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<!DOCTYPE HTML>
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<p>©Copyright ©<script>document.write(new Date().getFullYear());</script> All rights reserved</br><a href="https://www.linkedin.com/in/sofiadutta" target="_blank">@Sofia Dutta</a></span></br>
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<h1>Hi! <br>I'm Sofia</h1>
<h2>A Software Engineer with Cisco Systems Inc., building models to identify apps for the Cisco Secure Firewall.</br>I am interested in working on challenging problems around data!</h2>
<p><a class="btn btn-primary btn-learn" href="assets/resume-sofia-dutta-102823.pdf" target="_blank">Download Resume <i class="icon-download4"></i></a></p>
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<span class="heading-meta">About</span>
<h2 class="colorlib-heading">Who Am I?</h2>
<strong>My name is Sofia Dutta,</strong> a Software Engineer at <a href="https://www.cisco.com/site/us/en/index.html" target="_blank">Cisco Systems Inc.</a> At Cisco, I am part of the Cisco Secure Firewall team working on ways to identify applications for <a href="https://www.cisco.com/site/us/en/products/security/firewalls/index.html" target="_blank">the firewall</a>.</br></br>I have previously worked as a technical leader at a <a href="https://newwave.io/" target="_blank">startup</a>, building a data quality solution called the <a href="https://newwave.io/imersis-newwave-mathematica-state-data-quality/" target="_blank">Imersis project</a>. Before that I worked on many Data Science and Deep Learning projects as a graduate student at <a href="https://umbc.edu/" target="_blank">UMBC</a>.</br></br>I also worked as a Software Engineer for <a href="https://www.tcs.com/" target="_blank">Tata Consultancy Services</a> from 2010 to 2018.</p>
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<h3>Python Programming</h3>
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<h3>Deep Learning</h3>
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<h3>Master's in Data Science with a <strong>4.0</strong> GPA!</h3>
<a href="mailto:sofia.dutta17@gmail.com" target="_blank" class="btn-hire">Hire me</a>
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<h2 class="colorlib-heading animate-box">Work Experience</h2>
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<h2><a href="https://newwave.io/" target="_blank">Software Engineer</a> <span>Present - 2023</span></h2>
<p>Software Engineer at <a href="https://www.cisco.com/site/us/en/index.html" target="_blank">Cisco Systems, Inc.</a>, Fulton, MD, USA</p>
<ul>
<li>I am building ways of identifying applications for <a href="https://www.cisco.com/site/us/en/products/security/firewalls/index.html" target="_blank">the firewall</a>.</li>
</ul>
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<h2><a href="https://newwave.io/" target="_blank">Technical Leader</a> <span>2023 - 2021</span></h2>
<p>Technical Leader at <a href="https://newwave.io/" target="_blank">NewWave Telecom and Technologies, Inc.</a>, Woodlawn, MD, USA</p>
<ul>
<li>Designed the complete system architecture, database schema, and data workflow for the <a href="https://newwave.io/imersis-newwave-mathematica-state-data-quality" target="_blank">Imersis</a> data quality analytics platform.</li>
<li>Built the project's cloud infrastructure setup from scratch.</li>
<li>Built scripts to process hundreds of millions of healthcare records from the Centers for Medicare & Medicaid.</li>
<li>Created pre-processing scripts for consuming large batches of unstructured customer data.</li>
<li>Developed Apache PySpark code to compute data quality metrics for customer data.</li>
<li>Created Looker dashboard visualizations with drill-down options that "explains" why the data quality came out to a certain value.</li>
<li>Due to the lack of large quantities of data, re-designed the machine learning goal of the project into a data quality "Explainable AI" system.</li>
<li>Built a data quality system for State governments that allows them to understand where to improve their upstream data ingestion processes and helped them observe how that improves their data quality over time.</li>
