tianjin University, where she conducted significant research on LTE downlink logical channel design. Her foundational education in Communication Engineering from Qingdao University of Science & Technology further solidifies her expertise in the field.

🎓 Education

  • 2010-2013: M.E. in Electromagnetic Field and Microwave
    • Institution: Tianjin University, Tianjin, China
    • Thesis Title: Downlink Logical Channel Design and Algorithm Research in LTE
    • Supervisor: Prof. HanSong Su
  • 2006-2010: B.E. in Communication Engineering
    • Institution: Qingdao University of Science & Technology, Qingdao, China

💼 Work Experience

  • 03/2013 – Present: Engineer
    • Department: School of Electronic and Information Engineering, Tianjin University
    • Focus: Teaching and Motion Recognition research
  • 09/2018 – Present: Ph.D. Candidate
    • Research Topic: Motion Recognition Based on Multimodal Signals
    • Supervisor: Prof. Jie Jin
    • Institution: Tianjin University, Tianjin, China

🏆 Awards and Honors

  • Jun. 2019: “Shen-Zhikang Award” for Tianjin University’s Young Teachers in Talent
  • May. 2018: National First Prize in “The Fifth ‘Dingyang Cup’ National Electrical and Electronic Teaching Case Design Competition”

Publication Top Notes:

Improved encoder-decoder temporal action detection algorithm

Improved human action recognition algorithm based on two-stream faster region convolutional neural network

Algorithm for student behavior detection based on neural network

Improved class room face recognition algorithm based on insightface and its application

Classroom face detection algorithm based on convolutional neural network

Prof. Shing-Tai Pan | Signal Processing Awards | Best Researcher Award

Posted on by ScienceFather

Prof. Shing-Tai Pan | Signal Processing Awards | Best Researcher Award 

Prof. Shing-Tai Pan, National University of Kaohsiung, Taiwan

Shing-Tai Pan, is a distinguished academic in the field of computer science and engineering. He earned his M.S. degree in Electrical Engineering from National Sun Yat-Sen University, Kaohsiung, Taiwan, in 1992, followed by a Ph.D. from National Chiao Tung University, Hsinchu, Taiwan, in 1996. Since 2006, he has been a Professor in the Department of Computer Science and Information Engineering at the National University of Kaohsiung, Taiwan. Prof. Pan is an active member of several professional organizations, including the Taiwanese Association for Artificial Intelligence (TAAI), the Chinese Automatic Control Society (CACS), and The Association for Computational Linguistics and Chinese Language Processing (ACLCLP). His research interests encompass biomedical signal processing, digital signal processing, speech recognition, evolutionary computations, artificial intelligence applications, and intelligent control system design.

Professional Profile:

SCOPUS

ORCID

Summary of Suitability for the Best Researcher Award: Shing-Tai Pan

Shing-Tai Pan is a distinguished academic and researcher whose extensive contributions to the fields of biomedical signal processing, speech recognition, and artificial intelligence make him a highly suitable candidate for the Best Researcher Award. With a career spanning over two decades, his work reflects innovation, collaboration, and a commitment to advancing technology for societal benefits.

Education

  1. M.S. in Electrical Engineering
    • Institution: National Sun Yat-Sen University, Kaohsiung, Taiwan
    • Year: 1992
  2. Ph.D. in Electrical Engineering
    • Institution: National Chiao Tung University, Hsinchu, Taiwan
    • Year: 1996

Work Experience

  1. Department of Computer Science and Information Engineering
    • Position: Professor
    • Institution: National University of Kaohsiung, Kaohsiung, Taiwan
    • Joined: 2006

Professional Memberships

  • Taiwanese Association for Artificial Intelligence (TAAI)
  • Chinese Automatic Control Society (CACS)
  • The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)

Research Interests

  • Biomedical Signal Processing
  • Digital Signal Processing
  • Speech Recognition
  • Evolutionary Computations
  • Artificial Intelligence Applications
  • Intelligent Control Systems Design

Publication Top Notes:

Fuzzy‐HMM modeling for emotion detection using electrocardiogram signals

Performance Improvement of Speech Emotion Recognition Systems by Combining 1D CNN and LSTM with Data Augmentation

Editorial for special issue entitled “CACS2020: Applications of emerging intelligent techniques on modeling and control of modern systems”

Editorial for special section “CACS18: Modelling and control for practical systems”

Efficient robust speech recognition with empirical mode decomposition using an FPGA chip with dual core

 

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

Posted on by ScienceFather

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

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 🎓

  • Ph.D. in Computer Science
    • Institution: King Saud University, Saudi Arabia 🎓
    • Graduation: November 2021 📅
    • Dissertation: Developing an auto deep learning model with less complexity and high performance for automatic diabetic retinopathy screening 🧠💻
  • M.Sc. in Computer Science
    • Institution: King Saud University, Saudi Arabia 🎓
    • Graduation: May 2014 📅
  • B.Sc. in Computer Science
    • Institution: King Saud University, Saudi Arabia 🎓
    • Graduation: February 2007 📅

