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<!DOCTYPE html>
<html lang="en-us">
<head>
<meta charset="UTF-8">
<title>Hammad Ahmad Usmani</title>
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</head>
<body>
<section class="page-header">
<h1 class="project-name">Hammad Ahmad Usmani</h1>
<h2 class="project-tagline">Computer Scientist | Machine Learning Engineer | Georgia Tech & UCF Alum</h2>
<a href="resumes/Resume_202403271811.pdf" class="btn" target="_blank" rel="noopener noreferrer">Resume</a>
<a href="https://calendar.app.google/j5xk4ugAmAJUAZE37" class="btn" target="_blank" rel="noopener noreferrer">Book An Appointment</a>
<a href="contact.vcf" class="btn" target="_blank" rel="noopener noreferrer">Contact File</a>
<a href="https://www.linkedin.com/in/hammadus" class="btn" target="_blank" rel="noopener noreferrer">LinkedIn</a>
<a href="https://www.github.com/hammad93" class="btn" target="_blank" rel="noopener noreferrer">Github</a>
</section>
<section class="main-content">
<a name="Introduction"></a>
<p>As a computer scientist and machine learning engineer, my portfolio reflects my journey through prestigious institutions like M.I.T., Harvard Business School, Georgia Tech, and UCF. I specialize in areas of business, software, machine learning, and artificial intelligence, and have contributed to various projects and publications in these fields. My work often involves innovative applications of Python and other technologies, showcasing my commitment to solving complex challenges in AI and machine learning.</p>
<div class="github-card" data-github="hammad93" data-width="400" data-height="150" data-theme="default"></div>
<a name="Contents"></a>
<h2>2. Contents</h2>
<ol class="task-list">
<li><a href="#Introduction">Introduction</a></li>
<li><a href="#Contents">Contents</a></li>
<li><a href="#Projects">Projects</a></li>
<li><a href="#Publications">Publications</a></li>
<li><a href="#Programming">Programming Languages</a></li>
<li><a href="#Credentials">Credentials</a></li>
<li><a href="#Personal">Personalilty</a></li>
<li><a href="#References">Professional References</a></li>
<li><a href="#Attributions">Attributions</a></li>
</ol>
<a name="Projects"></a>
<h2>3. Projects</h2>
<div class="github-card" data-github="hammad93/hurricane-net" data-width="400" data-height="150" data-theme="default"></div></br>
<div class="github-card" data-github="hammad93/hurricane-deploy" data-width="400" data-height="250" data-theme="default"></div></br>
<div class="github-card" data-github="hammad93/loebner-prize-protocol" data-width="400" data-height="150" data-theme="default"></div></br>
<div class="github-card" data-github="hammad93/hurricane-map" data-width="400" data-height="250" data-theme="default"></div>
<div id="accordion" role="tablist">
<!-- Deep Learning - Convolutional Neural Network Image Classifier -->
<div class="card">
<div class="card-header" role="tab" id="headingOne">
<h5 class="mb-0">
<a data-toggle="collapse" href="#collapseOne" role="button" aria-expanded="false" aria-controls="collapseOne">
Deep Learning - Convolutional Neural Network Image Classifier
</a>
</h5>
</div>
<div id="collapseOne" class="collapse" role="tabpanel" aria-labelledby="headingOne" data-parent="#accordion">
<div class="card-body">
<p><a href="https://hammad93.github.io/deeplearning/" class="btn btn-primary" role="button">Go to Project Page</a><a href="https://hammad93.github.io/deeplearning/deeplearning.zip" class="btn btn-outline-primary" role="button">Download .zip</a></p>
<pre><code>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
</code></pre>
</div>
</div>
</div>
<!-- Unsupervised Learning - Creating Customer Segments -->
<div class="card">
<div class="card-header" role="tab" id="headingTwo">
<h5 class="mb-0">
<a data-toggle="collapse" href="#collapseTwo" role="button" aria-expanded="false" aria-controls="collapseTwo">
Unsupervised Learning - Creating Customer Segments
</a>
</h5>
</div>
<div id="collapseTwo" class="collapse" role="tabpanel" aria-labelledby="headingTwo" data-parent="#accordion">
<div class="card-body">
<p><a href="https://hammad93.github.io/unsupervised/" class="btn btn-primary" role="button">Go to Project Page</a><a href="https://hammad93.github.io/unsupervised/customer_segments.zip" class="btn btn-outline-primary" role="button">Download .zip</a></p>
