Lily Zhang

I am a Technical Lead and Research Scientist, based in Bay Area, California.

I currently work at Latitude AI on 3D generation and vision language models (VLM). From 2019 to 2024, I was at Ford Greenfield Labs, focusing on training offboard models as data engine. Before that, I was a Machine Learning Engineer at BMW working on perception.

My past research has involved 3D generation, data diversification, data balancing, embedding analysis, synthetic data augmentation and data retrieval using VLM. As a side open-source project, I built Deep-Seek, an LLM-powered retrieval engine that became GitHub's #1 rated data retrieval repository (This is before another DeepSeek went viral).

You can reach me at lilyzhng.ai AT gmail.com. I publish as Xianling Zhang but go by Lily Zhang professionally.

News

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Publications

• Lihi-GS: Lidar-supervised gaussian splatting for highway driving scene reconstruction [Project Page]
  PC Kung, X Zhang, KA Skinner, N Jaipuria.
  Under Review (2025)
• Unveiling the Ambiguity in Neural Inverse Rendering: A Parameter Compensation Analysis
  G Kouros, M Wu, S Nagesh, X Zhang, T Tuytelaars.
  Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024)
• LANe: Lighting-Aware Neural Fields for Compositional Scene Synthesis [Project Page]
  A Krishnan, A Raj, X Zhang, A Carlson, N Tseng, S Sridhar, N Jaipuria, James Hays,.
  Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision Workshop (2024)
• DatasetEquity: Are All Samples Created Equal? In The Quest For Equity Within Datasets [Code]
  S Shrivastava, X Zhang, S Nagesh, A Parchami.
  Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) (2023)
• SIMBAR: Single Image-Based Scene Relighting for Effective Data Augmentation for Automated Driving Vision Tasks [Project Page]
  X Zhang, N Tseng, A Syed, R Bhasin, N Jaipuria.
  Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2022)
• deepPIC: Deep perceptual image clustering for identifying bias in vision datasets [Project Page]
  N Jaipuria, K Stevo, X Zhang, ML Gaopande, I Calle, J Jain, VN Murali.
  Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2022)
• Deflating dataset bias using synthetic data augmentation
  N Jaipuria, X Zhang, R Bhasin, M Arafa, P Chakravarty, S Shrivastava, S Manglani, VN Murali.
  Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020)
• Operating a device such as a vehicle with machine learning
  A Raj, A Krishnan, J Hays, X Zhang, A Carlson, N Jaipuria, S Sridhar, N Tseng.
  Granted US/CN/DE Patent (2023)
• Debiasing Datasets for Machine Learning
  N Jaipuria, X Zhang, K Stevo, J Jain, VN Murali, M Gaopande.
  Granted US/CN/DE Patent (2022)
• Systems And Methods For Improved Training Data Acquisition
  VN Murali, N Jaipuria, X Zhang.
  Granted US/CN/DE Patent (2021)
• Single-perspective image relighting
  X Zhang, N Tseng, N Jaipuria, R Bhasin.
  Granted US/CN/DE Patent (2021)
• Image relighting
  X Zhang, N Tseng, N Jaipuria, R Bhasin.
  Granted US/CN/DE Patent (2021)
• Neural network image processing
  X Zhang, A Litvak, N Jaipuria, S Paudel.
  (2020)
• Enhanced vehicle operation
  M Arafa, VN murali, X Zhang, N Jaipuria, R Bhasin.
  Granted US/CN/DE Patent (2020)

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Service

• Program Committee Member
  TPC for NeurIPS ('21, '24, '25), CVPR ('22, '23, '24, '25), ICRA ('23), IROS ('23), ICML ('23), ICLR ('24), ECCV ('24), KDD ('24), ICCV ('25)
• Industry Advisory Board [MXET Board Meeting]
  Invited to serve on the Industry Advisory Board at Texas A&M University
• Journal Editor [Call for Papers]
  Invited guest editor for ACM Journal, Transactions on Internet of Things, Special Issue on Autonomous Driving
• Conference Chair [Keynote & Panel], [Slides]
  Chairing for The IEEE International Conference on Mobility (MOST) Panel Discussion "Driving Force: Towards Large-Scale Autonomous Driving Commercialization"
• Workshop Moderator [Slides]
  Moderated the "Generative AI: A New World Simulator to Transform Synthetic Data Generation" workshop at the Auto.AI conference
• Hackathon Judge
  Invited judge for Gen AI Hackathon in San Francisco