Lu Ling (original) (raw)

I am Lu Ling, a PhD student in the IDEADs Lab and CGV Lab at Purdue University, advised by Prof. Aniket Bera. I am passionate about all aspects of 3D/4D GenAI and multi-modal models, including generative AI, vision-language modeling, and agentic AI for reasoning and planning. To contribute to this field, I led the DL3DV-10K project, a real-world scene dataset to forge a path toward a foundation model for learning 3D representation. I was a NVIDIA Research intern in 2024 summer and fall, and working with Zhaoshuo Li, Chen-Hsuan Lin, Tsung-Yin Lin, and Ming-Yu Liu Email / CV / Google Scholar / LinkedIn

Research

	Scenethesis: A Language and Vision Agentic Framework for 3D Scene Generation Lu Ling, Chen-Hsuan Lin, Tsung-Yi Lin, Yifan Ding, Yu Zeng, Yichen Sheng, Yunhao Ge, Ming-Yu Liu, Aniket Bera, Zhaoshuo Li under review An Agentic Framework for Text-to-3D Scene Generation. The generated scenes are diverse, interactive, realistic, and physically plausible for cirtual content creation, editing, simulation, and embodied AI. > proj > paper [> code ](coming soon)
	DL3DV-10K: A Large-Scale Scene Dataset for Deep Learning-based 3D Vision Lu Ling, Yichen Sheng, Zhi Tu, Wentian Zhao, Cheng Xin, Kun Wan, Lantao Yu, Qianyu Guo, Zixun Yu, Yawen Lu, Xuanmao Li, Xingpeng Sun, Rohan Ashok, Aniruddha Mukherjee, Hao Kang, Xiangrui Kong, Gang Hua, Tianyi Zhang, Bedrich Benes, Aniket Bera CVPR 2024 10K real-world scene dataset for 3D vision > proj > paper > code
	Dr.Bokeh: DiffeRentiable Occlusion-aware Bokeh Rendering Yichen Sheng, Zixun, Yu, Lu Ling, Zhiwen Cao, Cecilia Zhang, Xin Lu, Ke Xian, Haiting Lin, Bedrich Benes CVPR 2024 Lens blur effects in image compositing > proj > video
	PixHt-Lab: Pixel Height Based Light Effect Generation for Image Compositing Yichen Sheng, Jianming Zhang, Julien Philip, Yannick Hold-Geoffroy, Xin Sun, HE Zhang, Lu Ling, Bedrich Benes CVPR 2023 (highlight) Light effects synthesis in image compositing > paper > code
	Cooperating Graph Neural Networks with Deep Reinforcement Learning for Vaccine Prioritization Lu Ling, Washim Uddin Mondal, Satish V. Ukkusuri IEEE Journal of Biomedical and Health Informatics (2024) Reinforcement learning, graph neural network, deep learning, disease diffusion > paper
	Investigating the effects of vaccine on COVID‑19 disease propagation using a Bayesian approach Lu Ling, Satish Ukkusuri Scienfic Reports (2023) Causality inference, Prediction and interpretation > paper
	Spatiotemporal impacts of human activities and socio-demographics during the COVID-19 outbreak in the US Lu Ling, Xinwu Qian, Shuocheng Guo, Satish Ukkusuri BMC Public Health (2022) Activity and mobility prediction and interpretation > paper
	Influencing factors for Right Turn Lane Crash Frequency Based on Geographically and Temporally Weighted Regression Models Lu Ling, Wenbo Zhang, Jie Bao, Satish V. Ukkusuri Journal of Safety Research (2023) Geographically and Temporally modeling, Prediction and interpretation, Safety, Human Driver Behavior. > paper
	Modeling the causality of received information, certainty, and decision making in hurricane evacuations Lu Ling, Satish V. Ukkusuri, Pamela Murray-Tuite, Seungyoon Lee, Yue ‘Gurt’ Ge Under review Causality inference, prediction and interpretation > paper
	Evaluating Public Transportation Service in a Transit Hub based on Passengers Energy Cost Xiongfei Lai, Jing Teng, Lu Ling 23rd International Conference on Intelligent Transportation Systems (2020) Public transportation, Energy Cost > paper
	Role of uncertainty and social networks on shadow evacuation and non-compliance behavior in hurricanes Lu Ling, Pamela Murray-Tuite, Seungyoon Lee, Yue ‘Gurt’ Ge, Satish V. Ukkusuri Transportation Research Record (2020) Social network, Information perception, Human behavior, and interpretation > paper
	Impact of Transportation Network Companies on Labor Supply and Wages for Taxi Drivers Lu Ling, Xinwu Qian, Satish V. Ukkusuri Under review Ridesharing, taxi industry, driver work behavior, wage expectation [> paper ](under review)
	Resilient Schedule Coordination for a Bus Transit Corridor Xiongfei Lai, Jing Teng, Paul Schonfeld, Lu Ling Journal of Advanced Transportation (2020) Public transportation, Resilience > paper
	Forecasting the gap between demand and supply of e-hailing vehicle in large scale of network based on two-stage model Lu Ling, Xiongfei Lai, Feng Li IEEE Intelligent Transportation Systems Conference (2019) Ridesharing, Matching, Neural Network, Prediction > paper
	Reliable feeder bus schedule optimization in a multi-mode transit system Lu Ling, Feng Li International Conference on Intelligent Transportation Systems (2017) Bus Schedule Optimization, prediction and interpretation > paper
	Analyzing the relationship between urban macroeconomic development and transport infrastructure system based on neural network Lu Ling, Feng Li, Linhui Cao Green Intelligent Transportation Systems, Part of the Lecture Notes in Electrical Engineering book series (LNEE,volume 419) (2017) Transportation, Economy, Neural Network, Prediction > paper
	Optimization of Regional Railway Fast Freight Transport Routes: Case Study of China’s Yangtze River Delta Area Lu Ling, Feng Li Transportation Research Board (2016) Operation research > paper

Projects

	Performance of Right-Turn Lane Designs at Intersections Project 2020-12-04 paper /