The main theme of Brain-inspired eXplainable Artificial Intelligence(BXAI) laboratory is a next generation Artificial Intelligence based on  Neuroscience.

Notice

• We are looking for postdocs, graduate and undergraduate students interested in 

  • • Brain-inspired Artificial Intelligence (to building Artificial Brain Models based on Neuroimage & Neural Computation)

      • Application 1: Brain-machine Interface

      • Application 2: Financial Time Series Forecasting

  • If you're interested, please send me an email(h2kim at pknu.ac.kr) with your curriculum vitae.

• We highly recommend that you apply to the job opening for AI and Data Scientist in 4N Inc.

  • Homepage: https://www.4nbrain.com/recruit

Research Areas

PI: HOON-HEE KIM (HUNHEE KIM), Ph.D.

• Assistant Professor, Pukyong National University, Republic of Korea, 2022.09.01. – present.

  • Pukyong National University (English Page)

  • College of Information Technology and Convergence (English Page)

  • Department of Computer Engineering and Artificial Intelligence (English Page)

  • Major of Computer Engineering (English Page)

    • E-mail: h2kim at pknu.ac.kr  |  Phone: +82-51-629-6244 | Fax: +82-50-7088-1203

    • Nuri-gwan(A13) 1st Floor #2104 (Office)  | #2105, #2106 (Lab)

• Scientific Advisor, 4N Inc., Republic of Korea, 2021.03.01. – present.

  • 4N Inc.

    • E-mail: hhkim at 4nbrain.com

• Assistant Professor, Kangnam University, Republic of Korea, 2021.03.01. – 2022.08.31.

• CTO, 4N Inc., Republic of Korea, 2020.09.01. – 2021.02.28.

• Researcher (PI),  Information & Electronics Research Institute, Korea Advanced Institute of Science and Technology, Republic of Korea, 2019.09.01. – 2020.08.31.

• Researcher, Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Republic of Korea, 2020.03.01. – 2020.08.31.

• Researcher, Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Republic of Korea, 2019.09.01 – 2020.08.31.

• Researcher, Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Republic of Korea, 2017.03.01 – 2017.12.31.

• Combined M.S./Ph.D., Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Republic of Korea, 2019.

Member

• Han-Beot Park | Major: Materials Science and Engineering

• Do-Hyeon Lim | Major: Computer Engineering

• Yun-Jeong Cho | Major: Biomedical Engineering

• Seung-Hyuk Ko | Major: Data Engineering

• Myeong-Ju Jo | Major: Computer Engineering

• Gyujin Kim | Major: Biomedical Engineering

• Tae-Hoon Lee | Major: Applied Mathmatics

• (Alumni) Su-Min Beak | Major: Data Science

• (Alumni) Myo-kyeong Kim | Major: Data Science

• (Alumni) Hoe-young Lee | Major: Data Science

• (Alumni) Yeon-hee Choo | Major: Software Engineering

• (Alumni) Hyun-Ku Kang | Major: Data Science

Selected Publications

• Hoon-Hee Kim, Jaeseung Jeong, “An electrocorticographic decoder for arm movement for brain-machine interface using an echo state network and Gaussian readout”, Applied Soft Computing, 117, 108393, 2022. https://doi.org/10.1016/j.asoc.2021.108393 [IF: 6.725, JCR=0.09 < 10%, Rank: 11/111 (COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS)] 

• Hoon-Hee Kim, “Integrated Model of Reservoir Computing and Autoencoder for Explainable Artificial Intelligence", BMC Neuroscience, 21(Suppl 1), P99, 29th Annual Computational Neuroscience Meeting: CNS(Organization for Computational Neuroscience)-2020. https://doi.org/10.1186/s12868-020-00593-1

• Sungu Nam, Hoon-Hee Kim, Dong-Hwa Jeong, Youngjo Song, Jeungmin Lee, Jaeseung Jeong, “Questionnaire accuracy measurement and verification using bio signal sensor based virtual reality head mounted display”, 10th World Congress of Neuroscience (International Brain Research Organization; IBRO), 2019.

