Ph.D. of Informatics
2018 - 2022
Nagoya University
2026
Latest publication year
4
Research and founder roles
9+
Years in driving intelligence
4
Working languages
About me
Naren Bao
I work at the intersection where AI meets the physical world.
As a researcher at the University of Tokyo, I focus on how autonomous systems perceive, reason, and act in real environments — from vision-language models for causal reasoning to sim-to-real deployment in industrial settings.
As founder of AquaAge, I've built and shipped AI-powered products across computer vision, real estate, and Agentic AI — learning firsthand what breaks when models leave the lab.
What I bring to the table
- 10+ publications at ITSC, IV, ICRA on autonomous perception and risk modeling
- Hands-on experience deploying AI systems in Japanese industrial environments
- Trilingual (Chinese / Japanese / English) perspective across three of the world's largest Physical AI ecosystems
I write about Physical AI Engineering — the messy, practical reality of making intelligent systems work in the real world.
Read on noteJPResearcher at The University of TokyoFounder of AquaAge Inc.Physical AI engineeringVision-language reasoningSim-to-real deployment
Continue to profileEducation
I believe that personal education never ends.
Master of Information Science
2016 - 2018
Nagoya University
Bachelor of Software Engineering
Completed
Tianjin University
Visiting Scholar
2019
The Ohio State University
Experience
Years of experience prove the through-line.
May 2023 - Present
Project Assistant Professor
The University of Tokyo
Working in the fields of Generative AI-based autonomous driving, cooperative perception, and computer vision for robotics.
September 2019 - Present
Founder and CEO
AquaAge Inc.
Founded AquaAge Inc. during the Ph.D. course at Nagoya University of Informatics.
- Builds data-centric image and data analysis solutions for business partners.
- Runs HADABON, a mobile app for personalized skincare services.
April 2016 - December 2022
NEDO Research Student
RoboticsCore Explainable AI Project
Built a data-driven control framework with inverse optimal control to estimate risk-sensitive driving features and incorporate them into a receding-horizon controller.
- Modeled individual differences in subjective driving risk.
- Tested five lane-change scenarios with thirty real drivers in CARLA.
March 2019 - 2021
Simulation System Constructor
Street Map Project in CARLA
Built simulated Nagoya University buildings using OpenStreetMap, Unreal Engine, and Blender for an autonomous testing simulation system.
- Designed and developed driving-condition scenarios for testing control algorithms.
Publications
Papers, workshops, patents, and books.
International JournalInternational Conference PaperDomestic Paper and WorkshopsPatentBook
20262 items
ICRA 2026
A Synthetic Benchmark for Collaborative 3D Semantic Occupancy Prediction in V2X-Enabled Autonomous Driving
Hanlin Wu, Pengfei Lin, Ehsan Javanmardi, Naren Bao, Bo Qian, Hao Si, Manabu Tsukada
IEEE International Conference on Robotics & Automation, Vienna, Austria, 2026.
Manuscript submitted to OJ-ITS
Foundation Models for Driving World Models: A Survey of Encoders, Simulators, Reasoners, and Data Engines
Bao, Naren; Carballo, Alexander; Javanmardi, Ehsan; Tsukada, Manabu; Takeda, Kazuya
Manuscript submitted to IEEE Open Journal of Intelligent Transportation Systems; not yet peer-reviewed. Prefer the official journal or arXiv BibTeX after publication.
Source20253 items
METACOM2025
4D Path Planning via Spatiotemporal Voxels in Urban Airspaces
Naren Bao, Alex Orsholits, Manabu Tsukada
The 3rd Annual IEEE International Conference on Metaverse Computing, Networking, and Applications, Seoul, Korea, 2025.
arXiv
A Synthetic Benchmark for Collaborative 3D Semantic Occupancy Prediction in V2X Autonomous Driving
Hanlin Wu, Pengfei Lin, Ehsan Javanmardi, Naren Bao, Bo Qian, Hao Si, Manabu Tsukada
arXiv preprint arXiv:2506.17004, 2025.
DICOMO2025
V2X通信における占有格子地図の共有とAutowareを用いた検証
松澤力, Naren Bao, Ehsan Javanmardi, 塚田 学
マルチメディア，分散，協調とモバイル(DICOMO2025)シンポジウム, 福島, 母畑温泉, 2025.
20242 items
ICEA2024
Best Paper Award (Silver)Cross-Attention Enhanced Imitation Learning for End-to-end Autonomous Driving in Unprotected Turns
Dongyang Li, Ehsan Javanmardi, Naren Bao, Manabu Tsukada
International Conference on Intelligent Computing and its Emerging Applications, Tokyo, Japan, 2024.
ITSC 2024 Workshop
Vision Language Model-based Human-Centered Autonomous Driving
Organizer of Workshop
The 27th IEEE International Conference on Intelligent Transportation Systems, Edmonton, Canada, 2024.
