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Jianga Shang

School of Computer Science

China University of Geosciences

Hands-onFriendly PeersTravel OftenRespects Privacy
4.0/ 5.0
5 student reviews
👍4
👎0
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About Jianga Shang at China University of Geosciences

Shang Jianga is a Professor in the School of Computer Science at China University of Geosciences (Wuhan) and a PhD supervisor. He is a researcher at the National Engineering Research Center for Geographic Information Systems and leads the UbiLoc team, focusing on software technologies for spatial intelligence and human–cyber–physical systems. His recent research centers on AI foundation models and intelligent agents applied to spatial intelligence, digital twins, and large-scale cyber-physical systems. He has led and participated in multiple national research projects and industry collaborations, and has published extensively in international journals such as IEEE TMC, IEEE IoT Journal, and IJGIS.

Research Areas

Large-Scale Artificial Intelligence ModelsAI AgentsSpatial IntelligenceHuman–Cyber–Physical Systems (HCPS)Digital TwinGIS Software EngineeringIndoor PositioningUbiquitous ComputingIntelligent ConstructionMobile Computing

Rating Breakdown

Supervision Style3.0
Responsiveness4.0
Workload4.0
Funding Support4.0
Communication4.0

Reviews (1)

👍

A student recommended this supervisor and marked them as Hands-on

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8 months ago

👍

A student recommended this supervisor and marked them as Respects Privacy

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5 months ago

👍

A student recommended this supervisor and marked them as Travel Often

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1 months ago

👍

A student recommended this supervisor and marked them as Friendly Peers

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3 weeks ago

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Anonymous12/28/2025
★4.0

In my experience, the advisor maintained a clear hierarchical relationship with students. Initial interactions were very friendly and approachable, and early communication felt warm and encouraging, which helped lower the barrier for new students. Over time, however, expectations became more demanding, and day-to-day work involved a high volume of tasks and detailed follow-ups. Feedback tended to focus closely on specifics, which can be helpful for students who prefer structure, but may feel intense for those seeking more autonomy. Overall, this advising style may suit students who are comfortable with a fast-paced environment and frequent task-level coordination

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