• Hoon-Hee Kim, Jaeseung Jeong, “Decoding electroencephalographic signals for direction in brain-computer interface using echo state network and Gaussian readouts”, Computers in Biology and Medicine, 110, 254-264, 2019. https://doi.org/10.1016/j.compbiomed.2019.05.024 [IF: 4.589, JCR=0.12 < 15%, Rank: 7/58 (MATHEMATICAL & COMPUTATIONAL BIOLOGY)]

• Hoon-Hee Kim, Jaeseung Jeong, “Decoding Electrocorticography Signals of the Arm Movement Using Echo State Networks”, The 3rd International Conference on Biomedical Imaging, Signal Processing, 2018.

• Hoon-Hee Kim, Jaeseung Jeong, “Predicting user intent directions in EEG using Echo State Network with Gaussian Readouts”, The 2nd International Conference on Medical Information and Bioengineering, 2017, (Best Presentation Award).

• Hoon-Hee Kim, Jaeseung Jeong, “Representations of directions in EEG-BMI using winner-take-all readouts”, IEEE 5th International Winter Conference on Brain-Computer Interface (BCI), Article number 7858178, Pages 121-122. 2017. https://doi.org/10.1109/IWW-BCI.2017.7858178 (Conference Paper)

• Hoon-Hee Kim, Seok-hyun Moon, Do-won Lee, Sung-beom Lee, Ji-yong Lee, Jaeseung Jeong, “Representations of directions in EEG‑BCI using Gaussian readouts”, BMC Neuroscience, 17(Suppl 1), P14, 25th Annual Computational Neuroscience Meeting: CNS(Organization for Computational Neuroscience)-2016. https://doi.org/10.1186/s12868-016-0283-6 

• Hoon-Hee Kim, Jaeseung Jeong, “The roles of short-term plasticity and synaptic weights in self-organized criticality”, BMC Neuroscience, 14(Suppl 1), P192-P192, 22nd Annual Computational Neuroscience Meeting: CNS(Organization for Computational Neuroscience)--2013. https://doi.org/10.1186/1471-2202-14-S1-P192

• Hoon-Hee Kim, Jaeseung Jeong, “Modeling Orientation Selectivity and Contrast Invariance using Recurrent Neural Networks without Attractors”, The 3rd Annual Meeting of Society for Computational Neuroscience, 2011. (Best Poster Award)

• Hoon-Hee Kim, Jaeseung Jeong, “Recovery of computation capability for neural networks from damaged states using self-organized criticality”, BMC Neuroscience, 11(Suppl 1), P30-P30, 19th Annual Computational Neuroscience Meeting: CNS(Organization for Computational Neuroscience)--2010. https://doi.org/10.1186/1471-2202-11-S1-P30

• Hoon-Hee Kim, Bon-Woong Ku, Byoung-Tak, “Modeling Orientation-Selectivity using Recurrent Neural Networks without Attractors”, Korea Computer Congress, 2008. 35(1C): p. 226-229, 2008. (Conference Paper)

Patents

• Hoon-Hee Kim, Seongkyun Kim, Jaehyung Kwon, “사용자의 생각을 디코딩하는 인공지능 시스템 (AN ARTIFICIAL INTELLIGENCE SYSTEM DECODING THE USER'S THOUGHTS)”, South Korea, Registration No. 10-2610810. (2023.12.01.), Application No.10-2022-0128484. (2022.10.07.).

• Hoon-Hee Kim, Seongkyun Kim, Jaehyung Kwon, “정신질환의 진단을 위한 설명 가능한 인공지능 시스템 및 정신질환 진단 방법 (EXPLAINABLE ARTIFICIAL INTELLIGENCE SYSTEM FOR DIAGNOSIS OF MENTAL DISEASES AND METHOD FOR DIAGNOSING OF MENTAL DISEASES)”, South Korea, Registration No. 10-2344532. (2021.12.23.), Application No.10-2021-0036451. (2021.03.22.).

• Hoon-Hee Kim, Seongkyun Kim, Jaehyung Kwon, “기계학습 모델을 이용한 전자약 처방 시스템 및 그 제어방법 (ELCTROCEUTICALS PRESCRIPTION AND THE CONTROL METHOD THEREOF USING MACHINE LEARCNING MODEL)”, South Korea, Registration No. 10-2316631. (2021.10.18.), Application No.10-2021-0036452. (2021.03.22.). 

