AI Engineer · Machine Learning Engineer · Computer Vision Researcher · MSc Advanced Data Science & AI — University of Liverpool (2025–26)

I build intelligent systems that bridge cutting-edge AI research and real-world applications. My experience spans Computer Vision, Deep Learning, Healthcare AI, Edge AI, Federated Learning, Explainable AI, and Multi-Agent Reinforcement Learning.

• Computer Vision & Deep Learning
• Artificial Intelligence for Healthcare
• Explainable AI (XAI)
• Disease Surveillance & Monitoring Systems
• Edge AI & TinyML
• Federated Learning
• Multi-Agent Reinforcement Learning
• Bio-inspired Optimization
• Intelligent Autonomous Systems

Python • SQL • R • C++ • Java

PyTorch • TensorFlow • Keras • Scikit-Learn • XGBoost • LightGBM

OpenCV • YOLOv5 • YOLOv8 • YOLOv9 • Detectron2 • EfficientNet

Pandas • NumPy • Matplotlib • Seaborn • Jupyter Notebook

Google Cloud Platform (GCP) • BigQuery • Cloud Storage • Vertex AI

Docker • Git • GitHub Actions • Linux • TensorFlow Lite • ONNX

LaTeX • Scientific Writing • Statistical Analysis • Explainable AI

MSc Dissertation | University of Liverpool

Developing AI-driven approaches for mosquito surveillance and monitoring using Computer Vision, Deep Learning, and Explainable AI techniques. The project focuses on improving mosquito detection, classification, and disease-risk assessment to support public health interventions and vector-control strategies.

Biomedical Research International

• Stack Regressor-based framework for drug discovery applications.
• DOI: https://doi.org/10.2174/0115701638405489251006073137

IET CVIoT 2024

• Novel underwater image enhancement and dehazing framework.
• DOI: https://doi.org/10.1049/icp.2024.4411

Springer CVIP 2024

• Comparative analysis of state-of-the-art object detection models in underwater environments.
• DOI: https://doi.org/10.1007/978-3-031-93691-3_25

IEEE ICERCS 2024

• AI-assisted medical image analysis for fracture detection.
• DOI: https://doi.org/10.1109/ICERCS63125.2024.10894779

• Vision Transformers (ViTs)
• Foundation Models
• Large Language Models (LLMs)
• Multimodal AI Systems
• Advanced Computer Vision Architectures
• AI for Public Health

• AI-driven Mosquito Surveillance and Disease Monitoring
• Swarm-Based Multi-Agent Reinforcement Learning for Search and Rescue
• Federated Learning on Edge Devices
• Underwater Object Detection using YOLO Architectures
• AquaVision Underwater Image Enhancement System
• Medical Image Analysis for Bone Fracture Diagnosis
• Edge AI Robotics using YOLOv8 + TensorFlow Lite

• LinkedIn: https://www.linkedin.com/in/spoorthi-jolakula-suresh-646b3a226
• GitHub: https://github.com/Spoorthi3011

Open to opportunities as:

• Computer Vision Engineer
• Machine Learning Engineer
• AI Engineer
• Applied AI Engineer
• Research Engineer

Interested in roles involving Computer Vision, Deep Learning, Healthcare AI, Edge AI, Intelligent Systems, and Applied Machine Learning across the United Kingdom.

“Using AI to build intelligent systems that create real-world impact through research, innovation, and deployment.”