ML/AI Engineer

SHRUSHTI GUPTA

United States +1-617-***-**** *****************@*****.*** LinkedIn GitHub

EDUCATION

Master’s in Computer Science, George Mason University, Fairfax, Virginia GPA – 3.90/4.00 May 2024 Relevant courses: Analysis of Algorithms, Theory and Applications of Data Mining, Advanced Natural Language Processing. Bachelor’s in Computer Science Engineering, GITAM University, Visakhapatnam GPA – 4.00/4.00 April 2022 Relevant courses: Software Engineering, Data Mining and Data Warehousing, Artificial Intelligence, Machine Learning. EXPERIENCE

Resilience Inc. Fairfax, Virginia

AI Software Engineer August 2024 - Present

• Refined Android application powered by an audio-based emotion detection model by adding new features and conducting rigorous testing to ensure stability and performance.

• Led the troubleshooting and debugging, identifying and resolving key performance bottlenecks, resulting in a 30% improvement in app stability and responsiveness.

• Collaborated with the project manager and the customer experience team to improve app usability and incorporate customer feedback effectively, contributing to over 100 downloads on the Play Store. Resilience Inc. Fairfax, Virginia

Machine Learning Developer October 2023 - March 2024

• Optimized a Random Forest model for audio-based emotion detection through effective feature selection and hyperparameter tuning, increasing accuracy from 65% to 88%.

• Developed an Android application using Java, integrating the emotion detection model to recommend personalized meditation exercises based on the user’s current mood.

• Applied a continuous feedback loop to collect user data, leading to model retraining that improved accuracy by 15% and enhanced adaptability over time.

Microsoft Remote

Microsoft Azure Cloud and Security Intern - Microsoft Future Ready Talent Program October 2021 - March 2022

• Explored and applied concepts in Cloud Computing, Artificial Intelligence, and Cyber Security using Azure services and GitHub tools, contributing to solutions for pressing societal problems.

• Pioneered the development of a Predictive Model for Diabetes within Microsoft Machine Learning Studio (classic), utilizing the Azure Open Dataset. This model forecasts diabetes with 78.6% accuracy in patients based on intricate laboratory results, using a two-class averaged perceptron algorithm.

• Attracted over 800 views and 300 downloads upon publication in the Microsoft Azure AI Gallery. Verzeo Bengaluru, India

Machine Learning Intern July 2021 - August 2021

• Developed a predictive machine learning model using Python and Scikit-learn to analyze student performance based on quiz scores, course activity, and engagement levels.

• Designed a personalized recommendation system that analyzed students' weak subjects and suggested targeted materials.

• Partnered with the engineering team to integrate the model into the platform, delivering real-time recommendations that resulted in a 20% increase in student retention.

PROJECTS

Employee Recognition System (Oracle SQL, Tomcat, Android Studio) January 2024 – May 2024

• Built a full-stack project using the Model-View-Controller (MVC) architecture, with an Oracle database and server-side functionality implemented via Java Servlets and JSPs deployed on Apache Tomcat. Integrated an Android application with the backend through a RESTful API, enabling 24/7 real-time access to employee sales records and personal information. Learn To Adapt (Python) January 2023 - May 2023

• Successfully reproduced the results of the ACL 2022 paper "Learn to Adapt for Generalized Zero-Shot Text Classification." Led comprehensive experiments to evaluate the robustness of the Natural Language Processing (NLP) model, with findings indicating sensitivity to noisy dataset and approximately a 30% reduction in accuracy when exposed to multilingual data. Object Information Retrieval in Real-time (Python, Android Studio) August 2022 - December 2022

• Engineered an Android application to assist blind individuals with real-time object detection, achieving an 82% accuracy using a TensorFlow-trained model. Incorporated a client-side camera that captures live video, rapidly processes it into frames, performs precise object detection and position identification within 0.5 seconds, and delivers instant audio feedback. SKILLS

Languages: C, C++, Java, Python, SQL, Scratch. Cloud technologies: MS Azure, AWS, Docker, Jenkins, Kubernetes, Rancher. Web Development: HTML5, CSS, Bootstrap, JavaScript, TypeScript. Operating Systems: Windows, Linux, Unix, macOS. Tools: Eclipse, Android Studio, VS Code, Tomcat, Google Colab, MS Office. Database Technologies: MySQL, Oracle. Libraries: Pandas, Scikit-learn, MATLAB, TensorFlow, Pytorch, NumPy, Matplotlib. Methodologies: DevOps, Agile.

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