• Hoon-Hee Kim, Seongkyun Kim, Jaehyung Kwon, “인공지능을 이용한 사용자의 생각을 단어로 도출하는 시스템 (SYSTEM FOR DERIVING THE USER'S THOUGHTS INTO WORDS USING ARTIFICIAL INTELLIGENCE)”, South Korea, Public No. 10-2023-0171413. (2023.12.20.), Application No. 10-2023-0172553. (2023.12.01.).

• Hoon-Hee Kim, Seongkyun Kim, Jaehyung Kwon, “EXPLAINABLE ARTIFICIAL INTELLIGENCE SYSTEM FOR DIAGNOSIS OF MENTAL DISEASES AND THE CONTROL METHOD THEREOF”, USA, Application No.17/531,619, under review. (2021.11.19.).

• Hoon-Hee Kim, Seongkyun Kim, Jaehyung Kwon, “ARTIFICIAL INTELLIGENCE SYSTEM DECODING USER'S THOUGHTS AND METHOD FOR CONTROLLING THEREO”, USA, Application No.18/047,073, under review. (2022.10.17.).

Miscellaneous

• Talk, Construction of Artificial Brain Models Using Individual EEG Data and Brain-Computer Interface Application, The Korean Society of Medical & Biological Engineering, 2024.05.10. 

• The Transfer of Technical Know-how, Technology for Developing Artificial Brain Models that Simulate Sensation-Perception Based on Individual EEG, 4N Inc., 2024.02.26.-2024.04.30.

• The Transfer of Technical Know-how, Implementation of qEEG reporting of large-scale EEG data using cloud computing, 4N Inc., 2023.03.02.-2023.03.20.

• Appearing of broadcast on YTN Science Today- Master of Science (SF 영화처럼 생각만으로 로봇 조종…인공두뇌 개발), 2022.03.10.

  • https://science.ytn.co.kr/program/program_view.php?s_mcd=0082&s_hcd=0031&key=202203101712448457&page=1

• 2nd Prize, AI Championship, Ministry of SMEs and Startups, 2020.11.20.

Research Project (PI)

• “Research on Spiking Neural Networks and Neuromorphic Simulations for Nonlinear Time Series Data Prediction”, Pukyong National University, 2024.09.01. - 2026.08.31.

• “Development of Artificial Intelligence-based Precise Detection System for False Statements using EEG-fMRI”, Ministry of Science and ICT / National Police Agency, 2022.07.01. - 2026.01.31

• “Development of a Portable Lightweight Brain-Machine Interface Using Low-Channel EEG Augmentation Technology”, LINC 3.0, 2024.08.22. - 2025.01.13.

• “Development of Software for Integrating Machine Learning Models to Enhance Information Capacity of Low-Channel EEG Measurement Devices”, 4N Inc., 2024.12.01. - 2024.12.31.

• “Development of Explainable Artificial Intelligence Based on Accumulated Computing for Edge-Mobile Environments”, Software Convergence Innovation Institute, 2024.08.01. - 2024.12.31.

• “Research on brain-machine interface decoder for smart device operation using spiking neural network with latent space”, Software Convergence Innovation Institute, 2024.08.01. - 2024.12.31.

• “Predicting Financial Time Series and Extracting Explainable Features using Reservoir Computing", Pukyong National University, 2022.09.01. - 2024.08.31.

• "Development of a new form of brain interface system for smart devices and the metaverse: User's thought command recognition brain-machine interface", Korea Technology and Information Promotion Agency for SMEs / Ministry of SMEs and Startups, 2022.07.01. - 2024.06.30.

• "A Study on the Optimal Learning Algorithm of EEG Decoder Based on Reservoir Computing”, 4N Inc., 2024.01.19. - 2024.02.28.

• "Development of an Artificial Intelligence for Long-term EEG Recording system", 4N Inc., 2022.12.06. - 2023.10.31.