<pre><code>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
</code></pre>
</div>
</div>
</div>
<!-- Supervised Learning - Targeting Customer Segments -->
<div class="card">
<div class="card-header" role="tab" id="headingThree">
<h5 class="mb-0">
<a data-toggle="collapse" href="#collapseThree" role="button" aria-expanded="false" aria-controls="collapseThree">
Supervised Learning - Targeting Customer Segments
</a>
</h5>
</div>
<div id="collapseThree" class="collapse" role="tabpanel" aria-labelledby="headingThree" data-parent="#accordion">
<div class="card-body">
<p><a href="https://hammad93.github.io/supervised/" class="btn btn-primary" role="button">Go to Project Page</a><a href="https://hammad93.github.io/supervised/finding_donors.zip" class="btn btn-outline-primary" role="button">Download .zip</a></p>
<pre><code>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
</code></pre>
</div>
</div>
</div>
<!-- Reinforcement Learning - Training a Smartcab to Drive -->
<div class="card">
<div class="card-header" role="tab" id="headingFour">
<h5 class="mb-0">
<a data-toggle="collapse" href="#collapseFour" role="button" aria-expanded="false" aria-controls="collapseFour">
Reinforcement Learning - Training a Smartcab to Drive
</a>
</h5>
</div>
<div id="collapseFour" class="collapse" role="tabpanel" aria-labelledby="headingFour" data-parent="#accordion">
<div class="card-body">
<p><a href="https://hammad93.github.io/reinforcement/" class="btn btn-primary" role="button">Go to Project Page</a><a href="https://hammad93.github.io/reinforcement/smartcab.zip" class="btn btn-outline-primary" role="button">Download .zip</a></p>
<pre><code>Language: Python
Dependencies: NumPy, Pandas, matplotlib, scikit-learn
Algorithms & Methods: Q-Learning, Simulating Enviornment, Optimal Policies, Learning Rates,
State Space
</code></pre>
</div>
</div>
</div>
<!-- Regression Analysis - Evaluating & Validating Real Estate Data -->
<div class="card">
<div class="card-header" role="tab" id="headingFive">
<h5 class="mb-0">
<a data-toggle="collapse" href="#collapseFive" role="button" aria-expanded="false" aria-controls="collapseFive">
Regression Analysis - Evaluating & Validating Real Estate Data
</a>
</h5>
</div>
<div id="collapseFive" class="collapse" role="tabpanel" aria-labelledby="headingFive" data-parent="#accordion">
<div class="card-body">
<p><a href="https://hammad93.github.io/bostonhousing/" class="btn btn-primary" role="button">Go to Project Page</a><a href="https://hammad93.github.io/bostonhousing/MLE-P1-master.zip" class="btn btn-outline-primary" role="button">Download .zip</a></p>
<pre><code>Language: Python
Dependencies: NumPy, Pandas, matplotlib, scikit-learn
Algorithms & Methods: Feature Predictions, Decision Tree Classifier,
Grid Search Model Tuning, K-Fold Cross Validation Training
</code></pre>
</div>
</div>
</div>
<!-- Regression Analysis - Exploring Titanic Survival Historical Data -->
<div class="card">
<div class="card-header" role="tab" id="headingSix">
<h5 class="mb-0">
<a data-toggle="collapse" href="#collapseSix" role="button" aria-expanded="false" aria-controls="collapseSix">
Regression Analysis - Exploring Titanic Survival Historical Data
</a>
</h5>
</div>
<div id="collapseSix" class="collapse" role="tabpanel" aria-labelledby="headingSix" data-parent="#accordion">
<div class="card-body">
<p><a href="https://hammad93.github.io/titanic/" class="btn btn-primary" role="button">Go to Project Page</a><a href="https://hammad93.github.io/titanic/MLE-P0-master.zip" class="btn btn-outline-primary" role="button">Download .zip</a></p>
<pre><code>Language: Python
Dependencies: NumPy, Pandas, matplotlib, scikit-learn
Algorithms: Feature Predictions, Decision Tree Classifier
</code></pre>
</div>
</div>
</div>
</div>
<a name="Publications"></a>
<h2>4. Publications</h2>
<div class="card-columns">
<div class="card">
<div class="card-body">
<h5 class="card-title">Analyzing the Existing Undergraduate Engineering Leadership Skills</h5>
<h6 class="card-subtitle mb-2 text-muted">Dr. Hamed M. Almalki,
Dr. Luis Rabelo,
Charles Davis,
Hammad Usmani,
Dr. Debra Hollister,
Dr. Alfonso Sarmiento</h6>
<p class="card-text">
<li>Surveyed and sampled 507 responses and conducted regression analysis, hypothesis testing, and other metrics</li>
