AI Engineer with less than a year in IoT and disaster management using Python.
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Assessing your cultural and operational fit
An aspiring Computer Science and Engineering graduate with a strong foundation in Python, AI/ML, IoT, and data visualization. Demonstrated ability to develop predictive models, real-time monitoring systems, and contribute to projects focused on workplace safety and smart solutions. Recognized with certifications and publications for academic achievements.
Presidency University
Bachelor of Technology · Computer Science and Engineering
N/A – June 30, 2025
St. Anne's PU College
12th Grade
N/A – May 31, 2021
VIDYANIKETHAN English School
SSLC
N/A – May 31, 2019
AI-ML Based Model for Predicting Agri-Horticultural Commodities.
June 19, 2026 – Present
Aim: Predict Agri-horticultural commodity prices using AI/ML for better decision-making. Learning Outcome: • Built predictive ML models using Python, R, SQL, and Scikit-learn. • Analyzed historical, seasonal, and market data for forecasting.
Proactive Disaster Management for Fire Hazards.
June 19, 2026 – Present
Aim: Strengthen workplace safety through proactive fire-risk management and training. Learning Outcome: • Enhanced workplace safety through proactive fire-risk assessment and training. • Worked with fire-alarm panels, detectors, emergency lighting, and inspection tools.
Women Safety Patrolling Robot using Raspberry Pi.
June 19, 2026 – Present
Aim: Ensure women's safety using a Raspberry Pi-based robot with real-time monitoring and emergency alerts. Learning Outcome: • Built a real-time monitoring and emergency alert robot using Raspberry Pi and IoT. • Implemented sensors, camera, motor driver, and alert system integration.
Python Full Stack Certification.
Unknown
June 1, 2026 – Present
Published in IJSREM (May 2025).
IJSREM
May 1, 2025 – Present
Presented at NCAET-2025.
NCAET
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic projects show a diverse range of interests, from agricultural prediction to women's safety and disaster management. This breadth suggests an open-minded approach to problem-solving and a willingness to apply technical skills to various domains. However, the projects are all academic and lack real-world, collaborative team experience, which is crucial for cultural fit in a professional setting. The target role is 'AI Engineer', and while there's a relevant project, the overall portfolio is still nascent and heavily academic, which might require significant mentorship to align with industry practices.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to define aims, outline learning outcomes, and list technologies used, suggesting a structured approach to problem-solving. The 'Proactive Disaster Management' project also hints at an awareness of safety and operational processes. However, without direct psychometric test results or interview data, a comprehensive assessment of soft skills like teamwork, stress handling, or adaptability is not possible.