
Research Associate
Oct 2024 - Jan 2025
University of Birmingham
Oct 2024 - Jan 2025





Hey 👋🏼 I am a Software / Machine Learning Engineer currently based in the United Kingdom. I completed my undergraduate degree in Computer Science in India and later earned my Master's degree in Computer Science with Human-Computer Interaction (HCI) at the University of Birmingham in the United Kingdom. I’m passionate about leveraging AI and machine learning to solve complex problems and crafting elegant code to build user-focused solutions. I’m also an active contributor to open-source projects in AI and HCI, collaborating with global communities to create impactful tools. Currently, I’m seeking exciting opportunities to apply my expertise in AI, machine learning, and software engineering to drive innovative solutions.
Oct 2024 - Jan 2025
University of Birmingham
Oct 2024 - Jan 2025
Jun 2024 - Aug 2024
Our Time HQ
Jun 2024 - Aug 2024
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Developed a brain-computer interface to decode speech sounds from EEG signals, training a model to recognise eight distinct speech phonemes with a 92.5% F1-score on synthetic data, while creating an interactive app that displayed topographic scalp maps and used visualisation techniques to show how the model interprets brain activity, making it easier for researchers to analyse results in real-time and support cognitive studies, with added reliability through cross-validation, hyperparameter tuning, and data augmentation.
View on GitHub
Built an AI-powered tool to help researchers tackle academic papers more efficiently, letting them upload PDFs to run semantic searches, extract key entities like concepts, authors, and references, and even answer specific questions about the content using a retrieval-augmented generation pipeline, while also creating knowledge graphs to map out relationships between studies, summarize papers, and highlight connections, all wrapped in a straightforward interface that made these insights easy for nontechnical users to dive into, boosting engagement by 45% among 10 beta testers.
View on GitHub
Developed a real-time facial emotion recognition app that analyzes webcam video to detect emotions and pairs them with custom emojis, training a convolutional neural network on the FER2013 dataset to classify seven emotions—angry, disgust, fear, happy, neutral, sad, and surprise—and designing an interactive GUI to show the live video feed alongside matching emojis, highlighting skills in deep learning, computer vision, and interface development.
View on GitHub
+44 7741918549
tirthkanani18@gmail.com
London, United Kingdom
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