Hi, I'm Dushyant Rathore.
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A passionate programmer with a tenacious background in Software Development, Data Science, and Firmware Engineering.
About
As a Senior Software Engineer at Dell, I work with cutting-edge technologies and methodologies to deliver innovative solutions for the Infrastructure Solutions Group. I try to leverage my strong background in Software/Firmware Engineering, Data Science, and Cloud Computing to develop and optimize solutions for high-performance and reliable systems.
I have a Master's in Computer Science from Texas A&M University, where I gained valuable research and academic experience in various computer science domains and applications. I also have 3+ years of industrial experience and 2+ years of research experience in leading companies such as Micron Technology and Western Digital, where I contributed to multiple projects and publications. I am passionate about learning new technologies and approaches and strive to create impactful and meaningful solutions.
Experience
- Working with cutting-edge technologies to deliver innovative solutions for the Infrastructure Solutions Group.
- Developed firmware modules and improved code coverage by more than 20% with BullseyeCoverage.
- Migrated functionalities from the deprecated PIT framework to Python. Added support for 25+ features exercising commands on simulated and physical hardware over the NVMe bus.
- Implemented 5+ OEM-specific features as a part of the Open Compute Project (OCP) specifications, contributing to the development of industry standards.
- Refactored vendor-specific source code (5000+ LOC) and incorporated better coding standards to improve the codebase's maintainability.
- Devised unit tests in C++ using Google's Testing and Mocking Framework to improve code quality, running automatically during feature commits and reducing execution time by ~10%.
- Achieved 100% coverage and validation of NVMe Host and Controller Telemetry Log Pages, ensuring the functionality and reliability of the module.
- Tools: Python, C++, Enterprise Storage, Shell Scripting, Linux, Git, CI/CD, NVM Express (NVMe), Jenkins, Bitbucket, JIRA, Confluence.
- Conducted an in-depth analysis of patent litigation in the United States, using data analysis techniques to identify trends and patterns.
- Formulated a framework for automatically syncing data from Contactually CRM to Google Contacts using Google People API, saving over 3 hours of manual effort in each iteration and improving data accuracy.
- Demonstrated strong analytical skills and attention to detail in working with data, ensuring accuracy and reliability. Collaborated effectively with team members and stakeholders to develop and execute projects, contributing to achieving organizational goals.
- Tools: Python, Data Science, Machine Learning, Numpy, Pandas, Scikit-learn, NLTK, Gensim, Scipy, Jupyter Notebook, Matplotlib, Seaborn, Excel, GCP, Colab.
- Worked in the Perception, Sensing, and Instrumentation (PSI) Lab with Dr. Ricardo Gutierrez-Osuna, contributing to research efforts in bioinformatics.
- Developed a diagnostic platform for detecting early-stage pancreatic ductal adenocarcinoma (PDAC) in higher-risk patient cohorts, using data analysis techniques to identify potential biomarkers.
- Focused on identifying an assay panel for early detection of exocrine pancreatic cancer, particularly in stages I & II when surgery is still an effective therapy.
- Achieved a peak accuracy of 75% with the developed framework, demonstrating the effectiveness of the diagnostic platform.
- Collaborated effectively with research team members to develop and execute the project, contributing to achieving the overarching research goals.
- Tools: Python, Data Science, Machine Learning, Deep Learning, BioinformaticsFlask, Scikit-learn, Pandas, Plotly, Matplotlib, Colab, Kaggle.
- Led a 4-member team to verify storage protocols for next-gen client-class Solid State Drives, ensuring product quality and performance for Western Digital Corporation.
- Actively participated in defining, developing, and analyzing new firmware features, contributing to functional and protocol development, execution, and validation of WD NVMe SN730, WD NVMe SN530, and WD Blue.
- Conducted an in-depth analysis of firmware bugs caught during validation and studied the feasibility of test cases that could replicate such scenarios during Firmware verification, leading to better and more efficient firmware development.
- Created an integration pipeline using Jenkins and Gerrit Code Review, which accomplished a ~10% improvement in code deployment time and facilitated smoother code review processes.
- Implemented Hyperparameter Tuning with an internal test prioritization tool (OctoSpider), resulting in a 15% improvement in performance for the client-class Solid State Drives.
- Created a visual framework extracting features from Google's Blockly to interact with and validate NVMe Devices.
- Verified customer escalated issues and served as the sole point of contact for Oakgate and DriveMaster, addressing issues and providing timely resolution.