<li>Accomplished the best 20%-25% paper at the <i>World Multiconference on Systemics, Cybernetics, and Informatics</i></li>
</p>
<a href="http://www.iiisci.org/Journal/CV$/sci/pdfs/MA302FK16.pdf" class="card-link">Download .pdf</a>
</div>
</div>
<div class="card">
<div class="card-body">
<h5 class="card-title">A Deep Recurrent Neural Network to Forecast the Intensity and Trajectory of Atlantic Tropical Storms (2019)</h5>
<h6 class="card-subtitle mb-2 text-muted">Hammad Usmani, Georgia Institute of Technology, Atlanta, GA</h6>
<p class="card-text">
This study presents a bidirectional deep recurrent neural network (BDRNN) utilizing LSTM cells to forecast Atlantic storm trajectories and intensity, outperforming statistical baselines like OCD5. Developed with HURDAT2 data, the BDRNN offers timely and precise emergency planning, highlighting the importance of advanced forecasting models in storm preparedness.
</p>
<a href="https://ams.confex.com/ams/2019Annual/webprogram/Paper353476.html" class="card-link">Read More</a>
<a href="https://ams.confex.com/ams/2019Annual/recordingredirect.cgi/id/50198?entry_password=null&uniqueid=Paper353476" class="card-link">Recorded Presentation</a>
</div>
</div>
<div class="card">
<div class="card-body">
<h5 class="card-title">Global Synthetic Weather Radar in AWS GovCloud for the U.S. Air Force (2020)</h5>
<h6 class="card-subtitle mb-2 text-muted">Mark S. Veillette, Haig Iskenderian, Patrick M. Lamey, Christopher J. Mattioli, Ashish Banerjee, Mark Worris, Alexander B. Proschitsky, Richard F. Ferris, Artyom Manwelyan, Shibi Rajagopalan, Hammad Usmani, Thomas E. Coe, Jennifer E. Luce, Blaine A. Esgar</h6>
<p class="card-text">
The U.S. Air Force, in collaboration with MIT Lincoln Laboratory, is advancing a machine learning tool for generating global radar-like mosaics for flight operations. Using data from lightning, the GALWEM model, and weather satellite images, a convolutional neural network creates global synthetic weather radar mosaics. Transitioned to the AWS GovCloud, it facilitates real-time evaluation and aids Air Force decision systems. The project entails capability development, cloud integration, user feedback, and ensuring sustainable machine learning practices.
</p>
<a href="https://ams.confex.com/ams/2020Annual/meetingapp.cgi/Paper/363150" class="card-link">Read More</a>
</div>
</div>
<div class="card">
<div class="card-body">
<h5 class="card-title">A Deep Neural Network to Globally Forecast the Track and Intensity of Tropical Cyclones (2020)</h5>
<h6 class="card-subtitle mb-2 text-muted">Hammad Usmani, Aadil Habibi, Daanish Habibi</h6>
<p class="card-text">
As tropical cyclones intensify with global warming, this study harnesses machine learning to predict their tracks and intensities. Utilizing the IBTrACS database and NCEP/NCAR Surface Temperature imagery, a deep neural network combining recurrent and convolutional layers is developed. An accompanying web application delivers forecasts, outperforming the NHC's statistical baseline for Atlantic storms. The open-source tool aims to aid both professionals and amateurs in tropical cyclone predictions, fostering better preparedness.
</p>
<a href="https://ams.confex.com/ams/2020Annual/meetingapp.cgi/Paper/370104" class="card-link">Read More</a>
</div>
</div>
<div class="card">
<div class="card-body">
<h5 class="card-title">Global Synthetic Weather Radar Capability in Support of the U.S. Air Force (2019)</h5>
<h6 class="card-subtitle mb-2 text-muted">Haig Iskenderian, Mark S. Veillette, Christopher J. Mattioli, Patrick M. Lamey, Eric P. Hassey, Ashish Banerjee, Mark Worris, Kendrick Cancio, Shibi Rajagopalan, Hammad Usmani, John P. Dreher, Nessa Hock, John Radovan</h6>
<p class="card-text">
The U.S. Air Force and MIT Lincoln Laboratory have collaborated to develop a synthetic weather radar capability, addressing global areas with limited weather data. This system utilizes a machine learning framework with inputs from global lightning, GALWEM numerical model, and weather satellite images to generate radar mosaics and forecasts up to 12 hours. It aims to enhance the Air Force's decision support systems. The presentation provides insights and outcomes from this partnership.
