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Shutong JIN

Shutong JIN

PhD Candidate · WASP Scholar
schedule
4th Year
PhD Candidate
article
15+
Publications
school
WASP
KTH / Berkeley

Hi there! I am a fourth-year PhD student at KTH Royal Institute of Technology, supervised by Prof. Florian Pokorny (main supervisor) and Prof. Erik Elmroth (co-supervisor). Previously, I completed my Master’s degree at Nanyang Technological University and my Bachelor’s degree at Wuhan University. My research is funded by the Wallenberg AI, Autonomous Systems and Software Program (WASP).

I am currently at the UC Berkeley AUTOLAB as a visiting PhD student under the supervision of Prof. Ken Goldberg.

KTH Royal Institute of Technology UC Berkeley AUTOLAB WASP Fellow
VIEW PUBLICATIONS arrow_downward GET IN TOUCH east
15+
Publications
3
Research Threads
4+
Workshop / Service Roles
WASP
Scholar & Fellow
"Designing tomorrow's generalizable robots through data-centric foundations."
— Shutong JIN
Highlights

FEATURED CASE STUDIES

Selected research highlights on cloud robotics, illumination perception, and generative robot learning.

#01
CloudGripper

CloudGripper: Scalable Cloud-Based Benchmarking

ICRA 2026 work on cloud-connected fleet learning & benchmark environments for robotic manipulation.

Cloud Robotics Scaling ICRA 2026
#02
Computational Illumination

Illumination-Aware Grasping & Perception

IEEE TMM paper on active computational illumination for robust perception in complex clutter.

Perception IEEE TMM Understanding
#03
Generative Scene Synthesis

Generative Scene & Data Curation

CoRL & IROS research on quality-aware data selection and generative data augmentation for robotics.

Generative AI CoRL 2025 Curating
System & Expertise

SKILLS, TECH & PHILOSOPHY

SKILLS & EXPERTISE
Robotic Data Curation 95%
Generative Modeling 90%
Computational Illumination 88%
Representation Learning 90%
Cloud & Fleet Robotics 85%
Active Perception & Sensing 80%
TECH STACK
code
PyTorch
smart_toy
ROS / ROS2
code
Python
code_blocks
C++
memory
CUDA
view_in_ar
CloudGripper
precision_manufacturing
Isaac Sim
visibility
OpenCV
cloud
Git / Linux
RESEARCH PHILOSOPHY
DATA-CENTRIC AI
Understanding
Curating
Scaling
Generalization
Updates

RECENT NEWS & RESEARCH THREADS

analytics

1. Understanding

Decoding perception & active sensing in physical clutter through computational illumination and neural light fields.

filter_alt

2. Curating

Treating robot data as a primary artifact: quality metrics, generative scene synthesis, and cross-embodiment curation.

cloud_sync

3. Scaling

Scaling manipulation policies to cloud-connected robot fleets with CloudGripper benchmarks and foundation VLA models.

KEYWORD LANDSCAPE

The Periodic Table of Our Research

Seven focus areas arranged as elements — clear, compact, fully static.

7 Topics 3 Groups Static View
01
RDC
Robotic Data Curating
02
IL
Imitation Learning
03
GM
Generative Modeling
04
AP
Active Perception
05
CI
Computational Illumination
06
VLA
VLA Models
07
CR
Cloud Robotics
Robotics Systems
Learning & Modeling
Perception & Rendering
Scholarly Work

PUBLICATIONS

15 peer-reviewed papers in ICRA, IROS, CoRL, CVPR, NeurIPS, IEEE TMM, and RA-L.

Community & Background

ACADEMIC SERVICE & EDUCATION

school Teaching

DD2424: Artificial Intelligence TA @ KTH2023–25
DD1420: Applied Artificial Intelligence TA @ KTH2022–24

groups Workshop Organization

RoDGE 2026: Robot Data Governance @ ICRA2026
CloudGripper 2026: Cloud Manipulation @ ICRA2026
Connected-Robots 2024 @ IROS2024

rate_review Reviewing

RSSCoRLICRAIROSRA-LIEEE TMMNeurIPS

diversity_3 MSc Supervision

Axel L. (Diffusion Policy Failure Modes)2025
Ben C. (Generative Scene Synthesis)2024
Jin W. (Cloud Robotics Benchmarking)2024
Journey

EDUCATION TIMELINE