Academic Experience 📚

  • Assistant Professor
    • Institution: College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia 🏫
    • Duration: 2022 to Present ⏳
    • Responsibilities: Teaching courses in Artificial Intelligence 🤖, Natural Language Processing 💬, Algorithm Design and Analysis 💻, Image Processing 🖼️, and Computer Vision 👀
  • Lecturer (Part-time)
    • Institution: King Saud University, Riyadh, Saudi Arabia 🎓
    • Duration: 2017 to 2021 ⏳
  • Researcher
    • Institution: King Saud University, Riyadh, Saudi Arabia 🧪
    • Duration: March 2015 to 2021 ⏳
    • Projects:
      • Automatic Diabetic Retinopathy Screening 🩺👁️
        • Achievements: Two ISI papers 📄
      • Identification of Fingerprint Interoperability 🧑‍⚖️
        • Achievements: One patent, one ISI paper, two conference papers 📑
      • Cloud-Based Privacy-Protected Computer-Aided Diagnosis System for Breast Cancer Screening 🩻
        • Achievements: One ISI paper 📄

Publication 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 Search–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

 

Mr. Rifa Asyari | Signal Processing Awards | Best Researcher Award

Posted on by ScienceFather

Mr. Rifa Asyari | Signal Processing Awards | Best Researcher Award

Mr. Rifa Asyari, University of Southern Denmark, Denmark.

Rifa Atul Izza Asyari is a highly skilled RF Engineer with over four years of hands-on experience in designing, analyzing, and optimizing advanced RF systems such as radar, RF front-end modules, metasurfaces, and antennas. He is currently pursuing a Ph.D. in Biomedical Engineering at the University of Southern Denmark, with his research focused on radar technology for vital sign monitoring, and is set to graduate in December 2024. He holds an M.Sc. in Telecommunication Engineering from National Sun Yat-Sen University, Taiwan, where he developed high-gain array antennas with frequency-selective surfaces, and a B.Sc. in Electrical Engineering from Universitas Islam Indonesia, Indonesia, with a thesis on optical network design for 4G LTE systems.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award

Rifa Atul Izza Asyari demonstrates an exemplary profile as a highly skilled RF Engineer and researcher with significant contributions in academia and industry. Here’s why Rifa is an excellent candidate for the Best Researcher Award

🎓 Education:

  • PhD in Biomedical Engineering 🏫
    University of Southern Denmark (Odense, Denmark)
    📅 Expected Completion: Dec 2024
    📑 Thesis: Radar for Vital Sign Monitoring
  • MSc in Telecommunication Engineering 📡
    National Sun Yat-Sen University (Kaohsiung, Taiwan)
    📅 June 2019
    📑 Thesis: High Gain Array Antenna with Frequency Selective Surface for Vital Sign Monitoring
  • BSc in Electrical Engineering ⚡
    Universitas Islam Indonesia (Yogyakarta, Indonesia)
    📅 Feb 2016
    📑 Thesis: Optical Network Design for 4G Long Term Evolution Sleman

💼 Work Experience:

  • Senior Hardware R&D Engineer ⚙️ at Pegatron (Batam, Indonesia)
    📅 Sept 2019 – Jan 2022

    • Designed and validated RF front-end WiFi modules and IP cameras.
    • Improved broadband performance by 40% and optimized key metrics like EVM and BER.
    • Conducted DVT, OTA measurements, and troubleshooting for WiFi and 5G communication standards.
  • Fibre Optic Engineer 🌐 at Biznet Networks (Yogyakarta, Indonesia)
    📅 May 2016 – Jun 2017

    • Planned and designed fiber-optic network architectures.
    • Conducted fusion splicing and troubleshooting using OTDR.
  • Heavy Dump Truck Operator 🚛 at Pamapersada Nusantara (Tabalong, Indonesia)
    📅 Jan 2010 – Sept 2012

    • Operated Komatsu trucks for open-cast mining operations.

🏆 Achievements:

  • 🏅 Best Student Paper Award at Taiwan Telecommunication Annual Symposium (2020)
  • 🌟 Top 50 Online Global Startup Weekend Unite to Fight COVID-19 (2020)
  • 📜 IMPTE Scholarship Award at National Sun Yat-Sen University (2017)

🔧 Technical Skills:

  • Programming: 🖥️ MATLAB, Python, C/C++, R
  • RF Tools: 📡 CST, Ansys, ADS, Spectrum Analyzer
  • Networking: 🌐 LAN/WAN, TCP/IP, VPN
  • Soft Skills: 🗣️ Leadership, Problem-solving, Presentation

Publication Top Notes:

High Gain Array Antenna With FSS for Vital Sign Monitoring Through the Wall