</p>
<a href="https://ams.confex.com/ams/2019Annual/meetingapp.cgi/Paper/355542" class="card-link">Read More</a>
<a href="https://ams.confex.com/ams/2019Annual/recordingredirect.cgi/oid/Recording51412/paper355542_1.mp4" class="card-link">Recorded Presentation</a>
</div>
</div>
<div class="card">
<div class="card-body">
<h5 class="card-title">Multivariate LSTM Approach to Hurricane Intensity and Tracking Predictions (2021)</h5>
<h6 class="card-subtitle mb-2 text-muted">Akash B. Patel, Hammad Usmani, Jonathan C. Brant</h6>
<p class="card-text">
In the backdrop of climate change and global warming intensifying hurricane conditions, there's an urgent need for real-time prediction of hurricanes and tropical storms. This research leverages deep learning, comparing a multivariate LSTM network with univariate LSTMs for hurricane prediction. The study utilizes data from IBTrACS version 4, hosted by NOAA. The research evaluates the effectiveness of Bidirectional LSTM networks and showcases the superiority of the multivariate model in predicting hurricane trajectories and intensities using MAPE. The outcome aids timely allocation of emergency resources and better preparation for adverse weather conditions.
</p>
<a href="https://ams.confex.com/ams/101ANNUAL/meetingapp.cgi/Paper/380154" class="card-link">Read More</a>
</div>
</div>
<div class="card">
<div class="card-body">
<h5 class="card-title">Global Synthetic Weather Radar in AWS GovCloud for the US Air Force (2020)</h5>
<h6 class="card-subtitle mb-2 text-muted">Mark S. Veillette, H. Iskenderian, P. M. Lamey and co-authors</h6>
<p class="card-text">
The US Air Force and MIT Lincoln Laboratory collaborate to produce a machine learning application creating global radar-like mosaics for pre-flight planning and execution. Drawing on various data sources, a convolutional neural network designs synthetic weather radar mosaics, integrated with GALWEM for up to 12-hour radar-forward forecasts. The system, in development for AWS GovCloud, capitalizes on extensive cloud compute and storage resources, feeding into Air Force decision aids like WxCC and AFW-WEBS viewer. The initiative represents a pioneering move to transit a mature ML system to AWS GovCloud. The project's facets include capability inception, AWS GovCloud development, training with feedback, and upholding ML "best practices" for sustained functionality post-transfer.
</p>
<a href="https://ams.confex.com/ams/2020Annual/webprogram/Paper363150.html" class="card-link">Read More</a>
</div>
</div>
<div class="card">
<div class="card-body">
<h5 class="card-title">P.A.M. - Personal Assistant Machine</h5>
<h6 class="card-subtitle mb-2 text-muted">Loebner Prize 2017 Entry</h6>
<p class="card-text">A recurrent neural network large language model that is multilingual.</p>
<a href="https://www.aomartin.co.uk/uploads/loebner_2017_finalist_selection_transcripts.pdf" target="_blank" class="card-link">View Results</a>
<p class="card-text"><small class="text-muted">Hammad Usmani</small></p>
</div>
</div>
</div>
<a name="Programming"></a>
<h2>5. Programming Languages</h2>
<div id="skillsAccordion" role="tablist">
<!-- Python 2 & 3 -->
<div class="card">
<div class="card-header" role="tab" id="headingPython">
<h5 class="mb-0">
<a data-toggle="collapse" href="#collapsePython" role="button" aria-expanded="false" aria-controls="collapsePython">
Python 2 & 3
</a>
</h5>
</div>
<div id="collapsePython" class="collapse" role="tabpanel" aria-labelledby="headingPython" data-parent="#skillsAccordion">
<div class="card-body">
<p>10 Years of Experience</p>
<!-- Python related links -->
<a href="https://www.tensorflow.org/" class="btn btn-primary btn-sm">TensorFlow</a>
<a href="http://scikit-learn.org/stable/" class="btn btn-primary btn-sm">scikit-learn</a>
<a href="https://keras.io/" class="btn btn-primary btn-sm">Keras</a>
<a href="https://anaconda.org/anaconda/python" class="btn btn-primary btn-sm">Anaconda</a>