• “A Study on Internal Unit Layer Size Optimization of EEG Decoder Based on Reservoir Computing”, 4N Inc., 2023.11.10. - 2023.12.31.

• “A Study on Spectral Radius Optimization of EEG Decoder Based on Reservoir Computing”, 4N Inc., 2023.08.11. - 2023.12.31.

• “Research on the Personal Electroencephalogram Data-Based Sensory-Perception Mimicking Artificial Brain Model for Brain-Machine Interface Decoders”, LINC 3.0, 2023.06.21. - 2023.12.31.

• “A Study on Brain-Machine Interface for Alternate Speech for Aphasia Patients”, X-Corps, 2023.04.01. - 2023.12.31.

• "Explainable Reservoir Computing Artificial Intelligence: Application for Nonlinear System Analysis", Pukyong National University, 2022.11.01. - 2023.10.31.

• "Target Detection based on Brain-computer Interface", Agency for Defense Development, 2022.07.01. - 2023.03.31.

• "Algorithm for Computational Function of Neuromorphic System", 4N Inc., 2022.12.28. - 2023.02.28.

• "Development of Long-term Usable and Comfortable EEG Recoding AI System", LINC 3.0, 2022.11.01. - 2023.02.28.

• “Implementation of qEEG Reporting of Large-scale EEG Data using Cloud Computing”, LINC 3.0, 2023.01.19. - 2023.02.20.

• "Development of Artificial Intelligence Algorithm for Ion-gel Neuromorphic Design", LINC 3.0, 2022.10.07. - 2023.01.31.

• "Development of Artificial Intelligence for EEG Analysis using Cloud Computing", 4N Inc., 2022.01.01. - 2022.06.30.

• "Research and Development of Artificial Intelligence Model for EEG and Bio-signal Processing", 4N Inc., 2021.10.01. - 2021.12.31.

• "Development of a Platform for Effective Management of Young Epilepsy Patients", Korea Health Industry Development Institute, 2020.12.18 - 2021.12.31(2025.08.31).

• "A Non-face-to-face EEG-based Depression Scale System", Gyeonggido Business & Science Accelerator, 2020.09.25 - 2020.11.30.

• "Development of Brain-inspired ‘White Box Machine Learning’ Methods for High Stakes Decision-Making", National Research Foundation of Korea, 2019.09.01. - 2020.08.31

BXAI Lab Survival Guides - Member Only

[Basic]

• 00 PI소개 / 인공지능관련 (학부) 교과목 소개 / 컴퓨터공학전공 & 인공지능전공 리터러시 (1 day)

  • 지도교수 및 연구실 소개, 컴퓨터공학/인공지능 전공 공부를 위한 교양지식

• 01 과학기술자료 (1 day)

  • 과학기술자료의 정의 및 검색 방법

• 02 과학글쓰기 (1 day)

  • 과학 글쓰기(연구계획서, 논문 등) 방법

• 03 연구 제안서 작성 (2 days)

  • 연구 제안서 작성 법 워크숍

• 04 How to Speak (MIT Patrick Winston) (1 day)

  • MIT의 Patrick Winston 교수님의 말하는 법 특강 

• 05 [Article] Ten simple rules for structuring papers (1 day)

  • 과학 논문 구조 설명

• 06 [Book] Science Research Writing A Guide for Non-Native Speakers of English (번역서: 유학생 및 과학자를 위한 영어논문 작성법) (3 days)

  • 영문 과학 논문 작성 법

• 07 [Book] How Not to Be Wrong-The Power of Mathematical Thinking (번역서: 틀리지 않는 법) (3 days)

  • 과학적 사고력 능력 함양

• 08 [Book] The Book of Why (3 days)

  • 과학적 사고력 능력 함양

• 09 [Book] (이상완) 인공지능과 뇌는 어떻게 생각하는가 (3 days)

  • 뇌 기반 인공지능 교양 서적

• 10 [Book] (제프 호킨스) 천개의 뇌 (3 days)

