Academic Curriculum Vitae

Indoor Positioning, PDR, Sensor Fusion, and Deep Learning

I am an M.S. student in Computer Engineering at Hallym University. My research focuses on AI-based indoor positioning systems that combine pedestrian dead reckoning, wireless signals, and smartphone inertial sensors for robust navigation in GNSS-denied environments.

Education

2026–Present

M.S. in Computer Engineering

Department of Computer Engineering, Hallym University

2020–2026

B.S. in Software

Division of Software, College of Information Science, Hallym University

Scholarships

Spring 2026

Merit Scholarship in Science and Engineering

Graduate School, Hallym University

KRW 2,500,000

Publications

Manuscripts Under Review

International Journals
  1. M2

    Kim, B., & Shin, B. (2026).

    A Robust Multi-Carrying-Mode End-to-End Deep Learning Framework for PDR.

    IEEE Sensors Journal.

    Under Review
  2. M1

    Li, S., Kim, B., & Shin, B. (2026).

    AI-Based Orientation-Robust Vehicle Dead Reckoning Using Smartphone IMU Sensors.

    IEEE Sensors Journal.

    Under Review

Manuscripts Under Review

Domestic Journals · KCI
  1. K3

    Yoo, S., Kim, B., Cho, S., & Shin, B. (2026).

    A High-Speed Wi-Fi Collection Device and a Radio Map Construction Method for Surface Correlation-Based Indoor Positioning.

    Journal of Positioning, Navigation, and Timing.

    Under Review
  2. K2

    Kim, J., Kim, H., Kim, B., Park, S., & Shin, B. (2026).

    Autonomous Exploration-Based Radio Map Construction for Indoor Localization Using a Mobile Robot Platform.

    Journal of Positioning, Navigation, and Timing.

    Under Review

International Journals

SCI/SCIE
  1. J2

    Kim, B., Li, S., Kim, J., & Shin, B. (2026).

    AI-Generated Spatial Pattern Matching for Hospital Indoor Positioning.

    Applied Sciences, 16(5), 2552.

    JCR Q2 · Engineering, Multidisciplinary · IF 2.7 (2024)

    DOI: 10.3390/app16052552
  2. J1

    Shin, B., Li, S., & Kim, B. (2025).

    Deep Learning-Based Vehicle Speed Estimation Using Smartphone Sensors in GNSS-Denied Environment.

    Applied Sciences, 15(16), 8824.

    JCR Q2 · Engineering, Multidisciplinary · IF 2.7 (2024)

    DOI: 10.3390/app15168824

Domestic Journals

KCI
  1. K1

    Kim, J., Kim, B., & Shin, B. (2025).

    Performance Analysis and Compensation Methods According to PDR Drift and Radio Map Resolution.

    Journal of Positioning, Navigation, and Timing, 14(3), 195–202.

    DOI: 10.11003/JPNT.2025.14.3.195

Domestic Conferences

Proceedings
  1. C5

    Kim, B., Li, S., & Shin, B. (2025).

    Development of an LSTM-Based AI-PDR System Utilizing Smartphone IMU.

    Proceedings of the IPNT Conference, Nov. 5–7, 2025, Jeju, Korea.

    Proceedings
  2. C4

    Li, S., Kim, B., & Shin, B. (2025).

    Smartphone-Based Vehicle Trajectory Estimation Using Attention-LSTM.

    Proceedings of the IPNT Conference, Nov. 5–7, 2025, Jeju, Korea.

    Proceedings
  3. C3

    Kim, J., Kim, B., & Shin, B. (2025).

    Impact of PDR Drift and Radio Map Resolution on SC-based Indoor Localization.

    Proceedings of the IPNT Conference, Nov. 5–7, 2025, Jeju, Korea.

    Proceedings
  4. C2

    Li, S., Kim, B., & Shin, B. (2025).

    A Study on the Estimation of Vehicle Speed Using Smartphone Sensor Data with AI Technology.

    Proceedings of the KICS Conference, Feb. 5–7, 2025, Yongpyong, Korea.

    Proceedings
  5. C1

    Kim, B., & Shin, B. (2024).

    Enhancing Smartphone-Based Pedestrian Dead Reckoning Using AI in Various Motions.

    Proceedings of the IPNT Conference, Nov. 6–8, 2024, Jeju, Korea.

    Proceedings

Awards

2025

Silver Award, Hallym University SW Capstone Design Competition

Development of a low-cost indoor positioning system using a Wi-Fi radio map and Surface Correlation for the Hallym University Engineering Building.

Research Projects

Integrated Analysis and Inference System for Cybercrime Investigation Clues Police Science Institute
  • Participating researcher in a large-scale national R&D project.
  • Developing enhanced target-location tracking techniques.
  • Researching burner-phone detection using communication transaction data.
  • Designed and implemented a call-history pattern-based burner-phone estimation algorithm.
AI-Based Low-Cost Hospital Indoor Positioning System Hallym University AI Convergence Research Institute · Completed
  • Collected real-world data and developed an AI-PDR model.
  • Constructed a radio map for the first floor of Hallym Sacred Heart Hospital.
  • Designed and evaluated an inertial-wireless fusion algorithm combining Surface Correlation and AI-PDR.
  • Published the experimental results in Applied Sciences.
Low-Power Remote Digital Signage Using E-Paper and Generative AI Startup Growth Technology Development Program · Completed
  • Analyzed system power consumption and verified energy efficiency.
  • Quantitatively evaluated whether the e-paper signage platform met low-power operating requirements.
  • Patent application: “Posted Content Management System for E-Paper Displays” (10-2025-0129940).