<a href="http://www.nltk.org/" class="btn btn-primary btn-sm">NLTK</a>
<a href="https://matplotlib.org/" class="btn btn-primary btn-sm">matplotlib</a>
<a href="http://flask.pocoo.org/" class="btn btn-primary btn-sm">flask</a>
<a href="https://www.scipy.org/" class="btn btn-primary btn-sm">SciPy</a>
<a href="https://ipython.org/" class="btn btn-primary btn-sm">IPython</a>
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</div>
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<!-- Java -->
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Java
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</h5>
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<div id="collapseJava" class="collapse" role="tabpanel" aria-labelledby="headingJava" data-parent="#skillsAccordion">
<div class="card-body">
<p>7 Years of Experience</p>
<!-- Java related links -->
<a href="https://www.scala-lang.org/" class="btn btn-primary btn-sm">Scala</a>
<a href="https://www.eclipse.org/" class="btn btn-primary btn-sm">Eclipse</a>
<a href="https://maven.apache.org/" class="btn btn-primary btn-sm">Maven</a>
<a href="https://docs.oracle.com/javase/7/docs/api/overview-summary.html" class="btn btn-primary btn-sm">Java.*</a>
<a href="http://openjdk.java.net/" class="btn btn-primary btn-sm">OpenJDK</a>
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<!-- C / C++ -->
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C / C++
</a>
</h5>
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<div id="collapseCCpp" class="collapse" role="tabpanel" aria-labelledby="headingCCpp" data-parent="#skillsAccordion">
<div class="card-body">
<p>7 Years of Experience</p>
<!-- C / C++ related links -->
<a href="https://www.arduino.cc/en/Main/Software" class="btn btn-primary btn-sm">Arduino</a>
<a href="http://www.codeblocks.org/" class="btn btn-primary btn-sm">CodeBlocks</a>
<a href="https://www.visualstudio.com/" class="btn btn-primary btn-sm">Visual Studio</a>
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SQL
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<div id="collapseSQL" class="collapse" role="tabpanel" aria-labelledby="headingSQL" data-parent="#skillsAccordion">
<div class="card-body">
<p>5 Years of Experience</p>
<!-- SQL related links -->
<a href="https://technet.microsoft.com/en-us/library/ms189826(v=sql.90).aspx" class="btn btn-primary btn-sm">T-SQL</a>
<a href="https://www.mysql.com/" class="btn btn-primary btn-sm">mySQL</a>
<a href="https://www.postgresql.org/" class="btn btn-primary btn-sm">PostgreSQL</a>
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JavaScript
</a>
</h5>
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<div id="collapseJavaScript" class="collapse" role="tabpanel" aria-labelledby="headingJavaScript" data-parent="#skillsAccordion">
<div class="card-body">
<p>14 Years of Experience</p>
<!-- JavaScript related links -->
<a href="https://nodejs.org/en/" class="btn btn-primary btn-sm">Node.js</a>
<a href="https://angularjs.org/" class="btn btn-primary btn-sm">Angular.js</a>
<a href="https://expressjs.com/" class="btn btn-primary btn-sm">Express.js</a>
<a href="http://www.chartjs.org/" class="btn btn-primary btn-sm">Chart.js</a>
<a href="https://d3js.org/" class="btn btn-primary btn-sm">D3.js</a>
</div>
</div>
</div>
</div>
<a name="Credentials"></a>
<h2>6. Credentials</h2>
<div class="card-columns">
<div class="card">
<img class="card-img-top" src="https://learn.microsoft.com/media/learn/certification/badges/microsoft-certified-associate-badge.svg">
<div class="card-body">
<h5 class="card-title"> Microsoft Certified: Azure AI Engineer Associate </h5>
<p class="card-text">This certifies expertise to Plan and manage an Azure AI solution, Implement decision support solutions, Implement computer vision solutions, Implement natural language processing solutions, Implement knowledge mining and document intelligence solutions, and Implement generative AI solutions.