<li>Reduced costs at four levels of the project:</li>
<ul>
<li>Pre-processing: Built scripts that brought down the data pre-processing time from ten days to a couple of hours.</li>
<li>Uptime of cluster: Analyzed causes of high cloud expenditure and deployed Apache Airflow workflow management platform scripts to automate resource uptime only during hours of usage. Reduced cost from thousands of dollars to a couple hundred.</li>
<li>Storage v/s data transfer: Performed the cost advantage analysis of using a Google compute engine with large storage versus using more network data transfer.</li>
<li>Partially working in local servers: Built a system that handled pre-processing in our local data farm to reduce project costs from over ten thousand dollars to a few hundred in a month.</li>
</ul>
<li>Quickly learned new technologies like Apache Airflow, Databricks, and Google Cloud Platform and guided team members in their technology ramp-up for the past 2 years and helped them in setting up data workflows in the cloud.</li>
<li>Provided educational expertise and mentoring to junior team members.</li>
<li>Built product feature lists with stakeholders, conducted system design sessions with other architects on the team and led code review meetings.</li>
<li>Investigated root causes for customer-found defects. Carried out several customer demonstrations to help sell the product and handled rapid prototyping and solution building for ad-hoc requirements and last-minute feature requests from the customer.</li>
<li>Advised management, business, and technical staff on the usage of specific technologies like Apache Airflow and Google Cloud Platform.</li>
</ul>
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<h2><a href="https://newwave.io/" target="_blank">Data Scientist Intern</a> <span>2020 - 2020</span></h2>
<p>Data Scientist Intern at <a href="https://newwave.io/" target="_blank">NewWave Telecom and Technologies, Inc.</a>, Woodlawn, MD, USA</p>
<ul>
<li>Carried out data visualization tasks using LookML, Matplotlib, and Seaborn to present quality measures based on chosen computation metrics.</li>
<li>Successfully improved computation speed by 10-fold by deploying data analysis workflow in Google Cloud Platform (GCP) clusters and using Apache Spark for quality metrics computations.</li>
<li>Collaborated with the Product Owner and other engineers in creating mechanisms for generating fake training data using Python programming to test out the efficacy of machine learning algorithms used in the project.</li>
<li>Carried out necessary DevOps tasks for setting up Big Data Analytics environment by configuring GCP environment to execute Python programs and connected the cloud infrastructure with Looker's dashboards for delivering computed results to be presented to customers.</li>
</ul>
</div>
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<h2><a href="https://ebiquity.umbc.edu" target="_blank">Researcher</a> <span>2020 - 2019</span></h2>
<p>Researcher at <a href="https://ebiquity.umbc.edu" target="_blank">Ebiquity Group</a>, <a href="https://www.umbc.edu" target="_blank">UMBC</a>, USA</p>
<ul>
<li>Authored an <a href="https://ebiquity.umbc.edu/paper/owl/id/887/Context-Sensitive-Access-Control-in-Smart-Home-Environments">Ontology</a> for Smart Home Access Control by extending earlier research in Semantic Web.</li>
<li>Developed an <a href="https://github.com/sofiadutta/AndroidSmartLights">Android app</a> for handling context-sensitive access control in a Smart Home Environment.</li>
<li>Created <a href="https://www.youtube.com/watch?v=DZq-oZ_Cv1g&list=UUEB2cqBZTym9WxWvGu2UA0w">YouTube videos</a> for presentation to the National Institute of Standards and Technology.</li>
<li>Published a <a href="https://ebiquity.umbc.edu/paper/html/id/887/Context-Sensitive-Access-Control-in-Smart-Home-Environments">paper</a> at the IEEE Big Data Security 2020 conference.</li>
</ul>
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<h2><a href="https://www.tcs.com" target="_blank">Software Engineer, Technical Leader</a> <span>2018 - 2010</span></h2>
<p>Software Developer and Data Analyst at <a href="https://www.tcs.com" target="_blank">Tata Consultancy Services (TCS) Ltd.</a>, India</p>
