Machine Learning United States

Lucy Nwosu

***** **** **** ****, ********, Texas, United States

832-***-****, ************@*****.***

Professional Summary

Dedicated and research-driven professional with over 15 years industry experience in computer engineering, specializing in artificial intelligence, machine learning, and data science. Proven track record of published research, innovative project leadership, and exceptional teaching abilities. Seeking an opportunity to contribute to and advance research in cutting-edge technology.

Skills

• Research: Experimental design, grant writing, academic publishing

• Research Interest: Deep Learning, Natural Language Processing, Computer Vision

• Machine & Deep Learning Algorithms/Frameworks: OpenCV, Tenserflow, Keras, SKLearn, PyTorch etc

• Object detection algorithms: Yolo, RNN, RCNN, Faster-RCNN

• Programming Languages: Python, R, Java, C++, Matlab

• Web Technologies: HTML, CSS

• Statistical Analysis: Excel, Python (Pandas, Numpy, sklearn, etc.)

• Statistics: Data distribution, Probability, Metrics (Spearman, Pearson, Chi-Square)

• Database Management: AWS, Kafka, NIFI, Microsoft Azure

• Data Analysis and Visualization: Tableau, R-Studio, Qlik Sense, PowerBI

• Operating Systems: Windows, Linux/Unix, ROS

• Programming Languages: Python, R, Matlab, C++

Education

i. Doctorate in Electrical Engineering (PhD)

Specialization: Computer Engineering - Machine Learning & Artificial Intelligence Prairie View A&M University, Prairie View, Texas, United States ii. Graduate Certificate in Deep Learning for Artificial Intelligence Prairie View A&M University, Prairie View, Texas, United States iii. Graduate Certificate in Generative AI in Business University of Cincinnati, Cincinnati, Ohio, United States iv. Master in computer engineering (M.Sc.)

Specialization: Computer Vision & Machine Learning University of Houston, Clear Lake, Texas, United States v. Post Graduate Diploma in Financial Management (PGD) Michael Okpara University of Agriculture, Umudike, Abia State, Nigeria vi. Bachelor’s in engineering (B Eng.) - Electronic Engineering University of Nigeria, Nsukka, Nigeria

Experience

Advanced Artificial Intelligence Engineer

Kroger Co. – AI Research & Development 2022-2024

• Conducted extensive research and development on language models for automated text summarization, significantly reducing the time required to generate concise summaries from large documents

• Designed and implemented an associate virtual assistant using a natural language processing

(NLP) system, increasing information retrieval time by 90%.

• Developed an image classification model using convolutional neural networks (CNNs) for real- time object detection, object recognition, and image quality assessment, achieving an accuracy rate of 92% on the validation dataset.

• Created and optimized a chatbot using NLP techniques for a customer service application that find items in the store, resulting in a 30% reduction shopping time and improved customer satisfaction scores.

• Integrated machine learning techniques in an OCR (Optical Character Recognition) project to extract and process text from product images, improving text recognition accuracy by 25%.

• Lead the design, development, and deployment of large language models on Microsoft Azure, ensuring high performance, scalability, and security within a cloud environment. Senior Data Scientist – AI Research & Development 2021 – 2022 Aspentech, Houston, Texas

• Research and build new algorithms, conducting experiments, and building mathematical models to uncover data patterns.

• Develop innovative algorithms to integrate AI features to machine reliability models.

• Build rapid prototypes and proof of concepts to turn ideas into features, infrastructure, and products

• Extensively work with time series data to understand underlaying trends, seasons and patterns. Research Assistant 2019 – 2023

The Center for Computational Systems Biology, Department of Electrical & Computer Engr, Prairie View A&M University

• Work in a research team that applies data-driven computational methods to build predictive and network models of complex biological processes and diseases using cell images and genomic data stored in FASTA and FASTQ formats.

• Created image processing and computer vision algorithms to analyze image data.

• Collect, analyze, clean, and build training/testing cell images for various visual analysis tasks.

• Train ML/DL models locally or using cloud-based solution - AWS to perform visual recognition tasks, classification, segmentation, and detection.

• Evaluate models, visualize experiments, and report results for easier decision making.

• Conduct error analysis and present the findings clearly.

• I have developed computer vision and machine learning methods that have gained successful insights into the large-scale interactions between genes and proteins, and cell classification thereby contributing to above 80% of the research success. Department of Homeland Security, USA (Snr. Data Science/Engineer) 2018- 2020

• Collect, build, cleanse, assemble and refine datasets to support the variety of data analytics needs put forward by business stakeholders including data scientists, law enforcement officials, and agency analysts.

• Build data ingestion and pipeline processes for innovative analytics platforms using best practices and open-source tools such as, NiFi.

• Develop analytical solutions that are scalable, repeatable, effective, and meet the expectations of the decision-makers and stakeholders.

• Currently working on building of reliable Object Detection and Optical Character Recognition Models to meet current business needs. (Contributing 80% to task)

• Team lead – Optical Character Recognition Team

Larson & Toubro Infotech - Data Scientist (Technical Consultant) 2018 Worked on a project to build global server-side extensions, object extensions and mush –up for organizations data visualizations at Travelers Insurance.

• Create server side extensions that gives extra functionality to qlik,- ability to make predictions based on a machine learning model trained in python.

• Carries out analysis, design, and build effort for Qlik Sense data discovery and visualizations to manipulate complex data sets in a simple and intuitive format.

