Yu Zhang(张瑜)

Ph.D. at ABEN NDSU - May 2023. Email: sgc908@gmail.com Accomplishments Graduate Research Assistant, ABEN, NDSU • Successfully spearheaded the development and integration of a computer vision and artificial intelligence algorithms pipeline project for a chemical robotic weed control platform • Achieved exceptional accuracy rates for weed recognition by building and optimizing convolutional neural network models using state-of-the-art architectures, including VGG16, ResNet50, Xception, DenseNet, MobileNetV3, EfficientNet, ConvNeXt, and YOLO-v4 • Streamlined the meat processing industry by developing an Android and IOS app using React Native and Python to identify and classify beef cuts • Enabled more efficient and precise detection of invasive plants by leveraging machine learning techniques and engineering Python scripts and Java code for weed identification • Simplified the image acquisition process and reduced the time and effort required for data collection by programming a bash script for automatic digital camera control • Expanded the scope and potential of agricultural research by collaborating with Microsoft employees, NDSU IT personnel, and professors to successfully deploy Microsoft Farm Beat Research Kit at NDSU • Provided valuable insights into the complex interactions between crops and the environment by conducting extensive field experiments using ground robotics and collecting data using multi-spectral, color, and hyper-spectral sensors Software Engineer, Deerwalk: • Developed core features for the company's main product, "Plan Analytics," using big data technologies such as Cascading, Hadoop, and Elasticsearch, achieving exceptional performance and scalability. • Processed large volumes of data on Amazon EMR and Amazon EC2 clusters and developed database queries on MySQL, Redshift, and Elasticsearch databases, ensuring data accuracy and reliability. • Built a builder and listener for creating Elasticsearch queries in Grail's framework using Java, streamlining the search process and improving query efficiency. • Researched AWS Application Load Balancer Implementation as a replacement for Elastic Load Balancer, resulting in significant cost savings and improved performance. • Collaborated with the Chief Technology Officer, Business Analyst, Front-end team, QA team, and Data team to successfully resolve an existing product issue, ensuring customer satisfaction and retention. • Created a Python script to parallelize job submissions on Hadoop, optimizing resource utilization on Amazon Cluster and reducing costs by 2%, demonstrating strong cost management skills.