Minas Sifakis

  • Machine Learning and
  • Acoustics

About Me


I am a physicist turned machine learning scientist. I have experience in time series forecasting, statistical modeling, unsupervised clustering, anomaly detection and natural language processing (NLP). I hold a degree in physics, an MSc in Computational Statistics and Machine Learning from UCL and an MSc in Sound and Vibration Studies from the University of Southampton.

I am currently a research associate at the University of Edinburgh, where I work on NLP and multilingual document matching and alignment at petabyte scale. Before that I was at the Alan Turing Institute, where I used a combination of pre-trained language models, transfer learning, search engine technologies (Elasticsearch) and a vector similarity engine (FAISS) to develop a state of the art system for large scale news article monitoring, fraud detection and question answering.

I have also worked in finance (Cisapline Ltd), developing algorithms for forecasting financial time series using neural network and Gaussian processes and in ML consulting (Machinable), developing ML-based transformation strategies for large corporates. Before my switch to machine learning I had worked for ten years in engineering acoustics, two years in academia (full-time lecturer) and four years in risk management.

Experience


Natural Language Processing

I am currently working on NLP. I have experience in natural language based information retrieval, document similarity and clustering, text extraction from pdf documents, etc.

Time Series Forecasting

I have worked in time series forecasting, using

signal processing methods, Neural Networks, SVMs,

Gaussian Processes and tree based methods.

Computer Vision

I am involved in the World Bank sponsored "Slum World" project,

where we use satelite imaginery to identify slums areas in cities.

Anomaly Detection, Density Estimation

I have experience working with Variational Autoencoders,

normalizaing flows and Bayesian models for anomaly detection,

probability density estimation, uncertainty quantification

and synthetic data generation.

Acoustics

I have 15 years experience in engineering acoustics,

noise and vibration control.

Coding

Python, Matlab, Tensroflow, Pytorch

GP-Flow, Elasticsearch/Kibana

Docker, Git, Bash, SLURM, AWS.

Other stuff

Publications, public speaking, etc.

Get In Touch


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