Houhan Lu Email & Phone Number

New York, NY, US

New York, United States

- Led the development of a full-stack web application for a label company, including backend development with Flask and Amazon DynamoDB, and frontend development with JavaScript, jQuery, and Bootstrap.- Managed production and development servers on AWS EC2, setting up PDF and document storage on AWS S3.- Developed real-time chat, voice call, and.

New York, United States

- Developed deep learning models using CNNs, RNNs, Transformer encoders, and large-scale pre-training.- Built Masked-Auto Encoder models for X-ray and health records representation using the MIMIC dataset.- Created a CLIP-like vector embedding model, integrating text and image representations, optimizing model performance to achieve a 95% precision score..

Beijing, China

- Collaborated with cross-functional teams remotely, using Git for version control.- Developed a novel Seq-Seq model combining Marginal Structural Models and Representation Learning for time series analysis, achieving a 0.6% RMSE and a 48.1% performance improvement.- Proposed a masked diffusion method to address gradient leakage, reducing SSIM losses by.

Chengdu, Sichuan, China

- Developed ETL data pipelines using a cloud-native tech stack, leveraging Python, SQL, Docker, and AWS services (S3, Lambda).- Automated data processing workflows, creating scalable software for pipeline triggering, monitoring, and validation using AWS Batch, CloudWatch, and Splunk.- Developed CV models to detect and classify medical components in power.

Kunming, Yunnan, China

- Created and analyzed Hive tables; implemented partitioning, dynamic partitions, and buckets in Hive.- Enhanced data processing pipeline and CTR algorithms (LR, GBDT+LR, DNN) using LightGBM and XGBoost for massive datasets on a big data platform.- Automated data processes using tools like Tableau, D3.js, Shiny, and Spark.- Developed ML and computer vision.

Chengdu, Sichuan, China

- Designed and implemented a multi-modal deep learning network using Camera and Lidar data for ground height and lane estimation.- Developed a 3D PointNet model for temporal smoothing of segmentation predictions over point cloud sequences.- Built a Sparse Point-Voxel CNN for semantic segmentation of point cloud sequences, increasing data annotation speed.

Chengdu, Sichuan, China

- Developed OCR solutions for document digitization using machine learning and deep learning, training models on the EMNIST dataset for handwritten text/number recognition.- Conducted marketing analytics projects using R and SAS, including pre-launch planning, target prioritization, control group identification, and post-launch ROI analysis.- Worked on.

Master Of Science - Ms, Computer Science

Education record