</p>
</div>
<ul class="list-group list-group-flush">
<li class="list-group-item">February 26, 2024 to February 26, 2025</li>
</ul>
<div class="card-body">
<a href="https://learn.microsoft.com/en-us/users/hammad-1421/credentials/d9b1bd8e88ed3e31" class="card-link">Overview</a>
</div>
</div>
<div class="card">
<img class="card-img-top" src="https://cdn.qwiklabs.com/oug2RNEtJGpZn6nxIYgSUjyh%2FVGSZjX%2FfUYi5GS%2FKZ0%3D">
<div class="card-body">
<h5 class="card-title">Google Cloud Generative AI</h5>
<p class="card-text"> Complete courses titled Introduction to Generative AI, Introduction to Large Language Models (LLM) and Introduction to Responsible AI. This certifies expertise of products including Vertex AI.</p>
</div>
<ul class="list-group list-group-flush">
<li class="list-group-item">June 25, 2023</li>
</ul>
<div class="card-body">
<a href="https://www.cloudskillsboost.google/public_profiles/5e4c2cc1-f62a-4a09-a53f-39c27ebcfc44" class="card-link">Overview</a>
</div>
</div>
<div class="card">
<img class="card-img-top" src="img/hbs.svg" alt="Card image cap">
<div class="card-body">
<h5 class="card-title">Harvard Business School Online: Entrepreneurship Essentials</h5>
<p class="card-text">Entrepreneurship Essentials is a 4-week, 30-hour online certificate program from Harvard Business School. Entrepreneurship Essentials introduces participants to the entrepreneurial journey from finding an idea to gaining traction in the marketplace to raising capital for a venture. Participants learn an overarching framework—People, Opportunity, Context, Deal—to evaluate opportunities, manage start-ups, and finance ventures.</p>
</div>
<ul class="list-group list-group-flush">
<li class="list-group-item">2020</li>
<li class="list-group-item">Complete</li>
</ul>
<div class="card-body">
<a href="https://online.hbs.edu/courses/entrepreneurship-essentials/" class="card-link">Overview</a>
</div>
</div>
<div class="card">
<img class="card-img-top" src="https://s3-us-west-1.amazonaws.com/udacity-content/degrees/catalog-images/ML.png" alt="Card image cap">
<div class="card-body">
<h5 class="card-title">Udacity Nanodegree Machine Learning Engineer</h5>
<p class="card-text">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.</p>
</div>
<ul class="list-group list-group-flush">
<li class="list-group-item">Summer 2018</li>
<li class="list-group-item">Nanodegree</li>
</ul>
<div class="card-body">
<a href="https://www.udacity.com/course/machine-learning-engineer-nanodegree--nd009" class="card-link">Overview</a>
<a href="https://github.com/hammad93/machine-learning-projects" class="card-link">Git Repository</a>
</div>
</div>
<div class="card">
<img class="card-img-top" src="img/hbs.svg" alt="Card image cap">
<div class="card-body">
<h5 class="card-title">Harvard Business School Online: Credential of Readiness</h5>
<p class="card-text">Harvard Business School Online 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.</p>
</div>
<ul class="list-group list-group-flush">
<li class="list-group-item">July, 2017</li>
<li class="list-group-item">Pass</li>
</ul>
<div class="card-body">
<a href="https://hbx.hbs.edu/courses/core/" class="card-link">Overview</a>
</div>
</div>
<div class="card">
<img class="card-img-top" src="https://acclaim-production-app.s3.amazonaws.com/images/f95262d1-c8dd-4b3c-bf5e-17127962ed5b/Explorer_no_stars.png" alt="Card image cap">
<div class="card-body">
<h5 class="card-title">Big Data - Programming</h5>
<p class="card-text">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.</p>
</div>
<ul class="list-group list-group-flush">
<li class="list-group-item">May, 2016</li>
</ul>
<div class="card-body">
<a href="https://www.youracclaim.com/badges/4ecb9276-1702-4328-a807-1a6890f99759" class="card-link">Overview</a>
</div>
</div>
<div class="card">
<img class="card-img-top" src="https://acclaim-production-app.s3.amazonaws.com/images/f95262d1-c8dd-4b3c-bf5e-17127962ed5b/Explorer_no_stars.png" alt="Card image cap">
<div class="card-body">
<h5 class="card-title">Big Data Foundations</h5>
<p class="card-text">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.</p>
</div>
<ul class="list-group list-group-flush">
<li class="list-group-item">December, 2015</li>
</ul>
<div class="card-body">
<a href="https://www.youracclaim.com/badges/b597b74e-8f8c-47bb-b339-04a10c19792e" class="card-link">Overview</a>
</div>
</div>
<div class="card">
<img class="card-img-top" src="https://acclaim-production-app.s3.amazonaws.com/images/f95262d1-c8dd-4b3c-bf5e-17127962ed5b/Explorer_no_stars.png" alt="Card image cap">
<div class="card-body">
<h5 class="card-title">Big Data Hadoop Foundations</h5>
<p class="card-text">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.</p>
</div>
<ul class="list-group list-group-flush">