  • 뇌과학 교양 서적

[Core-0] 연구실 활동을 위해 필수로 수강해야할 교과목

• [Core-0-1-ML] 2-2학기 기계학습

• [Core-0-2-DL] 3-1학기 딥러닝1 3-2학기 딥러닝2

• [Core-0-3-TS] 4-1학기 시계열데이터

• [Core-0-4-NeuroAI] 4-2학기 뇌기반인공지능-2026학년도 오픈예정

[Core-1-ML] 기계학습 특강

• 01 1시간 만에 머신 러닝 개념 따라 잡기

• 02 PyTorch Crash Course

[Core-2-SNN] Spiking Neural Networks 특강 및 기본 논문 자료

• 01 Spiking Neural Networks

• 02 Tutorial on Spiking Neural Networks (Cosyne)

• 03 (Article) (Neuron Model) - 200311 - Simple model of spiking neurons

• 04 (Code) Spiking Neural Networks Implementation

[Core-3-RC] Reservoir Computing(축적 컴퓨팅) 특강 및 기본 논문 자료

• 01 Reservoir Computing Lecture

• 02 (Article) (LSM Seed) 200211 - Real-time computing without stable states a new framework for neural computation based on perturbations

• 03 (Article) (ESN Seed) 200404 - Harnessing nonlinearity Predicting chaotic systems and saving energy in wireless communication

• 04 (Article) (ESN) 201200 - A Practical Guide to Applying Echo State Networks

[Core-4-OCW] OpenCourseWare URL - 뇌 기반 인공지능, 기계학습/딥러닝, 계산신경과학 관련 추천 공개강좌 모음

• • AI Summer - Project Based Learning Lectures

    • https://theaisummer.com

  • INCF Training Space - Lectures

    • https://training.incf.org

  • Neuromatch - Deep Learning Lecture

    • https://deeplearning.neuromatch.io/tutorials/intro.html

    • https://github.com/NeuromatchAcademy/course-content-dl

  • Neuromatch - NeuroAI

    • https://neuroai.neuromatch.io/tutorials/intro.html

    • https://github.com/neuromatch/NeuroAI_Course

  • Neuromatch - Computational Neuroscience

    • https://compneuro.neuromatch.io/tutorials/intro.html

    • https://github.com/NeuromatchAcademy/course-content

  • NeuroML - Neuroscience for machine learners

    • https://neuro4ml.github.io/

[D-BMI] Domain - Brain-machine Interface (4 weeks)

• 01  Introduction Brain-machine Interface

  • 뇌-기계 인터페이스 개론 강의

• 02 Practical Brain-machine Interface

  • Python, MNE, PyTorch 등을 이용한 뇌-기계 인터페이스 구현 실습 강의

• 03 (PT)EEG 실험프로토콜 with OpenBCI

  • 뇌파, BMI 실험 프로토콜 개발 방법

• 04  (Article) 201208 - Toward brain-actuated humanoid robots Asynchronous direct control using an EEG-Based BCI

  • 기계학습을 이용한 뇌-기계 인터페이스 구현 연구

[D-FNC] Domain - Finance (4 weeks)

• 01 Domain Study

  • 도메인 지식 이해를 위한 중요 용어 리스트 및 구현 패키지

• 02  Data Collecting

  • 금융 데이터 수집 구현 방법

• 03 (Journal) 200904 - Short-term stock price prediction based on echo state networks

  • Reservoir Computing을 이용한 주가 예측

• 04 (Journal) 201109 - Intelligent stock trading system based on improved technical analysis and Echo State Network

  • 기술적 지표 최적화와 Reservoir Computing을 이용한 주가 Trend 예측

  • 본 연구 논문 구현 프로젝트 진행

[Resource]

• Notion(Member Only): https://brainxai.notion.site 

• Cloud Computing: Amazon Web Service (https://aws.amazon.com), Vultr (https://www.vultr.com)

• EEG Hardware: BEL-EEG (https://www.bel.company, 130 Channels), OpenBCI (https://openbci.com)

• MEG/EEG Analysis & Visualization (https://mne.tools)

• GPU Platform: PyTorch (https://pytorch.org)

• Spiking Neural Networks: Open NeuroMorphic(https://open-neuromorphic.org)

• AI Tools: ChatGPT Team(https://chatgpt.com)

• Local GPU Machines (in Lab)