- Published research papers in the WDC IDTC on topics such as A Pub-Sub protocol-based validation framework and Zoned Storage, contributing to industry-wide research and development in storage technology.
- Tools: C, C++, Python, Client Storage, Storage Security, NVM Express (NVMe), Machine Learning, Flask, Jenkins, Gerrit, DriveMaster, Oakgate, MQTT, Scikit-learn, NLTK, Gensim, CI/CD, Shell Scripting, Linux, Git, Blockchain.
- Coordinated with clients worldwide on freelance projects, long-term mentoring, and consulting related to Software Development, Data Science, and Machine Learning.
- Delivered successful solutions to 60+ clients worldwide, which resulted in a 5/5 aggregate rating.
- Maintained effective communication with clients throughout the project lifecycle to ensure timely delivery and quality output.
- Enhanced client satisfaction by addressing feedback and incorporating it into the project requirements.
- Profile - https://www.codementor.io/@dushyantbgs.
- Tools: Python, JavaScript, Flask, Django, Scikit-learn, Tensorflow, Keras, NLTK, Spacy, Gensim, Selenium, Spacy, MongoDB, AWS, MQTT, Raspberry Pi.
- Collaborated with Dr. Akshi Kumar in conducting research on Deep Learning and Language Technologies.
- Utilized Neural Word Embeddings and Feature Extraction techniques for Feature Engineering.
- Developed Deep Learning models using Keras and TensorFlow frameworks for Genre Classification.
- Achieved a peak precision and f-score of 79.6% and 84.09%, respectively, surpassing the baseline models.
- Conducted research in Software Defect Prediction with Genetic Algorithms under the guidance of Dr. Ruchika Malhotra.
- Applied Differential Evolution and Simulated Annealing as optimizers on various datasets from open-source JAVA systems to explore the tuning space.
- Analyzed the results obtained from the optimization process to identify the best algorithm and parameter settings for software defect prediction.
- Acquired experience conducting research, analyzing experimental results, and presenting findings at conferences.
- Tools: Python, Tensorflow, Keras, Scikit-learn, NLTK, Gensim, Pandas, Numpy, Matplotlib, Colab.
- Designed and implemented an end-to-end architecture for IoT data ingestion, storage, and analysis.
- Developed RESTful APIs using Flask and Django to enable data retrieval and management. Integrated MQTT protocol to ensure seamless data flow from sensors to the platform.
- Utilized AWS Lambda to reduce infrastructure costs and optimize the performance of the IoT platform. Configured and optimized AWS S3 and DynamoDB to efficiently store and manage large volumes of IoT data.
- Implemented real-time data streaming using AWS Kinesis and explored its potential for machine learning and predictive analytics.
- Collaborated with front-end developers to ensure seamless integration of the backend with the web application.
- Tools: Python, Flask, Django, MQTT, AWS Lambda, AWS S3, AWS DynamoDB, AWS Kinesis, JavaScript, Scikit-learn.
- Worked with the Client Storage Solutions team at the SanDisk India Device Design Center.
- Developed test plans, test cases and executed test scenarios for validating OPAL and other security-related features of Solid-State Drives.
- Developed a tool using Python that automated the test process and reduced the execution time by 10%-15%.
- Tools: Python, DriveMaster, TCG, OPAL.
- Spearheaded the development of the Leave Management Platform, from requirements gathering to deployment, ensuring seamless tracking of employee leave requests, approvals, and management, improving operational efficiency by 25%.
- Worked with HTML, CSS, JavaScript, and jQuery to design and develop a user-friendly interface for the Leave Management Platform, enhancing the user experience. Employed Bootstrap to develop a responsive design for the web platform, optimizing the platform for various screen sizes and devices.
- Utilized PHP to create server-side scripts for processing data and seamless communication with the MySQL database.
- Leveraged Python and Scikit-learn to develop a machine learning model that predicts stock price movements using daily news, providing valuable insights for stock traders.
- Tools: Python, Scikit-learn, HTML, CSS, Jquery, Bootstrap, PHP, JavaScript.
Projects
![Bone Age Predictor](/assets/img/projects/bone_age_predictor.png)
A bone age prediction system using Convolutional Neural Networks
- A tool to correctly identify the age of a child from an X-ray image of the hand.
- Used Deep Convolutional Neural Networks like AlexNet, VGG16, VGG19, and ResNet along with image segmentation techniques.
- The best Mean Absolute Error achieved was 11 months.
