I currently head up AI & Big Data Platform groups at Meltwater. We do interesting work in the areas of Fully automated unsupervised web Data Extraction, Natural Language Processing, Rule mining and Link prediction on large probabilistic knowledge graphs, Scaling Elastic Search to handle petabytes of data.
We are actively hiring and If any of these sound interesting to you, drop me a note at adityaj at cs dot stanford dot edu
Previously I co-founded Predict Effect, an audience acquisition and Monetization platform. I was a founding member of the Cloud Solutions team at Netflix where I worked on Simian Army (Chaos Monkey), Cassandra/Priam, that are currently open sourced and used by several companies. Prior to that at Yahoo, I worked on Data Highway, a realtime data platform that collects and analyzes 300 Billion web events (10TB) a day with a total hardware installation footprint of 500,000 nodes. I received my Masters in Computer Science at Stanford University under the supervision of Hector Garcia Molina.
I also served as Visiting Research Scientist at Cornell (Robot Learning Lab) primarily responsible for driving the architecture of RoboBrain. Problems I investigate are motivated by large scale multi modal data, the Web, on-line media and Knowledge bases.
Mining massive datasets (Web, Social and Knowledge Graphs)
Large Scale Data Storage and Processing Systems (BigData)
Knowledge Integration & Representations
- 4th Nov 2017:
- Gave a talk at ODSC 2017 about Meltwater AI platform to mine competitive intelligence from billions of sources [video] [slides]
- 19th Aug 2015:
- Gave keynote at SmartData 2015 conference. I spoke about Robo Brain and the collective social Intelligence at Predict Effect. [video]
- 1st Jan 2015:
- Thrilled to announce our new lab DSLL at Stanford to explore novel learning algorithms to analyze large scale cross channel multimodal social data.
- 30th Nov 2014:
- Technical report on our RoboBrain knowledge base submitted at arXiv
- 15th Oct 2014:
- Excited to collaborate with multiple groups taking CS 229 & CS 221 at Stanford.
We are focusing on different machine learning algorithms to extract large space of hierarchical labels for cross channel social data. More Info
- Sep 2014:
- Robo Brain received significant Media coverage including NYT, Wired, TechCrunch, BBC etc. Check Media coverage for more information
- 25th July 2014:
- Spoke at the Cornell University AI Lab about different efforts going on under Robo Brain project.