Natural Language Processing and Graph Analytics

Recap Summary

Our first London Data Science Community event since lockdown so a great turn out and it was great to be back out meeting peers again face to face from across the data science sector.

We were fortunate enough to have presentations from 3 outstanding speakers on NLP and Graph Analytics.

Anil Bandhakavi spoke about the challenges in building Logically’s AI team and how they went about it.

Dominik Tomicevic, spoke about his organisation MemGraph and the advantages over Neo4j and some of the use cases 

Roxana Danger gave a fascinating talk about Privacy risks in NLP and potential solutions


Our 3 main takeaways from the event were as follows:

  1) Hire in preparation of your projects so your work isn’t delayed, and hire the skills you will be needing.

  2) Graph streaming is being used successfully for social networks, recommendation engines, fraud detection, supply chain and even chemical plants.

  3) Data cleansing and preparation is key to protect your data privacy


Speaker Bios:

Dominik Tomicevic

Founder, Memgraph

Dominik received his bachelor's degree in computer science from the University of Zagreb. In 2011, he was selected as one of the four people in the world to receive the Microsoft Imagine Cup Grant, awarded by Bill Gates personally. In 2016, he founded Memgraph, a venture-backed graph database company focusing on high-performance real-time connected data processing. Memgraph is backed by M12 (Microsoft's Venture Fund), In-Q-Tel, Heavybit, and other top-tier investors and entrepreneurs. In 2017, Dominik was named, by Forbes, as one of the top 10 Technology CEOs to watch.

Roxana Danger

Dr Roxana Danger is an experienced researcher in the fields of Natural Language Processing, Data Mining and Knowledge Representation. She completed her PhD on "Extraction and analysis of information from the Semantic Web viewpoint" and worked as a postdoctoral researcher at Universidad Politecnica de Valencia and Imperial College London. She has participated with key roles in multidisciplinary European and national projects, and published more than 30 international research papers. After moving to the private sector, she has worked as a Senior Data Scientist in and 10x Banking, and is currently working at, a company leading the development of Responsible AI technologies and tools to solve the data challenge for regulated industries. She is interested in promotion of statistical and data understanding in education and for the general public. Her main current research interests are data ethics, semantics and private AI.

Anil Bandhakavi

Head of Data Science – Logically

Anil heads the data science and machine learning operations at Logically with up-to 10 years of experience in the field of Artificial intelligence including a Ph.D. in NLP. He joined Logically in 2018 to lead the development of effective AI solutions that enable the tools and products of Logically. He believes strongly in extended (artificial + human) intelligence to create impactful and interpretable solutions to societal problems.

Anil will be talking about Logically’s requirements and approach to building a diverse AI team. Covering the recruitment challenges Logically faced and what the solutions the team have built so far to combat misinformation, disinformation etc


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