Projects — Denis Baldakov

AI Mental Health Assistant

An end-to-end machine-learning pipeline for mental-health diagnosis and treatment support: data cleaning and EDA, model training and evaluation (including a clinicalBERT-based text model), delivered with a continuous-integration workflow, a written report, and the demo above.

Data preparation, exploratory analysis and train/val/test splits over a clinical dataset
Diagnosis and medication/therapy-prediction models, including clinicalBERT for clinical text
Automated test pipeline via GitHub Actions

Code → Report →

Dissertation — Self-Hosted LLMs for Unit-Test Generation

My undergraduate dissertation: a multi-agent pipeline that generates unit tests for code, built to test whether small, self-hosted language models can rival a frontier model. A Programmer agent proposes a reference solution, a safety filter strips unsafe code, and a Tester agent writes the test suite — the same pipeline drives four quantised SLMs (Mistral-Small, DeepSeek-Coder, Llama-3.1, Nemotron-Mini) via LM Studio and Claude via the Anthropic SDK.

Benchmarked on HumanEval & MBPP with line coverage, mutation score and functional accuracy
Honest-by-default scoring: an empty-suite filter stops assertion-free tests scoring a trivial pass
Every run persisted as a JSON artefact; headline numbers come from a rescored 25-task evaluation

Code → Notebook →

More Projects

Deep Learning · Research

Deep Active Learning on CIFAR-10

Label-efficient image classification with a ResNet backbone, comparing selection strategies (TypiClust on supervised embeddings) and reporting accuracy vs. labeling budget.

PyTorchtorchvisionResNetActive Learning

Code Notebook

Computer Vision · Robotics

Object Detection Robot

ROS + LiDAR service robot that uses YOLO object detection to locate, collect and deliver items autonomously through a state-machine of navigation nodes.

PythonROSYOLOLiDAR

Code

Data Science

ML Feature Engineering

Feature engineering, exploratory data analysis and model comparison on tabular data, with reproducible evaluation notebooks.

Pythonpandasscikit-learnJupyter

Code Notebook

MLOps · Cloud

YOLOv5 + MLflow Microservices

Containerised MLOps platform: a YOLOv5 object-detection service with MLflow experiment tracking and MongoDB, orchestrated with Docker Compose and deployed to Kubernetes.

FastAPIYOLOv5MLflowDockerKubernetes

Code