Jagapathy Dhanushkar
Data ScienceAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Science with less than a year in Machine Learning & Deep Learning
Aspiring AI/ML Engineer with a strong foundation in machine learning, deep learning, and intelligent system design. Experienced in developing scalable predictive models, analyzing complex datasets, and implementing real-world AI solutions. Demonstrated leadership in technical projects with strong problem-solving and communication skills. Proactive, adaptable, and continuously learning—eager to contribute to innovative AI-driven technologies.
SLIIT (Sri Lanka Institute of Information Technology)
BSc (Hons) in Information Technology Specialising in Data Science · Data Science
August 1, 2023 – June 30, 2027
SLIIT (Sri Lanka Institute of Information Technology)
Higher National Diploma in Information Technology · Information Technology
August 1, 2023 – June 30, 2027
Highlands Central College, Hatton
GCE A/L (Physical Science) · Physical Science
June 1, 2019 – May 31, 2021
ESOFT Metro College - Hatton
Diploma in Information Technology and English (DiTec & DiE) · Information Technology and English
August 1, 2017 – June 30, 2018
Wildlife Animal Species Classifier
June 12, 2026 – Present
Developed a deep learning-based system to classify 90 wildlife animal species from images. Utilized EfficientNetB0 for feature extraction, optionally integrated YOLOv8 for object detection, and OpenCV for image preprocessing. Built a Streamlit app for real-time predictions with top-5 confidence scores and interactive visualization.
View ProjectMail Management Multi-Agent AI System
June 12, 2026 – Present
Developed an AI-powered email management system with multi-agent automation for organization, summarization, replies, and reminders. Integrated Gemini AI for intelligent categorization and context-aware responses, with a secure Streamlit dashboard for interactive email analytics.
View ProjectAI Resume Screening Application
June 12, 2026 – Present
Developed an NLP-based resume classification system using TF-IDF and KNN to predict 25 job roles. Built a Streamlit app for automated resume parsing, skill extraction, and real-time predictions with confidence scores.
View ProjectAir Quality Index (AQI) Prediction System
June 12, 2026 – Present
Developed a machine learning system to predict AQI categories using WAQI data, with preprocessing, model training, and evaluation. Built a Streamlit dashboard for predictions, pollutant analysis, probability visualization, and map-based insights.
View ProjectIBM Data Science Professional Certificate
IBM
June 1, 2026 – Present
Machine Learning Foundation Certificate
Duke University
June 1, 2026 – Present
IBM Applied Data Science Capstone
IBM
June 1, 2026 – Present
Participation in CodeRally 6.0
Unknown
June 1, 2026 – Present
AWS SimuLearn Series (2025) - Cloud Computing Essentials, Amazon S3, EC2, VPCs
AWS
January 1, 2025 – Present
Introduction to Azure Virtual Machines - Microsoft (2025)
Microsoft
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest in applying AI/ML to diverse real-world problems (wildlife classification, email management, resume screening, air quality prediction). This project diversity, coupled with certifications from IBM, Duke University, AWS, and Microsoft, indicates a proactive learning mindset and a broad technical curiosity. The participation in CodeRally also suggests an engagement with the broader tech community. These aspects align well with a culture that values continuous learning, innovation, and practical application of skills.
Soft Skills & Operational Fit
The candidate's resume highlights strong problem-solving and communication skills, and a proactive, adaptable, and continuously learning attitude. These traits suggest a good operational fit for dynamic project environments and a willingness to grow within a team. However, without direct interview data or peer feedback, these are self-reported and require validation.