<li class="list-group-item">April, 2016</li>
</ul>
<div class="card-body">
<a href="https://www.youracclaim.com/badges/8272be10-82c3-47ea-9c7c-ca7e0dce857c" class="card-link">Overview</a>
</div>
</div>
</div>
<a name="Personal"></a>
<h2>Personality</h2>
<img src="img/headshot_202309051838.png" style="width: 35rem;">
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<div class="card-body">
<iframe width="100%" src="https://www.youtube.com/embed/Jg_FXYFkYjg" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>
</div></br>
<div class="card" style="width: 25rem;">
<div class="card-body">
<iframe width="100%" src="https://www.youtube.com/embed/FGu0wbS24Bw" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>
</div></br>
<div class="card" style="width: 25rem;">
<div class="card-body">
<iframe width="100%" src="https://www.youtube.com/embed/3TQMxXCR4I8" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>
</div></br>
<div class="card">
<div class="card-body">
<iframe width="100%" src="https://www.youtube.com/embed/RElOYo7Nyek" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>
</div>
</div></br>
<div class="container mt-5">
<div class="row">
<div class="col-md-6">
<div class="card">
<div class="card-body">
<h5 class="card-title">Myers Briggs Type Indicator</h5>
<p class="card-text">I am an <strong>ENTJ</strong> (Extroverted Intuitive Thinking Judging) according to an assessment from 16personalities.com</p>
<img src="https://upload.wikimedia.org/wikipedia/commons/4/43/Rational_NT_Personality_Type_MBTI.jpg" alt="Rational NT Personality Type" class="card-img-top">
</div>
</div>
</div>
</div>
</div></br>
<div id="accordion" role="tablist">
<div class="card">
<div class="card-header" role="tab" id="headingOne">
<h5 class="mb-0">
<a data-toggle="collapse" href="#collapseOne" role="button" aria-expanded="true" aria-controls="collapseOne">
What is the most interesting fact or trend you've learned from analyzing data?
</a>
</h5>
</div>
<div id="collapseOne" class="collapse show" role="tabpanel" aria-labelledby="headingOne" data-parent="#accordion">
<div class="card-body">
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.
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<div class="card">
<div class="card-header" role="tab" id="headingTwo">
<h5 class="mb-0">
<a class="collapsed" data-toggle="collapse" href="#collapseTwo" role="button" aria-expanded="false" aria-controls="collapseTwo">
Describe a time you experienced a challenge while building a product/project and how you overcame it.
</a>
</h5>
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<div id="collapseTwo" class="collapse" role="tabpanel" aria-labelledby="headingTwo" data-parent="#accordion">
<div class="card-body">
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.
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<h5 class="mb-0">
<a class="collapsed" data-toggle="collapse" href="#collapseThree" role="button" aria-expanded="false" aria-controls="collapseThree">
What are the qualities you most desire in a work environment and/or manager?
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</h5>
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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.
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<h5 class="mb-0">
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Describe a unique experience you've had and how it changed your perspective.
</a>
</h5>
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<div id="collapseFour" class="collapse" role="tabpanel" aria-labelledby="headingFour" data-parent="#accordion">
<div class="card-body">
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.
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<div class="card-header" role="tab" id="headingFive">
<h5 class="mb-0">
<a class="collapsed" data-toggle="collapse" href="#collapseFive" role="button" aria-expanded="false" aria-controls="collapseFive">
What big-data problem would you solve that can benefit society at a large scale?
</a>
</h5>
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<div id="collapseFive" class="collapse" role="tabpanel" aria-labelledby="headingFive" data-parent="#accordion">
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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.
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<h5 class="mb-0">
<a class="collapsed" data-toggle="collapse" href="#collapseSix" role="button" aria-expanded="false" aria-controls="collapseSix">
How do you see data science and machine learning affect the way we design software?
</a>
</h5>
</div>
<div id="collapseSix" class="collapse" role="tabpanel" aria-labelledby="headingSix" data-parent="#accordion">
<div class="card-body">
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.
