I am a Software Engineer with professional experience from organizations including the Massachusetts Institute of Technology (MIT) Lincoln Laboratory and Moody's Analytics. My academic background focuses on Computer Science with strong insights into machine learning and algorithms including an academic background from Georgia Institute of Technology and University of Central Florida. I use my abilities to support open source, contribute to non profits, expand science, and foster entrepreneurship.

2. Contents

  1. Introduction
  2. Contents
  3. Projects
  4. Programming Languages
  5. Credentials
  6. Publications
  7. Personal Insights
  8. Professional References

3. Projects

Deep Learning - Convolutional Neural Network Image Classifier

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Language: Python
Dependencies: NumPy, Pandas, sklearn, keras, glob, matplotlib, cv2, tqdm, TensorFlow
Algorithms & Methods: Convolutional Neural Networks, Computer Vision, Transfer Learning,
	Model Architecture, Deep Learning Data Pipeline
		

Unsupervised Learning - Creating Customer Segments

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Language: Python
Dependencies: NumPy, Pandas, matplotlib, scikit-learn
Algorithms & Methods: Logarithmic Feature Scaling, Tukey's Method for Outlier Detection, 
	Principal Component Analysis, K-Means Clustering, Gaussian Mixture Clustering, 
	Cluster and Biplot Visualization
		

Supervised Learning - Targeting Customer Segments

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Language: Python
Dependencies: NumPy, Pandas, matplotlib, scikit-learn
Algorithms & Methods: Normailizing Numerical Features, Precision and Recall (Sensitivity), 
	Gaussian Naive Bayes, Decision Tree Classifier, Ensemble Methods (Bagging, AdaBoost, 
	Random Forest, Gradient Boosting), KNeighbors, Support Vector Machines, 
	Training and Predicting Pipeline, Grid Search Model Tuning, Extracing Feature Importance
		

Reinforcement Learning - Training a Smartcab to Drive

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Language: Python
Dependencies: NumPy, Pandas, matplotlib, scikit-learn
Algorithms & Methods: Q-Learning, Simulating Enviornment, Optimal Policies, Learning Rates,
	State Space
		

Regression Analysis - Evaluating & Validating Real Estate Data

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Language: Python
Dependencies: NumPy, Pandas, matplotlib, scikit-learn
Algorithms & Methods: Feature Predictions, Decision Tree Classifier, 
	Grid Search Model Tuning, K-Fold Cross Validation Training
		

Regression Analysis - Exploring Titanic Survival Historical Data

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Language: Python
Dependencies: NumPy, Pandas, matplotlib, scikit-learn
Algorithms: Feature Predictions, Decision Tree Classifier
		

4. Programming Languages

Python 2 & 3

8 Years of Experience

TensorFlow scikit-learn Keras Anaconda NLTK matplotlib flask SciPy IPython
Java

5 Years of Experience

Scala Eclipse Maven Java.* OpenJDK
C / C++

5 Years of Experience

Arduino CodeBlocks Visual Studio
SQL

3 Years of Experience

T-SQL mySQL PostgreSQL
JavaScript

12 Years of Experience

Node.js Angular.js Express.js Chart.js D3.js

5. Credentials

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Udacity Nanodegree Machine Learning Engineer

Machine learning represents a key evolution in the fields of computer science, data analysis, software engineering, and artificial intelligence.This program teaches how to become a machine learning engineer, and apply predictive models to massive data sets in fields like finance, healthcare, education, and more.

  • Expected Graduation: Summer, 2018
  • Nanodegree
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HBX | Harvard Business School CORe: Credential of Readiness

HBX CORe (Credential of Readiness) is a 150-hour certificate program on the fundamentals of business from Harvard Business School. CORe is comprised of three courses—Business Analytics, Economics for Managers, and Financial Accounting—developed by leading Harvard Business School faculty and delivered in an active learning environment based on the HBS signature case-based learning model.

  • July, 2017
  • Pass
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Big Data - Programming

The badge holder demonstrates the ability to use programming concepts provided by the various technologies in the Hadoop ecosystem including, but not limited to MapReduce and Pig.

  • May, 2016
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Big Data Foundations

This badge holder has a basic understanding of Big Data concepts and their applications to gain insight for providing better service to customers. The learner understands that Big Data should be processed in a platform that can handle the variety, velocity, and the volume of data by using components that requires integration and data governance.

  • December, 2015
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Big Data Hadoop Foundations

This badge holder has a basic understanding of Hadoop. The badge holder can describe what Big Data is and the need for Hadoop to be able to process that data in a timely manner. The individual can describe the Hadoop architecture and how to work with the Hadoop Distributed File System (HDFS) both from the command line and using the BigInsights Console that is supplied with IBM BigInsights.

