Praneesh Sharma

At HiDevs, I embrace the dynamic nature of a startup, where roles remain fluid and I take on responsibilities across multiple domains. I collaborate closely with teams in product development, engineering, marketing, user growth, and brand management. I contribute by developing generative AI features, engineering prompts, testing models, and supporting outreach efforts. Working in a fast-paced, remote environment, I stay adaptable and take a hands-on approach to drive innovation and deliver AI solutions that meet user needs and business objectives.

Selected as one of 200 talents worldwide for this prestigious annual program. Engaged in deep learning around Bitcoin, the Lightning Network, and decentralized systems through expert talks, workshops, and collaborative projects. Analyzed and presented insights on Bitcoin and Web3. Worked with industry peers to explore real-world applications and the future of finance, while building both technical skills and strategic perspective.

During my internship at Celebal Technologies, I gained hands-on experience in various aspects of data science and software development. I honed my skills in Python programming, mastering both the basics and advanced concepts, including Object-Oriented Programming. Additionally, I developed efficient file handling and data manipulation techniques. I built and deployed web applications using Flask and Django, and utilized Pandas and Numpy for data manipulation and analysis. My work also included applying statistical methods and feature engineering techniques to prepare data for machine learning models. One of my key projects was 'Anomaly Detection in Network Traffic,' where I implemented machine learning algorithms to identify unusual patterns in network traffic data, enhancing network security and performance monitoring.

Completed the Developer Trailmix on Salesforce Trailhead, earning 13 super-badges. Gained hands-on experience with the Salesforce Platform, including proficiency in Apex, Approval Processes, Flow Elements, and Process Automation. This immersive learning journey enhanced my skills in Salesforce development and process automation, preparing me to tackle real-world challenges in the Salesforce ecosystem.

Made a Virtual Assistant integrated with ChatGPT3. Also has functionalities like finding weather and controlling lights through integration with IoT.

Worked on the various cloud services offered by AWS

Focused on Natural Language Processing (NLP) projects, with a specific emphasis on sentiment analysis of social media comments. Working collaboratively in a team of three, we conducted extensive research and authored four research papers on this topic for the 'Recent Advances in Natural Language Processing'23 conference. These papers were subsequently published in the ACL anthology. This experience significantly enriched my understanding of NLP methodologies, particularly in the context of sentiment analysis and social media data processing. It honed my research and analytical skills, allowing me to contribute effectively to academic discourse in the field of computational linguistics.

Interned at HPCL, contributing to the optimization of petroleum refinery operations. Developed predictive models for precise Caustic consumption using real-time data from diverse refinery units. Engineered an AI-enabled procurement web app for dynamic chemical demand forecasting. Acquired profound industrial knowledge, gaining insights into the intricate workings of oil refineries. Enhanced skills in predictive modeling, process optimization, and real-world application of data-driven solutions.

Got accustomed with Amazon SageMaker and ways to deploy various deep learning models on the AWS

Data Analysis: Performed exploratory data analysis and clustering on the IRIS dataset Machine Learning: Made a linear prediction model to predict the score based on number of hours of studies.

Successfully completed the training in Machine learning during Autumn session 2021-22.