<ul>
<li>Led the design, development, and delivery of API interfaces using PL/SQL stored procedures for several projects of TCS.</li>
<li>Carried out change based regression impact analysis, created software functional specifications, prepared test plans for several projects of TCS.</li>
<li>Performed system integration, user-acceptance and performance testing and ensured client systems had very high uptime even when carrying out data migration activities. Saved millions of dollars in potential revenue lost to the client and was awarded for said effort by clients.</li>
</ul>
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<span class="heading-meta">My Specialty</span>
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<h3>Python</h3>
<div class="progress">
<div class="progress-bar color-1" role="progressbar" aria-valuenow="95"
aria-valuemin="0" aria-valuemax="100" style="width:95%">
<span>95%</span>
</div>
</div>
</div>
</div>
<div class="col-md-6 animate-box" data-animate-effect="fadeInRight">
<div class="progress-wrap">
<h3>Java</h3>
<div class="progress">
<div class="progress-bar color-2" role="progressbar" aria-valuenow="80"
aria-valuemin="0" aria-valuemax="100" style="width:80%">
<span>80%</span>
</div>
</div>
</div>
</div>
<div class="col-md-6 animate-box" data-animate-effect="fadeInLeft">
<div class="progress-wrap">
<h3>PyTorch</h3>
<div class="progress">
<div class="progress-bar color-5" role="progressbar" aria-valuenow="90"
aria-valuemin="0" aria-valuemax="100" style="width:90%">
<span>90%</span>
</div>
</div>
</div>
</div>
<div class="col-md-6 animate-box" data-animate-effect="fadeInRight">
<div class="progress-wrap">
<h3>Sci-kit Learn, MLlib, OpenCV</h3>
<div class="progress">
<div class="progress-bar color-4" role="progressbar" aria-valuenow="85"
aria-valuemin="0" aria-valuemax="100" style="width:85%">
<span>85%</span>
</div>
</div>
</div>
</div>
<div class="col-md-6 animate-box" data-animate-effect="fadeInLeft">
<div class="progress-wrap">
<h3>Keras</h3>
<div class="progress">
<div class="progress-bar color-3" role="progressbar" aria-valuenow="80"
aria-valuemin="0" aria-valuemax="100" style="width:80%">
<span>80%</span>
</div>
</div>
</div>
</div>
<div class="col-md-6 animate-box" data-animate-effect="fadeInRight">
<div class="progress-wrap">
<h3>Tensorflow</h3>
<div class="progress">
<div class="progress-bar color-6" role="progressbar" aria-valuenow="80"
aria-valuemin="0" aria-valuemax="100" style="width:80%">
<span>80%</span>
</div>
</div>
</div>
</div>
<div class="col-md-6 animate-box" data-animate-effect="fadeInLeft">
<div class="progress-wrap">
<h3>Apache Airflow</h3>
<div class="progress">
<div class="progress-bar color-7" role="progressbar" aria-valuenow="80"
aria-valuemin="0" aria-valuemax="100" style="width:80%">
<span>80%</span>
</div>
</div>
</div>
</div>
<div class="col-md-6 animate-box" data-animate-effect="fadeInRight">
<div class="progress-wrap">
<h3>PySpark</h3>
<div class="progress">
<div class="progress-bar color-8" role="progressbar" aria-valuenow="90"
aria-valuemin="0" aria-valuemax="100" style="width:90%">
<span>90%</span>
</div>
</div>
</div>
</div>
<div class="col-md-6 animate-box" data-animate-effect="fadeInLeft">
<div class="progress-wrap">
<h3>TSQL, Oracle SQL, PL/SQL</h3>
<div class="progress">
<div class="progress-bar color-9" role="progressbar" aria-valuenow="95"
aria-valuemin="0" aria-valuemax="100" style="width:95%">
<span>95%</span>
</div>
</div>
</div>
</div>
<div class="col-md-6 animate-box" data-animate-effect="fadeInRight">
<div class="progress-wrap">
<h3>Oracle Apps, Oracle Fusion</h3>
<div class="progress">
<div class="progress-bar color-10" role="progressbar" aria-valuenow="90"
aria-valuemin="0" aria-valuemax="100" style="width:90%">
<span>90%</span>
</div>
</div>
</div>
</div>
<div class="col-md-6 animate-box" data-animate-effect="fadeInLeft">
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<h3>Google Cloud</h3>
<div class="progress">
<div class="progress-bar color-11" role="progressbar" aria-valuenow="80"
aria-valuemin="0" aria-valuemax="100" style="width:80%">
<span>80%</span>
</div>
</div>
</div>
</div>