  • April, 2016

6. Publications

Analyzing the Existing Undergraduate Engineering Leadership Skills
Dr. Hamed M. Almalki, Dr. Luis Rabelo, Charles Davis, Hammad Usmani, Dr. Debra Hollister, Dr. Alfonso Sarmiento

  • Surveyed and sampled 507 responses and conducted regression analysis, hypothesis testing, and other metrics
  • Accomplished the best 20%-25% paper at the World Multiconference on Systemics, Cybernetics, and Informatics
  • Download .pdf

    7. Personal Insights

    Personality Overview

    source: 16personalities.com

    Twitter is a valuable and rich resource for data with a tremendous opportunity to gain insights from analysis. Twitter provides an API for developers and researchers that I was able to utilize with natural language processing to create conversational agents. By implementing a Recurrent Neural Network (RNN) with LSTM cells, I developed a data pipeline to perform extraction, transforming, and loading (ETL) into an interactive database of compiled models done entirely with a cloud architecture. These conversational agents, or chatbots, were able to accept any input and produce an output while having the ability to learn from the input and be recompiled. One of the most fascinating observations about these models is the ability to produce realistic conversations that mimics the personality of the Twitter user. The output was able to produce unique responses to the same questions and was able to convey conversational patterns that were emotionally expressive including emoji's and related hashtags. These trends show promising results for applied machine learning algorithms on conversational agents.
    One of the first steps in the software development cycle is requirement gathering where it is crucial that all team members understand what is required. When I led a project to build a multilingual dataset for natural language processing, we reached out to remote translators able to perform manual or automated data mining functions. The requirements outlined the data set size among other details that were conveyed to the translators. One of the translators was not able to meet the data set size requirements because of limitations in that specific language. I overcame this challenge by collaborating with the translator to add more resources by involving more professionals and mentoring of data mining techniques. The additional personnel was sufficient to complete the translators tasks. Because of the additional resources, we were able to complete the data set and met the requirements.
    I thrive in a fast-paced work environment where there are specific, measurable, attainable, reasonable, and timely goals. I enjoy collaborating with other professionals and become involved with social events quickly. I have curious nature with a strong desire to experiment and I desire any work environment that can foster these qualities.
    I led a medical expedition to a remote village in Haiti for a non profit organization. In this village, there is no running water or electricity; much less than the available internet and air conditioning that I experience from day-to-day. It changed my perspective of the priorities in life as a citizen of a first world country. I developed a more profound appreciation of basic technological research and development that many people often take for granted.
    I believe there is an enormous amount of potential for big data algorithms in the context of medical analysis. I would want to implement various algorithms that can give us insights into our physical health based on fitness trackers, medical diagnostics, and genetic profiles. These algorithms can benefit society and increase the well-being of all humans.
    Data science and machine learning can allow us to provide more personalized design of software. With a relevant data set, we can predict what interfaces, tools, and functionalities users require. This can extend to software architectures that can take advantage of data science by automating some of the testing, integration, and maintenance.

    8. Professional References

    Hammad is a hard working programmer with managerial and leadership skills. Besides his superior technical skills, his communication skills are outstanding too. I recommend him in all technical and managerial positions.

    Dr. Hamed Almalki, Change Management Consultant at Saei
    • halmalki@knights.ucf.edu

    Hammad has exceptional capability at conceptualization of a project which was based on the innovative technologies and sophisticated engineering that was required to accomplish it. He has got a sharp eye for detailings, expertise in managing the overall concept to realization of the same! I personally recommend him to anyone seeking a good balance between expertise and a good human being! May God bless him in life and every endeavor he's associated with!

    Andy D., Project Incharge at Diligence Digital India (P) Ltd
    • akashd.cwg@gmail.com

    Hammad is detail-oriented and committed to success in whatever role he is in.

    Saad Usmani, Data Scientist at New College of Florida
    • saadu.usmani@gmail.com

    As a manager of Hammad, I am proud to say he provided a unparalleled level of service for the company. With an unwavering work ethic and proactive approach to solving problems, Hammad served as a shining example for the rest of the team to excel service level agreements.

    Mohammed Rahman, Systems Analyst at K3 solutions llc
    • abdur.rahman@k3solutions.net

    Hammad is a tenacious computer scientist that exemplified entrepreneurship and produced excellent work.

    Sam Verma, Programmer Analyst III at Geico
    • s.verma2907@gmail.com

    I've never met anyone in my career with the same passion and drive as Hammad. He really embodies the leadership principal of "learn and be curious". When I worked with him at MIT Lincoln Laboratory, he consistency delivered new and innovative tools to our team. From those tools we were able to engage with our customers at a more profound level that ultimately led to wider adoption and follow-on efforts.

    Chris Mattioli, Data Scientist @ AWS

    Hammad has demonstrated exceptional leadership and teamwork skills during the time I worked with him at a non profit organization. He has showcased an ability to confidently lead a team in an unfamiliar situation.

    Anay Patel, Master of Public Health at Columbia University
    • aap2218@cumc.columbia.edu