In my role as an IT Support Specialist, I am committed to providing comprehensive technical assistance to students, staff, and alumni. My responsibilities include:- Troubleshooting and resolving IT issues efficiently to ensure seamless user experiences.- Collaborating with various teams to escalate and address complex problems promptly.- Ensuring immediate resolution of critical issues to minimize disruptions.- Providing guidance and support for a wide range of IT-related concerns, from software and hardware troubleshooting to network connectivity and account management.- Maintaining a high level of customer service by addressing inquiries and concerns with patience and expertise.

As the Assistant Manager at the Learner's Health and Wellness Center, I am dedicated to ensuring an exceptional experience for all patrons by overseeing superior customer service and meticulous facility management. My role involves:- Leading a dynamic team to provide top-notch service and support to our diverse clientele.- Implementing and maintaining high standards for facility cleanliness, safety, and functionality.- Addressing and resolving customer inquiries and concerns promptly and effectively.- Developing and executing strategies to enhance customer satisfaction and facility usage.

- Leveraged advanced machine learning techniques like cosine similarity, clustering, and personalization algorithms to enhance video recommendations and user engagement.- Developed and deployed a content ingestion pipeline using AWS Lambda, SQS, and S3, significantly improving operational efficiency. Integrated MongoDB for managing vast video metadata, enabling efficient querying, data analysis, and actionable insights. Utilized AWS CloudWatch to monitor pipeline performance and health.- Collaborated with multidisciplinary teams to upgrade and implement personalized feed suggestions, resulting in a markedly improved user experience and increased user retention.

Worked on a Solar Forecasting Project. Used different models like Random Forest, AdaBoost, XGBoost, and DeepLearning. Random Forest Regressor worked best to deliver accurate statistical data, had to predict the solar energy produced in a specific amount of time. Worked with a visualization tool i.e Plolty, Dash.

Worked on Ariel-Cactus Identification. Developed ML algorithms to analyze huge volumes of data to make predictions. Designed machine learning systems and self-running artificial intelligence (AI) software to automatepredictive Identification models.

Trained under-14 aged kids, gave them a proper understanding about the game and rules.