About me

Hi! I am Haoren, a final year Ph.D candidate in Electrical and Computer Engineering at the National University of Singapore advised by Professor Vadakkepat Prahlad and Professor Ho Weng Khuen. I am very fortunate to work closely with Prof. Lee Tong Heng and Prof. Abdullah Al Mamun in NUS, and Dr. Haiyue Zhu from SIMTech, A*Star.

I obtained my bachelor’s degree in Electrical Engineering from National University of Singapore, with a distinction in May 2021. I have joined the Huawei Singapore Research Center as an Architectural Computing Algorithm Engineer since May 2025.

Email: haorenguo_06@u.nus.edu

Research Interests

• machine learning
• neural network and deep learning
• time series prediction
• predictive maintenance
• domain adaptation
• self-supervised learning
• efficient AI
• large language model

Recent News

• [Nov 2025]. Our work "EPSegFZ: Efficient Point Cloud Semantic Segmentation for Few- and Zero-Shot Scenarios with Language Guidance" is accepted by AAAI 2026 as an Oral presentation!
• [Sep 2025]. Our work "SingRef6D: Monocular Novel Object Pose Estimation with a Single RGB Reference" is accepted by NeurIPS 2025!
• [Aug 2025]. I completed my Ph.D Oral Defence!
• [May 2025]. I’m very glad to join Huawei Singapore Research Center as Architectural Computing Algorithm Engineer!
• [Mar, 2025]. "SDSimPoint: Shallow--Deep Similarity Learning for Few-Shot Point Cloud Semantic Segmentation" is published by the IEEE Transactions on Neural Networks and Learning Systems!
• [Dec, 2024]. "Enhancing Multivariate Time-Series Domain Adaptation via Contrastive Frequency Graph Discovery and Language-Guided Adversary Alignment" is accepted by the Thirty-Ninth AAAI Conference on Artificial Intelligence (AAAI-25)!
• [May, 2024]. "Remaining Useful Life Prediction via Frequency Emphasizing Mix-Up and Masked Reconstruction" is accepted by IEEE Transaction on Artificial Intelligence (TAI)!
• [Oct, 2023]. "Lightweight Compressed Temporal and Compressed Spatial Attention with Augmentation Fusion in Remaining Useful Life Prediction" and "Few-Shot Point Cloud Semantic Segmentation for CAM/CAD via Feature Enhancement and Efficient Dual Attention" are accepted by IECON-2023!
• [Jun, 2023]. I passed my oral qualification exam.
• [Jan, 2023]. "Few-shot point cloud semantic segmentation via contrastive self-supervision and multi-resolution attention" is accepted by ICRA-2023!
• [July, 2022]. "CAM/CAD Point Cloud Part Segmentation via Few-Shot Learning" and "Masked Self-Supervision for Remaining Useful Lifetime Prediction in Machine Tools" are accepted by INDIN-2022!