GRE
333 / 340
KARLOSH YADAV
Computer Science Engineer focused on Machine Learning and Scalable Systems
M.Tech student (CSE) at Indian Institute of Science, Bangalore (2025–2027), with a BE in CSE from Visvesvaraya Technological University (2020–2024). I build reliable ML systems, design secure software, and enjoy solving practical problems with data-driven engineering.
About
I am a computer science engineer focused on machine learning, data-centric systems, and dependable software engineering. My recent work includes benchmarking deep learning models for brain tumor classification, building ensemble-based heart disease prediction, and implementing core ML algorithms from scratch.
Education
Master of Technology, Computer Science and Engineering
Indian Institute of Science, Bangalore | CGPA: 7.0/10
Aug 2025 – Jun 2027
Bachelor of Engineering, Computer Science and Engineering
Visvesvaraya Technological University | CGPA: 8.75/10
Aug 2020 – Jun 2024
Technical Skills
C++PythonMySQLMachine LearningData Structures and AlgorithmsSoftware Development Life CycleDatabase ManagementObject-Oriented ProgrammingSystem Design (Basics)
Profile Snapshot
Languages
English, Hindi, Maithili, Nepali
Focus Areas
Machine Learning, Databases, OOP, DSA
Projects
Benchmarking Deep Learning Models for Brain Tumor Classification: YOLOv8, ResNet50, and MobileNetV3
Aug 2025 – Dec 2025
- •Conducted comparative analysis of MRI-based brain tumor classification across YOLOv8, ResNet50, and MobileNetV3.
- •Performed hyperparameter optimization and ablation studies for model accuracy and generalization.
- •Applied K-fold cross-validation for statistical reliability and reproducibility.
- •Built TensorFlow training/evaluation pipeline for stable and fair model benchmarking.
TensorFlowDeep LearningYOLOv8ResNet50MobileNetV3K-Fold CV
Heart Disease Prediction System (Ensemble Learning)
Sep 2023 – May 2024
- •Built a Soft Voting ensemble using Logistic Regression, Random Forest, and XGBoost.
- •Handled preprocessing: missing values, encoding, scaling, and train-test splitting.
- •Addressed class imbalance using SMOTE and optimized with K-fold CV + GridSearchCV.
PythonScikit-learnXGBoostSMOTEGridSearchCV
Machine Learning Algorithms from Scratch
- •Implemented Linear Regression, Logistic Regression, Decision Tree, and Random Forest using NumPy.
- •Implemented MSE, Binary Cross-Entropy, Gradient Descent, and Information Gain mathematically from scratch.
- •Applied bootstrap sampling and feature randomization for stronger generalization in Random Forest.
NumPyMachine LearningAlgorithmsOptimization
Vehicle Care Management System
- •Designed normalized relational schema with ACID-compliant transactions and concurrency control.
- •Implemented JWT-based stateless auth, RBAC, and bcrypt-secured password management.
- •Configured secure environment variables and CORS policies for production safety.
Database DesignJWTRBACbcryptCORS
Certifications & Activities
Certifications
Graduate Record Examination
ETS
Score: 333/340.
C++ for Everyone
University of California
2021
Completed foundational C++ programming coursework.
Machine Learning for All
University of London
2023
Completed introductory machine learning course with practical applications.
Extra-Curricular Activities
President
International Student Club (ISC)
04/2023 – 04/2024
Led club initiatives and coordinated student activities.
Secretary
Soft Research Computing Society
04/2022 – 04/2023
Managed communications and organized society events.
Chess
Inter-Institution Level
Active competitive player.
Cricket
College and District Cricket Team
Represented teams in competitive matches.
Contact
Email: karloshyadav@iisc.ac.in
LinkedIn: linkedin.com/in/karloshyadav