💻 AI-ML Enthusiast & Data Scientist
🎓 B.Tech @ NIT Rourkela
🚀 Focused on intelligent systems, data-driven solutions, and algorithm optimization

const Suchismita = {
  languages: ["C++", "Python", "Java", "C"],
  ai_and_data: ["TensorFlow", "PyTorch", "Keras", "Scikit-learn", "Pandas"],
  web_and_db: ["FastAPI", "MySQL", "React", "Django"],
  interests: ["Deep Learning", "Competitive Programming", "Data Science"]
}

• Developed an intelligent virtual assistant utilizing Python to automate daily workflows, schedule tasks, and process complex user queries in real-time.
• Integrated modern AI and Natural Language Processing (NLP) libraries to engineer a responsive, hands-free voice interaction interface.
• Architected a modular backend system to handle asynchronous task execution, streamlining routine management and reducing manual operational effort.

• Engineered a robust machine learning pipeline utilizing XGBoost and Neural Networks to predict traffic accident severity based on environmental and situational features.
• Implemented SMOTE (Synthetic Minority Over-sampling Technique) and class weighting strategies to successfully resolve severe dataset imbalance and optimize model reliability.
• Extracted actionable data science insights from complex situational datasets to support data-driven decision-making for urban planning and proactive road safety initiatives.

• Developed a machine learning model to predict the severity of traffic accidents based on various environmental and situational data points.
• Aimed at leveraging data science to provide actionable insights for road safety and urban planning improvements.

🔗 https://github.com/suchismitab0511/Traffic-Accident-Severity-Prediction

• 🌱 Active member of AASRA, collaborating on community outreach to provide educational guidance and support for young, bright minds.
• ♟️ Avid chess player, always appreciative of a game that challenges strategic and tactical thinking.
• 📊 Deeply interested in core Data Science concepts, particularly how predictive modeling and analytics can be applied to solve complex real-world challenges.