Artificial Intelligence Computer Vision

PROFILE

•Innovative a Generative AI Engineer with 7 years of

experience in application design, development.

•Possess an unbridled passion for artificial intelligence with comprehensive knowledge of Computer Vision,

Natural Language Processing, LLM, Stable diffusion and other related technologies.

•Superior abilities to identify understand and translate program requirements into sustainable, advanced

technical solutions through C++, Python, C#, Java, JavaScript and other programs.

PROFESSIONAL EXPERIENCE

Artificial Intelligence Engineer, Mindlance

January 2023 – September 2023

Irving, Texas, United States

•Developed a stable diffusion model to create realistic images of products for online advertising. This model resulted in a 20% increase in click-through rates.

•Customized a language model to generate

personalized recommendations to users. This led to a 10% increase in engagement and a 5% increase in

conversion rates.

•Fine-tuned a computer vision algorithm that works in tandem with drones & cameras to detect diseases in crops.

•Created custom models to generate unique, theme-

based videos as NFTʼs with deep learning.

•Leveraged existing models for transfer learning and generated theme-based images as NFTʼs with deep

learning.

•Utilized Generative Adversarial Networks, VQGAN,

and other deep learning models.

•Provided AI generated clips to an official music video.

•The collection of NFTʼs are highly acclaimed and are traded at 500+% ROI.

Data Architect, NCQA

June 2022 – December 2022

Washington, District of Columbia, United States

•Gathered user requirements and analyzed and

designed software solution and database.

•Responsible for data extraction and data ingestion from different data sources into Hadoop Data Lake by creating ETL pipelines using Pig, and Hive.

•Worked extensively with Hive DDLs and Hive Query

language (HQLs).

•Helped in the design of the Architecture of the Data Warehouse and helped in performance tuning of the

data base.

SKILLS

Technical Skills

C, C++, C#, Java, Python, JavaScript, R, Scala, Node.js, React, MySQL, MongDB, Linux, Git, Docker, Kubernetes, Keras, Tensorflow, PyTorch, Pillow, OpenCV, OpenCL, Open3D, OpenMesh, Point Cloud Library, OpenVINO,

GAN, YOLO, SSD, RCNN, VGG16, GPT, MobileNet, OCR,

ViT, AWS

Theoretical Skills

Software Engineering, Statistical Analysis, Website Design, Cloud Computing, Data Science, Data Structures and Algorithm, ChatBot, CI/CD, Data Collection,

Software Engineering, Statistical Analysis, Website Design, Cloud Computing, Data Science, Data Structures and Algorithm, CI/CD, Data Collection, Data

Visualization, Machine Learning, Deep Learning,

Computer Vision, Natural Language Processing, Audio Processing, Time Series Forecasting, MLOps, DVC,

CVOps, Object Detection, Object Tracking, Object

Segmentation, 3D Reconstruction, Image Processing, Image Augmentation, 3D Object Detection, Stable

Diffusion, LLM fine-tuning

PROJECTS

Image Classification using Transfer Learning in large image dataset

March 2022 – April 2022

In this project, the client provided 10K images containing defective and non-defective images. The main objective of the project is to classify the two type of images and store the result. Project required to read massive images of the network path defined in the configuration. We have developed system which runs every hour and reads the files from the network. The challenge was to identify defective images with a high accuracy of nearly 99%. As a projectile, we need more images to form the deep learning model generated by the image enhancement

technique. In a second step, read the image using

OpenCV and apply the learning transfer to develop the model.

As a result, our image classification model obtained a satisfactory default image classification with a Type 2 error of zero.

Eugene Lucas

Senior Artificial Intelligence Engineer

**************@*****.*** +1-512-***-**** Liberty, United States live:.cid.2e9941adec3e7a43

•Designed SSIS Packages to transfer data from various sources like Text Files, SQL Server, and Excel to SQL Server using Business Intelligence Development

Studio.

•Wrote T-SQL queries, Stored Procedures and used

them to build packages.

•Created indexes on selective columns to speed up

queries and analyses in SQL Server Management

Studio.

•Stored Procedures, User Defined Functions, Views, TSQL Scripting for complex business logic.

•Worked on QA testing by writing scripts for source and target data to verify the integrity of the data.

Artificial Intelligence Engineer, Urbint

June 2020 – April 2022 New York, United States

•Responsible for designing and developing 3D sensor perception pipelines, ranging from low-level driver integration with ROS (Robot Operating System) to

advanced computer vision features such as real time object detection and segmentation.

•Researched and developed sensor extrinsic pose

calibration solutions using Ceres Solver (C++) for convex optimization and Point Cloud Library (C++) for 3d sensor data processing.

•Implemented an odometry algorithm for estimating

robot's location.

•Supported development work on ROS drivers for

hardware communication devices such as CAN bus

and serial port.

•Established the Brain Injury Detection System using Python, Docker, OpenCV, AWS Amplify, AWS Lambda,

AWS S3, AWS ECR, AWS SageMaker and AWS IoT.

Also used Support Vector Regression algorithm for

forecasting the position of pupils.

•Established Auto MLFlow for 3D character generation from an image using Python, PIFuHD, RunPod, Google Colab and developed motion planning algorithm using Logistic Regression and KNN.

Full-Stack Developer, CaseCTRL

June 2017 – April 2020 Houston, Texas, United States

•Focused on the latest trend - React, built several projects with Redux.

•Designed and implemented robust and scalable APIs using frameworks like Express.js and Django, ensuring seamless integration with the front-end systems.

•Collaborated with client teams to onboard new models and algorithms and design end to end data pipelines.

•Maintained the back-end server using Express.js for monitoring Ethereum smart contracts.

•Developed comprehensive unit tests using the testing framework in Go to ensure code quality and

functionality.

•Implemented various private APIs on a Node.js and MongoDB backend.

•Worked on a couple of Wordpress websites to

maintain the user traffic and to improve the user

experience.

Terabyte-Scale Data Ingestion Cloud Infrastructure for Autonomous Driving

June 2020 – August 2020

In this project, a custom solution was developed to address challenges in scaling terabyte-scale data

ingestion pipelines for an autonomous driving company. Vertax AI, Kubernetes clusters, and autoscaling

technologies were leveraged to increase efficiency, reliability, and scalability while reducing costs. The infrastructure was bootstrapped using Terraform and Terragrunt, and Argo Workflows were employed to run the data ingestion pipelines, with ArgoCD for self- healing capabilities and continuous deployment. By implementing auto-scaling policies, the solution

dynamically scaled based on demand, resulting in

significant cost savings and a robust, efficient, and secure cloud infrastructure. The project successfully improved data processing and storage capabilities, ensuring the company could scale their operations

effectively.

Hospital position recommendation

To find the most reasonable hospital position in 10k satellite images, in each image every element that can be influenced to hospital is detected using a trained model, which is builded using AWS Sagemaker and

AWS ECR. And then every image is evaluated to see if a new hospital can be builded or not in it.

EDUCATION

Bachelor's Degree of Computer Science,

University of California

May 2013 – May 2017 Berkeley, United States

This was the best happy period that I've ever meet. LANGUAGES

English

Chinese

•Participated in the design and implementation of CI / CD and DevOps processes for agile projects and

worked with technologies and platforms such as

Python, Golang, JavaScript, GIT, Linux, Docker,

Kubernetes, Ngnix, Jenkins, AWS, used debugging

tools like React-Dev Tools for faster debugging and reducing debugging time by 50%.

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