I am an architect in Microsoft’s Cloud and AI division. My group develops ML.NET, Microsoft’s machine learning toolkit. I am also a member of the Apache Software Foundation and was the inaugural PMC chair (VP) of Apache REEF. My work focuses on machine learning techniques, systems therefore and applications thereof. Prior, I lead the machine learning research group of the Cloud Information Services Laboratory (CISL) at Microsoft and prior to that, was a researcher at Yahoo! Research.

Software contributions

  • Microsoft ML.NET: Machine learning for .NET developers. Open Source and cross platform.
  • Apache REEF: A standard library for writing high performance applications on Big Data clusters.
  • ScalOps A domain specific language for distributed, larger scale data analytics and machine learning.
  • DIOS: A large scale machine learning library used at Yahoo!
  • CofiRank: A collaborative filtering algorithm that supports predicting the ranking of items as opposed to mere rating.
  • BMRM: Open source, modular and scalable convex solver for many machine learning problems cast in the form of regularized risk minimization problem.
  • Elefant: A machine learning toolbox. My contributions include a bridge that renders UIMA annotators into feature extraction tools for machine learning. This code is Open Source under the Mozilla Public License.
  • DkPro: A set of UIMA annotators developed at TU Darmstadt.

Awards

Academic Service

  • 2019: PC Member ICML 2019, SIGMOD 2019, SysML 2019
  • 2018: PC Member of SysML 2018
  • 2017: Demonstrations and Competitions Chair for NIPS 2017
  • 2016: Co-Chair for KDD Cup 2016. Reviewer / PC Member: HotCloud, USENIX ATC, VLDB
  • 2015 Organizer of Learning Systems 2015. Reviewer / PC Member: NIPS, KDD
  • 2014: PC Member: KDD, ACM Recommender Systems, NIPS
  • 2013: PC Member CIKM 2013, ACM RecSys 2013, SIGMOD 2013, NIPS 2013, SOCC 2013; Tutorials on large scale machine learning at ICDE and SIGMOD
  • 2012: New Templates for Scalable Data Analysis Tutoria at WWW 2012; PC-Member KDD, ICML, Hadoop Summit 2012
  • 2011: Organizer KDD Cup; PC-Member: KDD, HetRec, BigLearn, CMPL, AISTATS, ICANN
  • 2010: Organized HetRec 2010; PCMember: NIPS, ACM Recommender Systems, ICML, AISTATS, ECML/PKDD, MLOSS ‘10, IEEE Transactions on Knowledge and Data Engineering (TKDE) and the Special Issue of the Journal of Web Semantics on “Bridging the Gap” – Data Mining and Social Network Analysis for Integrating Semantic Web and Web 2.0
  • 2009: Organized iatel09; PC Member: Deutsche KI-Konferenz, KDD, ECML/PKDD, Workshop on Social Information Retrieval for Technology-Enhanced Learning (SIRTEL’08) in the International Conference on Web-based Learning (ICWL) 2009

Student guidance

  • Sergey Dudoladov: Summer intern at Microsoft, 2016
  • Ignacio Cano: Summer intern at Microsoft, 2015
  • Alex Beutel: Summer intern at Microsoft, 2014
  • Arun Kumar: Summer intern at Microsoft, 2013
  • Daniel Glöckner: Collaborative filtering of framework code, Diploma thesis at TUD.
  • Kai Michael Höver: Ranking im Web 2.0. Diplomarbeit an der TU Darmstadt.
  • David Koch: Study of the discrepancy between client- and server side logging of clickstreams. Master’s Thesis at the KTH Stockholm.

Former affiliations

  • Yahoo! Research: My focus there was anti-abuse and web scale machine learning.
  • I obtained my PhD as a student in the graduate school for the improvement of e-learning at the computer science department of the Technische Universität Darmstadt, Germany. I worked on applications of machine learning in elearning. To do so, I was lucky enough to gather support by two supervisors: Max Mühlhäuser (TUD) and Alex Smola.
  • Yahoo! Labs: Research intern. I worked on email spam filters in the SPARTA project.
  • Statistical Machine Learning Program of NICTA: Visiting Scholar
  • Data Mining Group MINE of Fraunhofer’s Integrated Publication and Information Systems Institute (IPSI): Research associate
  • Centre for Complex Systems and Control (CDSC) at The University of Newcastle, Australia: Visiting Scholar