Zhizhang "Kevin" Hu

Zhizhang "Kevin" Hu

About Me

Hi, Welcome to my page! I am an Applied Scientist at Amazon. I work on multi-lingual multi-modal LLMs. I earned my Ph.D. in Electrical Engineering and Computer Science at University of California, Merced with a focus on multimodal learning and ubiquitous computing. Please feel free to contact me if you want to chat/ collaborate/ ask for the latest resume :-D.

Interests
  • Multimodal Large Language Model
  • Multi-agent Reasoning
Education
  • Ph.D. in Computer Science, 2024

    University of California, Merced

  • M.Sc in Building Science, 2020

    Carnegie Mellon University

  • B.Eng in Mechanical Engineering, 2018

    Southwest Jiaotong University

Experience

 
 
 
 
 
Amazon Inc.
Applied Scientist II
Amazon Inc.
Apr 2025 – Present
Multi-lingual multi-modal large language models.
 
 
 
 
 
Microsoft AI
Research Data Scientist II
Microsoft AI
Jan 2025 – Apr 2025
Multi-agent spatial intellegence and open-world visual language reasoning.
 
 
 
 
 
University of California, Merced
Ph.D. Researcher
University of California, Merced
Aug 2020 – Dec 2024

Work in following areas:

  • Physics-informed multimodal sensing and learning algorithms.
  • Causal inference for deep learning bias reduction.
  • Smart healthcare with heterogeneous Internet of Things(IoT) systems.
  • Representation learning and transfer learning algorithms.

Recent Publications

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(2024). De-noised Vision-language Fusion Guided by Visual Cues for E-commerce Product Search. 2024 IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) Workshops.

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(2024). IOTeeth: Intra-Oral Teeth Sensing System for Dental Occlusal Diseases Recognition. IMWUT 2024.

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(2023). ProVLA: Compositional Image Search with Progressive Vision-language Alignment and Multimodal Fusion. 2023 IEEE/CVF International Conference on Computer Vision (ICCV) Workshops.

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(2022). CIPhy: Causal Intervention with Physical Confounder from IoT Sensor Data for Robust Occupant Information Inference. SenSys 2022 AIoT Workshop.

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(2022). MODES: multi-sensor occupancy data-driven estimation system for smart buildings. ACM e-Energy.

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(2022). Demo: Real-Time Teeth Functional Occlusion Monitoring via In-Mouth Vibration Sensing. IPSN 2022.

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(2022). Poster: Sedentary Posture Muscle Monitoring via Active Vibratory Sensing. IPSN 2022 (Best Poster Award).

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(2021). AutoQual: task-oriented structural vibration sensing quality assessment leveraging co-located mobile sensing context. CCF Transactions on Pervasive Computing and Interaction.

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(2021). Footstep-Induced Floor Vibration Dataset: Reusability and Transferability Analysis. SenSys 2021 DATA Workshop.

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(2021). Poster: Vibration-based Indoor Occupant Gait Monitoring with Robot Vacuum Cleaners. IoTDI 2021.

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(2021). Vibration-based indoor human sensing quality reinforcement via Thompson sampling. Proceedings of the First International Workshop on Cyber-Physical-Human System Design and Implementation.

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(2020). A window-based sequence-to-one approach with dynamic voting for nurse care activity recognition using acceleration-based wearable sensor. UbiComp/ISWC 2020 Workshop(Best Paper Award).

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(2020). Fine-grained activities recognition with coarse-grained labeled multi-modal data. UbiComp/ISWC 2020 CML-IoT Workshop.

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(2020). Improving the Interoperability of gbXML Data Model through Redefining Data Mapping Rules of HVAC Systems. ASHRAE Transactions.

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(2019). Device-free sleep stage recognition through bed frame vibration sensing. BuildSys 2019 DFHS Workshop.

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Contact Me