MRes Artificial Intelligence @ University of Wolverhampton (2025–2026)
AI Researcher | Machine Learning Engineer | Information Retrieval & Recommender Systems
Former Software Engineer @ UST Global (Analytics & Data Systems)
Developing AI systems that combine Machine Learning, NLP, and Information Retrieval to transform unstructured data into intelligent decision-support tools. My work focuses on semantic search, recommendation systems, predictive modelling, and explainable AI pipelines.
Tech Stack:
Python SQL PyTorch TensorFlow Scikit-learn Transformers spaCy
Random Forest XGBoost BM25 SBERT Flask APIs Azure
Power BI Power Apps Power Automate
📍 Wolverhampton, UK | Right to Work in the UK
⭐ Open to AI Engineer | Machine Learning Engineer | Data Analyst | Power Platform roles
My research explores how Artificial Intelligence can improve decision-making for students and course seekers. Current postgraduate course discovery systems rely heavily on keyword-based search and manual filtering, which often fail to capture the semantic relationship between a candidate’s experience and suitable programmes.
To address this gap, I develop Hybrid Information Retrieval–Machine Learning systems that analyse unstructured CVs and generate ranked course recommendations using semantic embeddings and ML ranking models.
The long-term goal is to build AI-powered decision-support systems that improve accessibility, transparency, and fairness in educational guidance.
- Dual retrieval architecture combining
BM25 sparse search+SBERT dense embeddings - Ensemble ranking models using
Random ForestandXGBoost - Semantic CV parsing pipelines generating structured candidate profiles
- Ranking evaluation framework using
nDCG@K,Precision@K, and rank correlation - Integration of CAMEL multi-agent reasoning framework to improve explainability in AI recommendations
University of Wolverhampton (2025 – Present)
Researching AI-driven recommendation systems and semantic information retrieval.
Key work:
- Developing Hybrid IR–ML recommendation systems for postgraduate course matching
- Designing transformer-based CV parsing pipelines
- Building ranking models using ensemble ML techniques
- Evaluating recommendation quality using IR ranking metrics
- Investigating multi-agent reasoning systems (CAMEL) for explainable AI decision support
UST Global (2022 – 2025)
Worked on enterprise analytics engineering and cloud-based reporting systems.
Key contributions:
- Designed semantic data models supporting 1M+ row datasets
- Reduced dataset refresh time from 2.5 hours → 35 minutes (70% improvement)
- Built REST API pipelines for external JSON data ingestion
- Implemented CI/CD deployment pipelines and monitoring workflows
- Developed enterprise analytics dashboards using Power BI + Azure
Technologies:
Power BI Power Apps Power Automate SQL Server Azure REST APIs
Multi-output ML system predicting risk type, probability, and mitigation strategy using Random Forest and Extra Trees.
NLP system matching candidate CVs with job descriptions using semantic similarity.
Predictive ML model identifying students at risk of academic failure.
Multi-agent AI system inspired by CAMEL architecture for automated resume evaluation.
Healthcare ML system predicting diabetes risk factors using classification models.
Random Forest XGBoost SVM Extra Trees
Deep Neural Networks CNNs Multi-output classification
Transformers BERT SBERT
BM25 Retrieval Semantic Search
CV Parsing Feature Extraction
PyTorch TensorFlow Scikit-learn spaCy Hugging Face Transformers
ETL Pipelines Feature Engineering
Cross Validation Model Evaluation
Flask APIs REST APIs CI/CD Pipelines
Microsoft Azure Power BI SQL Server
MRes Artificial Intelligence
University of Wolverhampton
Research Areas
Machine Learning • NLP • Information Retrieval • Recommender Systems
BTech Electrical & Electronics Engineering
Cochin University of Science and Technology
Final Project
Intelligent Shopping Trolley (IoT + Embedded Systems)
Hugging Face – Transformers & NLP
Kaggle – Machine Learning
Kaggle – Natural Language Processing
Google Cloud Ready Facilitator
LinkedIn
https://www.linkedin.com/in/gopika-sushama
GitHub
https://github.com/GOPIKA-SUSHAMA
Email
gvndgpk@gmail.com