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Vinayak graduated with flying colors! His thesis was highly rated by all reviewers who gave it an ``award quality”. He (remotely) defended the thesis from U Washington where he is doing his post-doc with Tim Althoff.

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After waiting what seemed like an eternity (it was just 2 days due to delayed notifications), we got acceptance notifications for both of our submissions. Work led by wonderful Ph.D. students, Vinayak Gupta and Shubham Gupta!!

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Garima Gaur, my second Ph.D. student, advised jointly with Arnab Bhattacharya at IITK, successfully defended her thesis titled Provenance-Aware Computation and Maintenance of Graph Query Results under Dynamic Knowledge Graphs. Congratulations, Dr. Gaur!

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Despite its importance in many applications, anomaly detection using one-class classification techniques, is notorious for its inability to scale to large features and datasets. We offer FROCC family of one-class classification techniques that are super-fast (12x fast) and accurate (2 pp better than closest deep learning based method). Oh…it scales to millions of dimensions and training datasets easily!

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I am co-organizing the second edition of the workshop on Data Quality Assessment (Data Readiness) @ KDD 2021

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Excited to be co-chairing the first International Conference on AI-ML-Systems – targeting research in the intersection of AI/ML techniques and systems engineering.

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Can we learn temporal models even with some missing observations? We offer an efficient neural point process named IMTPP in this paper, which can accurately predict next events in a temporal event stream.

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Great start to 2021 – honored to be appointed the “DS Chair Professor of Artificial Intelligence”!

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Our SIGMOD 2019 work on regular simple path queries on billion-node graphs with zero indexing receives SIGMOD reproducibility badge!

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Woot!!! Our paper proposing a novel language modeling approach for temporal information needs was awarded the Test of Time award at ECIR 2020!

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