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<h3>AWS S3</h3>
<div class="progress">
<div class="progress-bar color-12" role="progressbar" aria-valuenow="80"
aria-valuemin="0" aria-valuemax="100" style="width:80%">
<span>80%</span>
</div>
</div>
</div>
</div>
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<div class="progress-wrap">
<h3>LookML, Looker</h3>
<div class="progress">
<div class="progress-bar color-13" role="progressbar" aria-valuenow="85"
aria-valuemin="0" aria-valuemax="100" style="width:85%">
<span>85%</span>
</div>
</div>
</div>
</div>
<div class="col-md-6 animate-box" data-animate-effect="fadeInRight">
<div class="progress-wrap">
<h3>Knowledge Graph, OWL, SPARQL</h3>
<div class="progress">
<div class="progress-bar color-7" role="progressbar" aria-valuenow="75"
aria-valuemin="0" aria-valuemax="100" style="width:75%">
<span>75%</span>
</div>
</div>
</div>
</div>
</div>
</div>
</section>
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<a data-toggle="collapse" data-parent="#accordion" href="#collapseOne" aria-expanded="true" aria-controls="collapseOne">Master's Degree in Data Science</a>
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<p><strong>2020 - 2019</strong></br>Completed my Master's in Data Science from <a href="https://umbc.edu" target="_blank">University of Maryland, Baltimore County</a>, Baltimore, USA. GPA: <strong>4.0</strong>!</br>See transcript <a href="assets/transcript-sofia-dutta.pdf" target="_blank">here</a>.</p>
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<h4 class="panel-title">
<a class="collapsed" data-toggle="collapse" data-parent="#accordion" href="#collapseTwo" aria-expanded="false" aria-controls="collapseTwo">Bachelor's Degree in Computer Science
</a>
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<div class="panel-body">
<p><strong>2010 - 2006</strong></br>Completed my Bachelor of Technology in Computer Science from <a href="https://makautwb.ac.in" target="_blank">West Bengal University of Technology</a>, Kolkata, India with a <strong>3.5</strong> GPA!</br>See transcript <a href="assets/ug_transcript.pdf" target="_blank">here</a>.</p>
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</section>
<section class="colorlib-captsone" data-section="capstone">
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<span class="heading-meta">Captsone Project</span>
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<h2><a href="https://sites.google.com/umbc.edu/data606/home/previous-semesters/fall-20/sofia-dutta" target="_blank">QABot: A Chatbot for Open Question Answering Using Neural Networks</a></h2>
<p><a href="https://sites.google.com/umbc.edu/data606/home/previous-semesters/fall-20/sofia-dutta" target="_blank">QABot: A Chatbot for Open Question Answering Using Neural Networks</a>: Built “QABot”, a Chatbot using the sequence-to-sequence Deep Learning model that utilizes the Encoder Decoder Neural Network architecture combined with Attention Mechanism to answer user search queries. Created a model by training a Deep Neural using the PyTorch Deep Learning Framework. Used Recurrent Neural Network architecture that are better at dealing with text sequences. Used both Teacher Forcing and Auto-Regressive approaches for model training and Auto-Regressive approach for model evaluation. Used BERT (Bidirectional Encoder Representations from Transformers) for tokenization and combined Transformer and GPT-2 for model fine tuning.</p>
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<h3>Capstone: QABot standard</h3>
<p><a href="datascience-ipynbs/capstone/QABot.html" target="_blank">QABot standard</a></p>
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<h3>Capstone: QABot using RNN</h3>
<p><a href="datascience-ipynbs/capstone/QABot_seq2seq_model_using_rnn.html" target="_blank">QABot using RNN</a></p>
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<h3>Capstone: QABot Transformer</h3>
<p><a href="datascience-ipynbs/capstone/QABot_seq2seq_model_using_transformer.html" target="_blank">QABot using Transformer</a></p>
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<h3>PyTorch project</h3>
<p><a href="datascience-ipynbs/pytorch/CycleGAN_Img_Translation_PyTorch_Horse2Zebra.html" target="_blank">Horse2Zebra Image translation using CycleGAN</a></p>
