Ayush K.

Key Skills

Software

Don't disclose

OpenCV AI Kit (OAK)

Top Subject Matter

Logistics and operations analytics

Computer vision / emotion recognition

Healthcare analytics / drug classification

Top Data Types

Text

Computer Code Programming

Top Task Types

Data Collection

Emotion Recognition

Classification

Freelancer Overview

Junior Data Analyst (Internship) — Tata Tubes (data analysis involving movement pattern insights). Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose and OpenCV AI Kit (OAK). Education includes Bachelor of Technology, KIIT University (2025) and Higher Secondary Certificate, Andhra Association English School (2021). AI-training focus includes data types such as Text, Computer Code, and Programming and labeling workflows including Data Collection, Emotion Recognition, and Classification.

Labeling Experience

Project: Face Emotion Recognition — TensorFlow/Keras (real-time emotion recognition)

OpenCV AI Kit (OAK)Emotion Recognition

Built a real-time emotion detection system using TensorFlow/Keras, which required preparing and working with labeled training examples for facial emotion recognition. Optimized preprocessing and model design to reduce processing time while maintaining model performance. Applied machine learning workflows to develop an emotion recognition pipeline suitable for inference. • Developed an emotion detection model with TensorFlow/Keras. • Performed data preprocessing to support training/inference. • Optimized model and pipeline for faster execution. • Implemented a real-time detection system.

2024 - 2024

Project: Drug Classification Model — supervised classification workflow (labeled data implied)

Don't discloseClassification

Developed a drug classification model by applying multiple supervised learning algorithms, which implies use of labeled datasets for training and evaluation. Implemented model selection and hyperparameter optimization using GridSearch CV to improve prediction accuracy. Compared classifier approaches (KNN, Random Forest, Logistic Regression, Naive Bayes) for healthcare-oriented classification. • Trained and evaluated classification models on labeled drug data. • Used GridSearch CV for optimization. • Compared multiple supervised learning algorithms. • Focused on improving healthcare prediction accuracy.

2023 - 2023

Junior Data Analyst (Internship) — Tata Tubes (data analysis involving movement pattern insights)

Don't discloseTextData Collection

Analyzed truck and trailer movement patterns to identify operational bottlenecks and inefficiencies in logistics using available datasets. Translated observations from movement behavior into actionable insights to support improved decision-making. Supported data-driven optimization by working with structured records and performance indicators. • Worked on transportation/logistics movement data. • Identified bottlenecks from pattern analysis. • Informed optimization of resource allocation. • Focused on improving operational efficiency.

2023 - 2023

Education

Work History