About

I am an Applied Scientist at Amazon AWS AI Labs, working on LLM-assisted code development. I obtained my Ph.D. degree in 2024, from the department of Electrical and Computer Engineering (ECE) at the University of Illinois at Urbana-Champaign (UIUC). My research spans Computer Vision, Large Language Models(LLMs), Multi-modal Learning and Generative Modeling, with a particular focus on developing efficient and robust approaches for real-world applications.

Research Interests

Machine Learning, Computer Vision, LLMs, Multimodal Learning, Generative Modeling, Foundation Models, Efficient ML.

Current and Past Affiliations

Amazon 2024-Now Summer-Fall 2022, Summer 2023	UIUC 2019-2024	Microsoft Fall 2023	IBM Watson Summer 2020

C3SR 2019-2021	UCLA Summer 2018	Technion Summer 2017	UESTC 2015-2019

Projects

	Understanding and Constructing Latent Modality Structures in Multi-modal Representation Learning Qian Jiang, Changyou Chen, Han Zhao, Liqun Chen, Qing Ping, Son Dinh Tran, Yi Xu, Belinda Zeng, Trishul Chilimbi CVPR 2023 PDF
	EH-DNAS: End-to-End Hardware-aware Differentiable Neural Architecture Search Qian Jiang*, Xiaofan Zhang*, Deming Chen, Minh N. Do, Raymond A. Yeh ICML Workshop 2023 PDF Code
	Federated Recommendation via Hybrid Retrieval Augmented Generation Huimin Zeng, Zhenrui Yue, Qian Jiang, Dong Wang IEEE Big Data 2024 PDF
	SLA: Stochastic Label Augmentation for Robust Vision-Language Contrastive Learning. Qian Jiang, Jingjing Meng, Alireza Bagheri Garakani, Yang Jiao, Yetian Chen, Yikai Ni, Yan Gao, Yi Sun, Changyou Chen Under Review PDF
	When Contrastive Learning Meets Bayesian Modeling: Learning Multi-Modal Representation Alignments with Noisy Data-Pairs Qian Jiang, Jingjing Meng, Alireza Bagheri Garakani, Yang Jiao, Yetian Chen, Yikai Ni, Yan Gao, Yi Sun, Changyou Chen Under Review PDF
	Multi-source transfer learning by learning to weight past tasks Qian Jiang, Raymond A. Yeh, Minh N. Do. Under Review

Work Experiences

• Research Intern @ Microsoft (Fall 2023)
• Applied Scientist Intern @ Amazon (Summer 2023)
• Applied Scientist Intern @ Amazon (Summer Fall 2022)
• Research Intern @ IBM Watson (Summer 2020)

Teaching Experiences

• ECE311 - Digital Signal Processing Lab @UIUC (Spring 2022)
• ECE310 - Digital Signal Processing @UIUC (Fall 2021)

Other Experiences

• Cross-disciplinary Scholar in Science and Technology (CSST) @ Univesity of California, Los Angeles (UCLA) (Summer 2018)
• Summer School of Engineering @ Israel Institute of Technology (Technion) (Summer 2017)

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