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<h3>PyTorch project</h3>
<p><a href="datascience-ipynbs/pytorch/CycleGAN_Img_Translation_PyTorch_Orange2Apple.html" target="_blank">Orange2Apple Image translation using CycleGAN</a></p>
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<h3>PyTorch project</h3>
<p><a href="datascience-ipynbs/pytorch/Sentiment-Analysis-using-PyTorch.html" target="_blank">Sentiment Analysis using PyTorch</a></p>
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</span>
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<h3>PyTorch project</h3>
<p><a href="datascience-ipynbs/pytorch/Image-Classification-using-PyTorch.html" target="_blank">Image classification using PyTorch</a></p>
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<h3>PyTorch project</h3>
<p><a href="datascience-ipynbs/pytorch/WGAN.html" target="_blank">Image generation using WGAN</a></p>
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<h3>PyTorch project</h3>
<p><a href="datascience-ipynbs/pytorch/Denoising-Autoencoder.html" target="_blank">Image reconstruction using Denoising Autoencoder</a></p>
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<h3>Exploratory Data Analytics</h3>
<p><a href="datascience-ipynbs/EDA/Data_Analysis_Baltimore_City_Salaries.html" target="_blank">Baltimore City Govt. Salary data analyzed for income inequality</a></p>
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<h3>Exploratory Data Analytics</h3>
<p><a href="datascience-ipynbs/EDA/Data_Analysis_NYC_Film_Permits.html" target="_blank">New York City Film Permit data analyzed to find popular filming locations</a></p>
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<h3>Exploratory Data Analytics</h3>
<p><a href="datascience-ipynbs/EDA/Data_Analysis_NYC_Fire_Department.html" target="_blank">New York State Fire Dept. Fallen Heroes data analyzed to find significant incidents</a></p>
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<h3>Sentiment Analysis using Word2Vec Doc2Vec</h3>
<p><a href="datascience-ipynbs/sentiment-analysis/Sentiment_Analysis_Amazon_Laptop_Review.html" target="_blank">On Amazon laptop review data using SVM, LR, Keras CNN and Bidirectional LSTM</a></p>
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<h3>Sentiment Analysis using Word2Vec Doc2Vec</h3>
<p><a href="datascience-ipynbs/sentiment-analysis/Sentiment_Analysis_IMDB_Movie_Review.html" target="_blank">On IMDb Movie review data using SVM, LR, Keras CNN and Bidirectional LSTM</a></p>
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<h3>Big Data Analytics using PySpark MongoDB</h3>
<p><a href="datascience-ipynbs/big-data-analytics/Using_MyClassifier_Twitter_Data_Sentiment_Classification_and_Big_Data_Analytics_on_Spark_Dataframe.html" target="_blank">1. My Classifier, MongoDB</a></br>
<a href="datascience-ipynbs/big-data-analytics/Twitter_Stream_Analysis_Using_Spark_Streaming.html" target="_blank">2. Spark Streaming Analytics</a></br>
<a href="datascience-ipynbs/big-data-analytics/Using_SparkMLLib_Word2Vec_Model_Driven_LogReg_Sentiment_MyClassifier_Creation.html" target="_blank">3. MLlib, Model creation</a></p>
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<h2><a href="https://ebiquity.umbc.edu/paper/html/id/887" target="_blank">Context Sensitive Access Control in Smart Home Environments</a></h2>
<p>Sofia Dutta et. al., <a href="https://ebiquity.umbc.edu/paper/html/id/887" target="_blank">"Context Sensitive Access Control in Smart Home Environments"</a>, InProceedings, <i>6th IEEE International Conference on Big Data Security on Cloud (BigDataSecurity2020),</i> May 26, 2020, Baltimore, MD, USA.</p>
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<h2>Smart home controller app with rules demo</h2>
<iframe class="embed-responsive-item" src="https://www.youtube.com/embed/DZq-oZ_Cv1g" allowfullscreen>
Smart home controller app with rules demo
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Smart home controller app demo
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<p>sofia DOT dutta 17 AT gmail DOT com</p>
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