CHRISTIAN EMIYAH

Charlotte, NC, USA
christian.emiyah@gmail.com

EDUCATION

Morgan State University (MSU) Baltimore, MD

  • Doctorate in Electrical Engineering (Machine Learning & Data Science
    • Thesis: Framework for Extracting Relevant Transportation Metrics from Drone Surveillance Videos using Computer Vision & Machine Learning
    • Winner: Annual Innovation of the Year Award in Life Sciences, MSU
  • Master’s in Mathematics
    • Thesis: Optical Character Recognition Using Principal Component Analysis (PCA)
    • Winner: Best Technical Presenter Award, Annual Research Symposium
  • Bachelor of Science in Electrical and Computer Engineering
    • Capstone: Mesh Networking Protocol for Visible Light Communication
    • Nominee: Black Engineer of the Year Awards (BEYA)

SKILLS

  • Programming Languages: Python, C, C++, Matlab, SQL, R, HTML, CSS
  • Data Analysis and Visualization: PowerBI, Tableau, Jenkins
  • AWS Cloud Technologies: IAM, S3, EC2, RDS, DynamoDB, VPC, Redshift, CloudShell, Cloud9, CodeCommit, CodeBuild, CodeDeploy, CodePipeline, EBS, Networking, etc.
  • Soft Skills: Leadership, Team Work, Conflict Resolution, Public Speaking, Agile, etc.
  • Data Science: Data Modelling, Data Mining, Data Warehousing, Data Analytics, Data Visualization, Data Engineering, Feature Engineering, Machine Learning, etc.

WORK AND RESEARCH EXPERIENCE

Quantitative Analytics Specialist - Wells Fargo Jul 2021 - Current

  • Developing and improving analytical models used by the trading desk using C++, Python, Git and Jenkins for CI/CD
  • Conducting unit tests, regression tests, & integration tests to verify model design & development
  • Executing model testing plans not limited to sensitivity, stability, and stress analysis
  • Preparing documentation encompassing model summaries, testing plans, and monitoring results.
  • Performing data extraction, transformation, aggregation, and analysis from various data sources to generate single-value outputs such as NPV and multi-value tables such as projected cash flows.
  • Mentoring junior quants and serving as instructor for the Data Science & AI camp.

Data Science Team Lead - Crewasis Oct 2020 - Jan 2021

  • Managed and developed a high-performing team of data scientists and analysts, setting clear goals and providing training for career advancement.
  • Collaborated with key stakeholders across departments to identify business challenges, gather data, build analytical models, and deliver recommendations that drove measurable improvements in customer experiences and revenue growth.
  • Led a successful US expansion initiative focused on regional sales analysis and forecast modeling, identifying significant growth opportunities in the US flavored water market.
  • Provided valuable support and guidance during the Covid pandemic by organizing and leading free Google Analytics setup and training sessions, advising businesses on effective marketing and website content strategies to boost traffic and sales.

Data Scientist/ML Engineer at Data Engineering & Predictive Analytics Jan 2019 – Sep 2020

  • Developed machine learning-backed software applications using programming languages such as C/C++, Python, and SQL to support clustering and predictive analytics.
  • Conducted data collection, preprocessing, visualization, and ML model fitting and evaluation using Python, R, and Tableau for sentiment analysis, pattern recognition and feature engineering.
  • Ensured efficient workflow management using AWS Cloud technologies and Docker.
  • Built an automated framework that extracts traffic-related metrics from video surveillance footage utilizing trained neural network object detector and computer vision, streamlining processes and increasing efficiency.

Data Systems Analyst – Baltimore City Public Schools Human Capital Feb 2018 – Oct 2018

  • Collaborated with senior HR and business leaders to identify significant people metrics to measure staff retention across the district, and therefore, device ways to improve budget allocation.
  • Contributed to database improvements by participating in data modeling, resulting in reduced inaccuracies, and allowing for smoother extraction, transformation, and loading processes before data analysis and visualization.
  • Created and maintained PowerBI dashboards enabling stakeholders to quickly glean data analysis findings and insights.