- Tools : Python, Image Processing, Tensorflow
![quiz app](/assets/img/projects/genre_classification_system.png)
A Genre Classification System for Spotify songs
![Screenshot of web app](/assets/img/projects/software_defect_prediction_system.png)
Parameter Tuning on Software Defect Prediction using Differential Evolution & Simulated Annealing
- Developed Differential Evolution and Simulated Annealing as optimizers using different datasets from open-source JAVA systems to explore the tuning space.
- Tuning improved the performance in the majority of cases. It was also found that not all optimization algorithms used for tuning produced the same results.
- Tools : Python, Scikit-learn, Pandas, Numpy
![Screenshot of web app](/assets/img/projects/desktop_notification_tool.png)
Developed Desktop Notification tools for Linux, Windows and MacOS
- Crypto Notifier (A tool for the latest cryptocurrency rates)
- Weather Notifier (A tool for current weather based on the user's location)
- DTU RM Notifier (A tool for DTU's Resume Manager)
- Cricket Score Notifier (A tool for the latest cricket scores from around the world)
- Tools : Python, PyPI
![Screenshot of web app](/assets/img/projects/location_recommender_system.png)
A location based recommendation system on the FourSquare dataset
- Implemented a clustering-based recommendation model on the FourSquare dataset.
- Used RBF NN, SVM, and PNN in order to predict interesting locations to a user according to the user’s preferences and his/her social connections. ADA Boost algorithm was used to enhance the prediction results.
- Tools : Python, Scikit-learn, Pandas, Numpy
Publications and Reports
[1] Zoned Namespaces based storage for Blockchain - Western Digital Innovation Bazaar 2019 , Milpitas, United States
[2] MQTT protocol based Logging System - Western Digital Innovation Bazaar 2019 , Milpitas, United States
Skills
Languages
![](/assets/img/skills/languages/python.png)
Python
![](/assets/img/skills/languages/c.png)
C/C++
![](/assets/img/skills/languages/javascript.png)
JavaScript
![](/assets/img/skills/languages/html.jpg)
HTML
![](/assets/img/skills/languages/css.jpg)
CSS
![](/assets/img/skills/languages/php.png)
PHP
![](/assets/img/skills/languages/sql.png)
SQL
![](/assets/img/skills/languages/shell.png)
Shell Scripting
Frameworks, Tools, and Libraries
![](/assets/img/skills/tools/django.png)
Django
![](/assets/img/skills/tools/flask.png)
Flask
![](/assets/img/skills/tools/bootstrap.png)
Bootstrap
![](/assets/img/skills/tools/tensorflow.png)
Tensorflow
![](/assets/img/skills/tools/keras.png)
Keras
![](/assets/img/skills/tools/pytorch.png)
PyTorch
![](/assets/img/skills/tools/nltk.png)
NLTK
![](/assets/img/skills/tools/gensim.png)
Gensim
![](/assets/img/skills/tools/scikit.png)
Scikit-learn
![](/assets/img/skills/tools/pandas.jpg)
Pandas
![](/assets/img/skills/tools/numpy.png)
Numpy
![](/assets/img/skills/tools/matplotlib.jpg)
Matplotlib
![](/assets/img/skills/tools/plotly.png)
Plotly
![](/assets/img/skills/tools/mysql.jpg)
MySQL
![](/assets/img/skills/tools/mongo.png)
MongoDB
![](/assets/img/skills/tools/jenkins.png)
Jenkins
![](/assets/img/skills/tools/git.png)
Git
![](/assets/img/skills/tools/mqtt.png)
MQTT
Cloud Computing and Orchestration
![](/assets/img/skills/cloud/aws.png)
AWS
![](/assets/img/skills/cloud/heroku.png)
Heroku
![](/assets/img/skills/cloud/docker.png)
Docker
![](/assets/img/skills/cloud/kubernetes.png)
Kubernetes
Education
College Station, Texas, USA
Degree: Master of Computer Science
GPA: 4/4
- Analysis of Algorithms
- Software Engineering
- Parallel Computing
- Machine Learning
- Data Mining & Analysis
- Distributed Systems & Cloud Computing
- Cybersecurity Risk
- Data Analytics for Cybersecurity
- Directed Studies
- Information Storage and Retrieval
Relevant Courseworks:
Delhi Technological University
New Delhi, India
Degree: Bachelor of Technology in Software Engineering
GPA: 9.26/10
- Data Structures
- Object Oriented Programming
- Algorithm Design & Analysis
- Database Management Systems
- Operating Systems Design
- Web Technology
- Software Engineering & Validation
- Artificial Intelligence
Relevant Courseworks: