Gbadebo Ayoade

• Designed and implemented statistical data generation module to synthesize case/issue generation pattern using Python and SQL
• Performed Query Tuning and Parameter tuning to increase ETL Pipeline throughput in Dataflow and Dataproc.
• Designed and implemented tool to rank bug priorities to help with faster resolution.
• Implemented Hadoop/Spark stress testing module for GCP Dataproc Clusters using Pyspark
• Implemented tools and automation to improve usability of Google Cloud products.
• Write troubleshooting guides used by the frontline team to drive speedy resolution of common classes of cloud infrastructure problems.
• Deliver onboarding training for new members of this worldwide team.
• Handle technical issue escalations and operational responsibilities day to day.
• Work with key accounts to improve technical client experience and address negative patterns or concerns with product team.
• Act as a Data Analyst. Write queries and generate dashboards for visualization. Generate business intelligence around client technical bottlenecks for GCP in general in order to better manage the team.
• Identify training or process gaps. Highlight problem areas for each product and bring those to the product team.

• Developed and applied machine learning based approach to successfully detect and mitigate real attack threats on the enterprise network
• Feature extraction and dimensionality reduction using PCA
• Kmeans clustering for network node behavioral modelling and malicious activity detection
• Explored and Implemented Deep learning based approach for feature extraction such as LSTM autoencoder for packet sequence data analysis using Keras TensorFlow 2.0 framework
• Explored and implemented complex deep learning graph topologies using keras TensorFlow functional API
• Leveraged AWS, pyspark for large scale network log processing (1TB/day)

• Large scale data processing with Apache Spark, Hadoop. Machine learning and natural processing language applications.
• Transfer learning using pre-trained deep learning models with Keras.
• Keras deep learning model topology modification for custom classification.
• Network data collection both for system calls and network packet data
• Responsible for data identification, collection, exploration, cleaning for modeling.
• Gathered data from multiple web, external data sources and APIs, writing SQL to join and aggregate various data for analysis.
• Hands on experience in implementing Machine Learning algorithms like
  K-Nearest Neighbors, Naïve Bayes, Support Vector Machines, Decision Trees, Random Forests.
• Hands on experience in performing Dimensionality Reduction with Technique like Principal Component Analysis
• Text analytics on threat report data using Natural Language Processing Tool Kit (NLTK) and natural language processing techniques using Word vectors.
• Created various types of data visualizations using Matplotlib.

• Tuned Cassandra  and Kafka cluster to handle 250,000 writes/sec
• Optimized Kafka topic partition to increase throughput
• Tuned Cassandra CQL to optimize performance
• Setup of production grade docker, mesos, marathon application framework for Internet of things
  (IOT) pipeline for large scale message handling (250,000 messages per sec) Identified bottlenecks
  and performed system tuning that improved IOT application message throughput.
  
• Developed an IOT pipeline for more than 60 million virtual IOT devices using microservices architecture.
  
• Automated deployment scripting using bash, expect and python.

• Implemented Mobile Based App with customer identification and In-store service recommendation system.
• IPhone/IPad Development FedEx Office Print mobile Application.
• Restful webservices.
  Objective C, Passbook implementation.
  

KIMONO:
Point of Sale Management System

• Developed SQL stored procedures for managing sales data
• Implemented SQL queries for managing POS transactions on resource constrained devices using sqlite
• Data exchange specification using RESTFUL web services and XML  

Advisor: Dr. Latifur Khan