Data Scientist – Dept of Compt. Sci, Morgan State Univ. Jul 2017 – Jan 2018

  • Developed a neural network based machine learning system for classifying skin lesion images as benign or malignant using Python’s deep learning API Keras with Theano and Tensorflow.
  • Improved model performance by 17% through data augmentation when tested on the International Skin Imaging Collaboration (ISIC) image dataset consisting of over 2000 images.
  • Streamlined data pipelines, ensured code accuracy through unit testing and regression testing

Software Engineer/Innovator, Engineering Visualization Research Lab Jul 2013 – Dec 2016

  • Co-led a team of four in the development of an innovative LED-based home automation and occupant/asset tracking system, resulting in a granted patent and two research publications
  • Designed and implemented software for encoding and decoding data into electrical signals, enabling visible light communication within the lighting system
  • Created impactful demos and presentations for conferences and stakeholder meetings to effectively communicate project progress and results.

Engineering Research Assistant, Engineering Visualization and Research Lab Jul 2012 – Jun 2013

  • Contributed to groundbreaking research on incorporating haptic feedback as an alternative communication method for those with audiovisual impairments
  • Utilized C++ programming skills to simulate and map various vibration patterns for user response/feedback using Arduino microcontroller
  • Developed a user-friendly Graphical User Interface (GUI) for Phidget I/O board in Visual Basic, improving overall efficiency and accessibility of the project.

Summer Research Intern, University of Maryland College Park May 2012 – July 2012

  • Demonstrated expertise in advanced-level math problem solving, utilizing knowledge of generative functions and game theory. Devised an innovative gravity-based system for transporting mass in a 2-D space, leveraging engineering principles and differential equations to achieve maximum efficiency. Cultivated key technical skills in areas such as Technical Documentation, Set Theory, Linear Algebra, Game Theory, Combinatorics, and Fibonacci Numbers, applying these concepts to develop cutting-edge generative algorithms and functions.

EXTRA CURRICULAR ACTIVITIES

LoveWorld Inc (2012-2021)

  • Technical Consultant
    • Led efforts to digitize the information management systems from data collection through its storage, retrieval and analysis while following best identity and access management practices
  • Senior Manager (2019-2021)
    • Provided structure and coordinated with line managers and team leads to ensure achievement of set goals not limited to community engagement, growth, & leadership development
  • Chapter Manager (2014-2015)
    • Provided leadership and guidance to stimulate growth and ensure business continuity.
    • Organized personal and career development conferences for members and invited guests.

Verizon Innovative Learning for Middle School Boys – MSU Jan 2019 – Aug 2019

  • Program Mentor
    • Mentored 14 students through an intensive learning experience including courses in Augmented and Virtual Reality, Computer Programming, 3D Design, Entrepreneurship and Design Thinking principles.

PUBLICATIONS AND PATENT

  • Patent: K. Nyarko, C. Emiyah and S. Mbugua. 2017. System and Method for Lighting and Building Occupant Tracking, U.S. Patent Application 15430904, Patent Number US 9,973,275 B2 May 15, 2018
  • Publication: K. Sayrafian, B. Cloteaux, V. Marbukh and C. Emiyah: “Evaluation of the Bluetooth-based Proximity Estimation for Automatic Exposure Determination,” 2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC), published 2022
  • Publication: Christian E., Kofi N., Celeste C, Istiak B.: “Extracting Vehicle Track Information from Unstabilized Drone Aerial Videos using YOLOv4 Common Object Detector and Computer Vision,” in Future Technologies Conference, 2021
  • Publication: K. Nyarko, C. Emiyah and S. Mbugua. “Building Occupant and Asset Localization and Tracking Using Visible Light Communication”, Proc. SPIE 9844, Automatic Target Recognition XXVI, 98440B (May 12, 2016); doi:10.1117/12.2224089; http://dx.doi.org/10.1117/12.2224089
  • Publication: K. Nyarko and C. Emiyah, “A Low-Cost Demonstration Platform for Reducing Energy Consumption by Regulating Building Controls through VLC,” Proceedings of World Scientific and Engineering Academy and Society, September 2013, Baltimore, USA

ATTENDED CONFERENCES

  1. Super Computing Conference SC12, Salt Lake City, Utah, USA
  2. Richard Tapia Celebration of Diversity in Computing Tapia
  3. Command, Control and Interoperability Center for Advanced Data Analysis CCICADA Conference, Howard University, Washington DC
  4. IEEE Student Activity Conference IEEESAC, Ohio State University
  5. Modeling and Optimization: Theory and Applications (MOPTA) Conference, Lehigh University, Pennsylvania link
  6. Applied Mathematics: The Next 50 Years Workshop and Conference, University of Washington link