20234 items
IEEE Internet of Things Journal
Secure and Efficient Blockchain-Based Federated Learning Approach for VANETs
M. Asad, S. Shaukat, E. Javanmardi, J. Nakazato, N. Bao, M. Tsukada
IEEE Internet of Things Journal, vol. 11, no. 5, pp. 9047-9055, 1 March 2024, doi: 10.1109/JIOT.2023.3322221.
IoR-WS 2023
Towards a Trusted Inter-Reality: Exploring System Architectures for Digital Identification
Naren Bao, Jin Nakazato, Muhammad Asad, Ehsan Javanmardi, Manabu Tsukada
The 1st International Workshop on Internet of Realities at International Conference on the Internet of Things, Nagoya, Japan, 2023.
ITSC2023
Personalized Causal Factor Generalization for Subjective Risky Scene Understanding with Vision Transformer
Bao, Naren, Carballo, Alexander, Tsukada, Manabu, Takeda, Kazuya
The 26th IEEE International Conference on Intelligent Transportation Systems, Bilbao, Bizkaia, Spain, 2023.
Towards Human-Vehicle Harmonization
Personalized Lane Changes Using Subjective Risk-Sensitive Framework
Naren Bao, Alexander Carballo, Kazuya Takeda
Towards Human-Vehicle Harmonization 3, 2023, p. 211.
20222 items
IV2022
Driving Risk and Intervention: Subjective Risk Lane Change Dataset
Naren Bao, Alexander Carballo, Kazuya Takeda
33rd IEEE Intelligent Vehicles Symposium, Aachen, Germany, June 2022.
IEEE Access
Data-driven Risk-Sensitive Control for Personalized Lane Change Maneuvers
Naren Bao, Linda Capito, Dongfang Yang, Alexander Carballo, Chiyomi Miyajima, Kazuya Takeda
IEEE Access, Jan. 2022, doi: 10.1109/ACCESS.2022.3163267.
20211 items
IV2021
Prediction of Personalized Driving Behaviors via Driver-adaptive Deep Generative Models
Naren Bao, Alexander Carballo, Kazuya Takeda
32nd IEEE Intelligent Vehicles Symposium, Nagoya, July 2021.
20201 items
JRM
Personalized Subjective Driving Risk: Analysis and Prediction
Naren Bao, Alexander Carballo, Chiyomi Miyajima, Eijiro Takeuchi, Kazuya Takeda
Journal of Robotics and Mechatronics, Vol. 32 No. 3, June 2020.
20191 items
ITSC2019
Personalized Safety-focused Control by Minimizing Subjective Risk
Naren Bao, Dongfang Yang, Alexander Carballo, Umit Ozguner, Kazuya Takeda
2019 IEEE Intelligent Transportation Systems Conference, Auckland, New Zealand, Oct. 27-30, pp. 3853-3859.
20181 items
IEICE2018
Estimating Subjective Driving Risk Feeling using Random Forest
Naren Bao, Chiyomi Miyajima, Akira Tamamori, Eijiro Takeuchi, Kazuya Takeda
2018 IEICE General Conferences, Tokyo, Mar. 2018.
20172 items
4th FASTZERO
Estimating Risk Levels Perceived by Individuals for Lane Change Scenes
Naren Bao, Chiyomi Miyajima, Eijiro Takeuchi, Kazuya Takeda, Shinichiro Honda, Toshiya Yoshitani, Masayoshi Ito
The fourth International Symposium on Future Active Safety Technology Toward zero traffic accidents, Nara, Sept. 2017.
IPSJ
Analysis of Individual Risk Perception during Highway Lane-Change Scenes
Naren Bao, Chiyomi Miyajima, Eijiro Takeuchi, Kazuya Takeda
The 79th National Convention of IPSJ, Nagoya, Mar. 2017.
20161 items
IV2016
Prediction of Individual Driving Behavior on Highway Curves
Naren Bao, Daiki Hayashi, Chiyomi Miyajima, Kazuya Takeda
The third Workshop on Naturalistic Driving Data Analytics, IEEE Intelligent Vehicles Symposium, Gothenburg, June 2016.
Languages and Skills
Practical range for research and building.
Languages
Chinese100%
ᠮᠤᠩᠭᠤᠯ ᠬᠡᠯᠡ (Mongolian)100%
Japanese95%
English95%
Skills
Data Science95%
Image Analysis95%
Cloud Computing90%
Web Development90%
Business90%
Robotics and Optimization80%
Unreal Engine70%
Blender60%
Certificates
Continuous learning, in the form of small course completions.
Contact me
Let's get in touch.
For research collaboration, product conversations, or data-centric projects, send a short note by email or connect through the links below.