Swastik-Swarup-Dash

Machine Learning

https://talent.gravityer.com/swastik-swarup-dash

Machine Learning | Cloud Computing | Docker | K8s

ADP

Key Strengths

Demonstrated interest in Machine Learning and AI through multiple personal projects (Q-A_ChatBot, WebLLM, SkimLit-PubMed-RCT-200, Food-Vision, Predictive-Modelling, Blog_agent).
Experience with Python, a core language for Machine Learning.
Exposure to various ML/AI concepts including LLMs, NLP, Computer Vision, and Time Series Forecasting.
Initiative in exploring different technologies and frameworks (Flask, Groq Cloud API, Google GenAI Models).

Cultural & Operational Fit

Cultural Fit Analysis

The candidate shows a strong drive for personal projects, indicating self-motivation and a passion for learning. The diversity of projects, from web applications to CLI tools and various ML domains, suggests adaptability and a broad interest in technology. However, the lack of team-based projects or contributions makes it difficult to assess collaboration and cultural fit within a team environment.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insights.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

GODEX

May 30, 2026 – Present

A Go based CLI

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Blog_agent

May 1, 2026 – Present

Blog_agent — GitHub repository

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Predictive-Modelling

March 9, 2026 – Present

Time series forecasting system for real-time XAU/USD (gold) price prediction.

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Spring

February 6, 2026 – Present

Spring-Starters

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Py_FlowCheck

January 6, 2026 – Present

py-flowcheck provides runtime validation for Python applications with minimal overhead. Add 1-2 decorators to your functions and get immediate contract checks in dev/staging, with configurable sampling in production.

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WebLLM

March 31, 2025 – May 23, 2025

A Flask-based web app leveraging Groq Cloud API for fast LLM inference" This repository contains a Flask web application that integrates with Groq's cloud API to provide a user-friendly interface for interacting with large language models (LLMs).

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BodyLink-The-Digital-Twin-Human-Body

October 20, 2024 – November 14, 2024

The purpose of this study is to develop a digital twin of the human body that utilizes basic sensors to visualize the status of various organs in real-time. The research aims to address the problem of providing a continuous, non-invasive, and cost-effective method for monitoring the health status of individuals.

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Q-A_ChatBot

August 22, 2024 – February 10, 2025

A Q&A Chatbot that answers all your Queries using Goggle Genai Models

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SkimLit-PubMed-RCT-200

June 21, 2024 – June 21, 2024

A Natural Language Processing Model used for Easy Reading through The Medical Paper

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Food-Vision

June 5, 2024 – September 30, 2025

A Deep Leaning project using Computer Vision and Transfer-Leaning

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Key Strengths

Demonstrated interest in Machine Learning and AI through multiple personal projects (Q-A_ChatBot, WebLLM, SkimLit-PubMed-RCT-200, Food-Vision, Predictive-Modelling, Blog_agent).
Experience with Python, a core language for Machine Learning.
Exposure to various ML/AI concepts including LLMs, NLP, Computer Vision, and Time Series Forecasting.
Initiative in exploring different technologies and frameworks (Flask, Groq Cloud API, Google GenAI Models).

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insights.

Swastik-Swarup-Dash

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit