4
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Data Scientist
United States
3 years of experience
INTEL AI Hackathon FIRST prize Winner! Published papers: 1. FIE 2023 IEEE conference, Texas, USA: EEG Spectral Analysis and Prediction for Inattention Detection in Academic Domain 2. AIMC 2023, Brighton, UK: Introductory Studies on Raga Multi-track Music Generation of Indian classical music using AI.
'FINGU' is an innovative, AI-powered personal finance assistant designed to revolutionize the way individuals manage their finances. Built upon state-of-the-art machine learning algorithms, 'FINGU' constantly learns from user interactions, financial behaviors, and market trends to provide highly personalized financial advice. By integrating real-time data analytics, 'FINGU' offers users insights into their spending habits, investment opportunities, and potential financial pitfalls. Furthermore, its interactive interface is designed for user-friendliness, ensuring that even those unfamiliar with financial jargon can make informed decisions. With its emphasis on data security, 'FINGU' employs end-to-end encryption to protect user information, ensuring confidentiality and trustworthiness. Beyond mere number crunching, 'FINGU' understands the nuances of individual financial goals, helping users strategize for both short-term and long-term objectives. In essence, 'FINGU' isn't just a toolβit's a comprehensive financial companion aimed at empowering users to achieve financial success.
Raga Music Generation Pipeline: RagaCraft Our project, RagaCraft, bridges the gap between raw human emotion and the timeless art of raga music using cutting-edge AI. Here's a deeper dive into the underlying process: Customer Interaction: Users interact with our platform, sharing their current emotions and contextual information. For example, "I am feeling romantic today. It is Valentine's Day. I'd like a song to suit the mood." JavaScript Selection: Our system, powered by JavaScript, scans the user's input to select an appropriate raga that resonates with the given emotion. OpenAI Integration: To add depth and specificity, RagaCraft sends a refined request to OpenAI: "Generate a text-to-music prompt for a single romantic raga. Include parameters such as tempo, scale, pitch, and rhythm to optimize the romantic mood. Define ideal values for these features." OpenAI's Response: The API, enriched with musical knowledge, replies with precise musical direction. For instance, "For a romantic setting, employ the Hindustani raga Kamboji. Utilize a medium-slow tempo, major scale, and a high pitch with low undertones. The rhythm should be gentle with a 4/4 signature. Dynamics can vary, with crescendos and decrescendos, ensuring a light texture and smooth timbre." Audiogen Transformation: The detailed prompt from OpenAI is fed into Audiogen, which processes it and crafts a song that encapsulates the user's emotions. Delivering the Experience: Our user interface then presents the generated raga song to the user, completing a journey from raw emotion to personalized musical expression. Through RagaCraft, we're redefining the way users experience and interact with traditional music forms in the age of AI.