Code review, standard check of code written with Qlik, HTML, CSS, Jquery, Javasrcipt, Python, Machine Learning Models.

Improved organization’s data analysis and visualization of key performance measures by creating machine learning python-based plugins.

Participated in AGILE SCRUM meetings

Data Analyst & Visualization March 2010 –January 2015 Firstbank of Nigeria Ltd

• Joined the bank’s first data science team, developed intricate algorithms based on deep-dive statistical analysis and predictive data modeling that were used to deepen relationships, strengthen longevity, and personalize interactions with customers.

• Analyzed and processed complex data sets using advanced querying, visualization and analytics tools.

• Furnish executive leadership team with insights, analytics, reports and recommendations enabling effective strategic planning across all business units, distribution channels and product lines.

• Received a commendation letter for doubling campaign response rates with predictive models in R and Using random forest algorithm to help identify loyal customers and predict the likelihood of customers buying a recommended product. Other Experiences

Lecturer – Engineering Data Science

University of Houston, Texas USA 2023/2024

• Deliver lectures to over 200 graduate level students, prepared lecture notes, exams, and content evaluation.

• Mentor students in effective next steps for education and career preparedness.

• Hold office hours to work with struggling students.

• Courses taught include machine learning for data scientists, digital image processing, information visualization, Statistics for engineers, database management systems Etc.

• Ensured quality delivery of subject, and ensured improved understanding of course content by 100%

Texas Southern University, Houston, Texas USA –Adjunct Professor 2018/2019, 2020/2021

• Worked is the faculty of engineering, prepared lectures, exams, and content evaluation.

• Courses taught include programming for engineering applications, big data, circuit analysis, digital systems, microcomputer operating systems Etc.

• Ensured quality delivery of subject, and ensured improved understanding of course content by 100%

Research Assistant 2016 –2017

Telecommunication Lab, UHCL, Houston, Texas

• Researched and developed computer vision and machine learning algorithms related on object recognition, gradient domain editing, image enhancement, edge detection/classification, and face detection/recognition.

• Acquiring data from primary or secondary data sources to aid in maintaining databases deliverables, create reports and write small programs to test and analyze the database to ensure quality and functionality. Developed a deep learning application which can predict human inner emotions for application in security surveillance systems.

• Research & develop Machine Learning models and deep learning algorithms in the areas of Computer Vision and Data Management that received two IEEE awards Software skills/tools used: Python, Jupyter Notebook, Ms Power Point, Matlab, C++, Machine Learning algorithms

Infosys Limited (Data Scientist Consultant) 2019

The purpose of the project is to create fraud models for a wealth domain.

• Create models that will find fraud (identify triggers, patterns, abnormalities’, outliers, and reduction of false positives)

• Build the infrastructure for optimal extraction, transformation, and loading of data from a variety of data sources using SQL and AWS’ big data technologies.

• Create data tools for analytics and data scientist team members. Alcon – Research & Development 2021

• Implemented large scale image quality assessment using deep learning algorithms.

• Comparison of different deep learning image quality assessment methods

• Implemented traditional methods of image quality assessment – PSNR, MSE Etc.

• Creating different image distortion types – Gaussian blur, Gaussian Noise, JPG Compression Etc.

• Research and documentation of findings for future reference.

• Contributed to 80% of effort towards initial image quality assessment research in team. Apple Inc – Research & Development 2022

• Use modeling, machine learning and programming skills for people’s analytics (generate insights by leveraging large amounts of customers data)

• Demonstrate how analytical results are connected the business problem or objective

• Statistical analyses using Python libraries.

• Conducted cluster analysis to generate segmented profiles of customers

• Implemented and managed Oracle database for backend data access using SQL queries

• Participated in AGILE SCRUM meetings.

Selected Publications

1. Nwosu, Lucy, et al. "Deep convolutional neural network for facial expression recognition using facial parts." 2017 IEEE 15th Intl Conf on Dependable, Autonomic and Secure Computing, 15th Intl Conf on Pervasive Intelligence and Computing, 3rd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress

(DASC/PiCom/DataCom/CyberSciTech). IEEE, 2017.

2. Wang, Hui, et al. "Two-channel convolutional neural network for facial expression recognition using facial parts." International Journal of Big Data Intelligence 6.3-4

(2019): 259-268.

3. Nwosu, Lucy, et al. "Semi-supervised learning for COVID-19 image classification via ResNet." arXiv preprint arXiv:2103.06140 (2021).

4. Nwosu, Lucy, and Cajetan M. Akujuobi. "Engineering Solutions in the Era of COVID-19 Choosing a CNN Architecture for a Computer-Based Covid-19 Diagnosis." J Electron and Telecommun Eng 1 (2021): 1-11.

5. Nwosu, Lucy, et al. "Calibrated bagging deep learning for image semantic segmentation: A case study on COVID-19 chest X-ray image." PloS One 17.11 (2022): e0276250 Presentations &Awards:

• Title: Deep Convolutional Neural Network for Facial Expression Recognition using Facial Parts (IEEE DataCom Nov 2017) Award: Best Poster Award

• Title: A Two-Channel CNN Architecture for Real-time Facial Expression Recognition System. (IEEE IA Conf. Sept.2017) Award: Second Best Poster Award Professional Affiliations

• Institute of Electrical and Electronics Engineers (IEEE)

• Society of Women Engineers (SWE)

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