Welcome Julia Wiedmann – Machine Learning Engineer (Research)

 

Hi there! My name is Julia and I am a Machine Learning Research Engineer at Diffbot.

Born and raised in Vienna, Austria, I moved to London to study Business. While I enjoyed my degree, I realized I was much more interested in technology, so I taught myself enough coding and math to qualify for a Masters degree in Computer Science at University College London (UCL). I recently finished my PhD at the University of Oxford, primarily developing new methods for machine learning-based web data extraction which can extract data from new pages at scale and without site-level supervision. My research interests widely overlap with Diffbot’s work, so I interned here last summer building the EventsAPI. The EventsAPI is a new addition to the Automatic API’s, which automatically extracts events from the open web. This allows events to be added to the Diffbot Knowledge Graph and customers to use the API directly. Now as an excited full timer, I am focusing on improving and expanding the Automatic API extraction methods.

In my free time I love all sorts of sports, such as cycling (mostly indoors, well, because English weather), skiing (Austrian slopes are the best but I might be slightly biased), hiking and running. I love spending time with my friends and family and I am a big fan of cooking, baking (then eating it all), and crime novels.

I look forward to more adventures at Diffbot!

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Welcome Paramita Mirza – Machine Learning Engineer Intern

 

Hello there! I’m Paramita (sounds similar to ‘parameter’) and I’m excited to be part of the Relation Extraction research team at Diffbot.

I received my PhD degree from the University of Trento/FBK-ICT in spring 2016. Under the supervision of Sara Tonelli, my PhD research focused on extracting temporal and causal relations between events from natural language texts, as part of the NewsReader project. I then joined Gerhard Weikum‘s group at Max Planck Institute for Informatics, where YAGO (Yet Another Great Ontology) Knowledge Base was developed, as a Postdoc. My research interests have always been revolved around Information Extraction and Machine Learning approach for it, making sense of unstructured text and building structured knowledge out of it. 

I learned more about Diffbot when I attended ISWC’18 in Monterey, and found out that they’re on their steadfastly way on building a gigantic knowledge graph out of the whole web. I got hooked and decided to temporarily escape rainy Germany to sunny California. Here at Diffbot, I’ll be working on extracting temporal qualifiers for facts extracted to build Diffbot Knowledge Graph, making sure that we can differentiate fresh facts from the historical ones. I would love to hear your ideas and suggestions on how to make that happen!

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