</div>
</div>
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</div>
<a name="References"></a>
<h2>Professional References</h2>
<div class="card-columns">
<div class="card p-3">
<blockquote class="blockquote mb-0 card-body">
<p>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.</p>
<footer class="blockquote-footer">
<small class="text-muted">
Dr. Hamed Almalki, <cite title="Source Title">Change Management Consultant at Saei</cite>
</small>
</footer>
</blockquote>
<ul class="list-group list-group-flush">
<h6><li class="list-group-item">halmalki@knights.ucf.edu</li></h6>
</ul>
</div>
<div class="card p-3">
<blockquote class="blockquote mb-0 card-body">
<p>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!</p>
<footer class="blockquote-footer">
<small class="text-muted">
Andy D., <cite title="Source Title">Project Incharge at Diligence Digital India (P) Ltd</cite>
</small>
</footer>
</blockquote>
<ul class="list-group list-group-flush">
<h6><li class="list-group-item">akashd.cwg@gmail.com</li></h6>
</ul>
</div>
<div class="card p-3">
<blockquote class="blockquote mb-0 card-body">
<p>Hammad is detail-oriented and committed to success in whatever role he is in.</p>
<footer class="blockquote-footer">
<small class="text-muted">
Saad Usmani, <cite title="Source Title">Data Scientist at New College of Florida</cite>
</small>
</footer>
</blockquote>
<ul class="list-group list-group-flush">
<h6><li class="list-group-item">saadu.usmani@gmail.com</li></h6>
</ul>
</div>
<div class="card p-3">
<blockquote class="blockquote mb-0 card-body">
<p>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.</p>
<footer class="blockquote-footer">
<small class="text-muted">
Mohammed Rahman, <cite title="Source Title">Systems Analyst at K3 solutions llc</cite>
</small>
</footer>
</blockquote>
<ul class="list-group list-group-flush">
<h6><li class="list-group-item">abdur.rahman@k3solutions.net</li></h6>
</ul>
</div>
<div class="card p-3">
<blockquote class="blockquote mb-0 card-body">
<p>Hammad is a tenacious computer scientist that exemplified entrepreneurship and produced excellent work.</p>
<footer class="blockquote-footer">
<small class="text-muted">
Sam Verma, <cite title="Source Title">Programmer Analyst III at Geico</cite>
</small>
</footer>
</blockquote>
<ul class="list-group list-group-flush">
<h6><li class="list-group-item">s.verma2907@gmail.com</li></h6>
</ul>
</div>
<div class="card p-3">
<blockquote class="blockquote mb-0 card-body">
<p>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.</p>
<footer class="blockquote-footer">
<small class="text-muted">
Chris Mattioli, <cite title="Source Title">Data Scientist @ AWS</cite>
</small>
</footer>
</blockquote>
</div>
<div class="card p-3">
<blockquote class="blockquote mb-0 card-body">
<p>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.</p>
<footer class="blockquote-footer">
<small class="text-muted">
Anay Patel, <cite title="Source Title">Master of Public Health at Columbia University</cite>
</small>
</footer>
</blockquote>
<ul class="list-group list-group-flush">
<h6><li class="list-group-item">aap2218@cumc.columbia.edu</li></h6>
</ul>
</div>
<div class="card p-3">
<blockquote class="blockquote mb-0 card-body">
<p>Hammad is an exceptional talent in the realm of Artificial Intelligence and Data Engineering. During our time working together, I was consistently impressed by their expertise in R&D, especially within the weather and environmental sectors. Hammad's Python programming skills are top-notch, and they consistently deliver results that exceed expectations. Anyone would be fortunate to have Hammad as part of their team. Although he's proven himself in the weather and environmental sectors, he would thrive in any sector he decides to pursue.</p>
<footer class="blockquote-footer">
<small class="text-muted">
Nofel Khan, <cite title="Source Title">Data Engineer</cite>
</small>
</footer>
</blockquote>
<ul class="list-group list-group-flush">
<h6><li class="list-group-item">mohammed090909@gmail.com</li></h6>
</ul>
</div>
</div>
<h2>Attributions</h2>
<a href="https://commons.wikimedia.org/wiki/File:Rational_NT_Personality_Type_MBTI.jpg">czarinacleopatra</a>, <a href="https://creativecommons.org/licenses/by-sa/4.0">CC BY-SA 4.0</a>, via Wikimedia Commons</br>
ChatGPT 3.5, 4
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