Dr Ninh Dang Pham

Biography

I am a lecturer at the School of Computer Science, University of Auckland since Dec 2018. Prior to joining UOA, I worked in Copenhagen for 7 years at University of Copenhagen (DIKU) and IT University of Copenhagen (ITU).

I was a postdoctoral researcher at DIKU, University of Copenhagen, working with Stephen Alstrup in the DABAI project, aiming at designing efficient algorithms for machine learning and using big data for digital learning support.

I was also a postdoctoral researcher in the Algorithms Group, ITU, involving in the SSS project, investigating efficient algorithms for high-dimensional similarity search on big data.

I received my PhD at ITU under the supervision of Rasmus Pagh in 2014. My PhD project, part of the MaDaMS project, focused on efficient randomized algorithms for big data analytics. I was the recipient of the best paper award in WWW Conference 2014.

My personal homepage: https://sites.google.com/site/phamninh/

Research | Current

Design and analyze efficient and practical randomized algorithms for large-scale machine learning and data mining tasks.

Selected publications:

• L1-Depth Revisited: A Robust Angle-based Outlier Factor in High-dimensional Space
  • Ninh Pham
  • ECML/PKDD 2018
• Hybrid LSH: Faster Near Neighbors Reporting in High-dimensional Space
  • Ninh Pham
  • EDBT 2017
• Scalability and Total Recall with Fast CoveringLSH
  • Ninh Pham, Rasmus Pagh
  • CIKM 2016
• I/O-Efficient Similarity Join
  • Rasmus Pagh, Ninh Pham, Francesco Silvestri, Morten Stöckel
  • ESA 2015 - Full version appears in Algorithmica 2017
• Efficient Estimation for High Similarities using Odd Sketches
  • Michael Mitzenmacher, Rasmus Pagh, Ninh Pham
  • WWW 2014, Best Paper Award
  • Media: ACM Computing Reviews, CPH Post, Videnskab, Berlingske
• Fast and Scalable Polynomial Kernels via Explicit Feature Maps
  • Ninh Pham, Rasmus Pagh
  • KDD 2013
• A Near-linear Time Approximation Algorithm for Angle-based Outlier Detection in High-dimensional Data
  • Ninh Pham, Rasmus Pagh
  • KDD 2012
• Online Discovery of Top-k Similar Motifs in Time Series Data
  • Hoang Thanh Lam, Toon Calders, Ninh Pham
  • SDM 2011

Teaching | Current

Thesis supervision

University of Auckland:

• Big Data Management (COMPSCI 752), Semester 1, 2019
• Uncertainty in Data (COMPSCI 753), Semester 2, 2019
• Applied Algorithmics (COMPSCI 320), Semester 2, 2019

University of Copenhagen: 

• Large-scale Data Analytics, Spring 2017
• Project Course on “Authorship verification using textual features”, Fall 2017

IT University of Copenhagen:

• Algorithm Design II, Fall 2014 - 2015

Postgraduate supervision

Master students:

• Sorin Victor Dimofte at IT University of Copenhagen, Spring 2015.
  • Thesis: Approximate nearest neighbor search in high-dimensional spaces
• Yifang Deng at University of Copenhagen, Spring 2018
  • Thesis: Ghost writing detection using textual features on Danish high school assignments

Distinctions/Honours

• Best Paper Award in WWW 2014
• Student Travel Awards in KDD 2012 - 2013

Responsibilities

Coordinator (Deputy) of the Master of Data Science programme.

Areas of expertise

Randomized Algorithms; Hashing; Data Stream; Machine Learning; Data Mining; Big Data

Committees/Professional groups/Services

Program Committee:

• WWW 2015, 2016 (Poster track)
• AusDM 2019

Journal Reviewer:

• Transactions on Knowledge and Data Engineering (TKDE)
• Transactions on Big Data (TDB)

External Conference Reviewer:

• PKDD 2013, ESA 2015, SISAP 2016, STOC 2018