Muhammad Bilal Zafar

Former Doctoral Student
Max Planck Institute for Software Systems (MPI-SWS)
Email: mzafar at mpi-sws dot org

About

As of July 2018, I work as a Research Scientist at Bosch Center for Artificial Intelligence in Renningen, Germany.

Before that, I was a PhD student at Max Planck Institute for Software Systems (MPI-SWS). I was co-advised by Krishna P. Gummadi and Manuel Gomez Rodriguez. Before joining MPI-SWS, I completed my undergraduate studies at LUMS School of Science and Engineering, Lahore, Pakistan.

Max Planck Institute for Software Systems, Germany (2019)
PhD in Computer Science
Saarland University, Germany (2015)
MS in Computer Science
SBA School of Science and Engineering, LUMS, Pakistan (2012)
BS in Computer Science

Fairness in Classification: Code related to our AISTATS’17, WWW’17 and NIPS’17 papers. Provides a Python implementation of fair logistic regression classifiers.
What is Happening? Web-service related to our CSCW’16 paper. Discover real-time topical news on Twitter!
Dataset for our ICWSM’16 paper.
Who is Who? — Discover crowdsourced opinion on Twitter users.
Whom to Follow? — Discover topic authorities on Twitter.

Fairness Constraints: A Flexible Approach for Fair Classification
M. B. Zafar, I. Valera, M. Gomez Rodriguez and K. P. Gummadi
Journal of Machine Learning Research, 2019.
[PDF]
Loss-Aversively Fair Classification
J. Ali, M. B. Zafar, K. P. Gummadi and A. Singla
AIES 2019, Honolulu, HI, January 2019.
[PDF]
Search Bias Quantification: Investigating Political Bias in Social Media and Web Search
J. Kulshrestha, M. Eslami, J. Messias, M. B. Zafar, S. Ghosh, K. P. Gummadi, K. Karahalios
Information Retrieval Journal, 2019.
[PDF]

A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual &Group Unfairness via Inequality Indices
T. Speicher, H. Heidari, N. Grgić-Hlača, K. P. Gummadi, A. Singla, A. Weller and M. B. Zafar
KDD 2018, London, UK, August 2018.
[arXiv]
Beyond Distributive Fairness in Algorithmic Decision Making: Feature Selection for Procedurally Fair Learning
N. Grgić-Hlača, M. B. Zafar, K. P. Gummadi and A. Weller
AAAI 2018, New Orleans, LA, February 2018.
[PDF]
Also presented at NIPS Symposium on ML and the Law 2016, Barcelona, Spain, December 2016. (Notable Paper Award)

From Parity to Preference-based Notions of Fairness in Classification
M. B. Zafar, I. Valera, M. Gomez Rodriguez, K. P. Gummadi and A. Weller
NIPS 2017, Long Beach, CA, December 2017.
[PDF] [arXiv] [Code]
Also presented at FATML 2017, Halifax, Canada, August 2017.
On Fairness, Diversity and Randomness in Algorithmic Decision Making
N. Grgić-Hlača, M. B. Zafar, K. P. Gummadi and A. Weller
FATML 2017, Halifax, Canada, August 2017.
[arXiv]
Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment
M. B. Zafar, I. Valera, M. Gomez Rodriguez and K. P. Gummadi
WWW 2017, Perth, Australia, April 2017. (Best Paper Honorable Mention)
[PDF] [arXiv] [Code]
Also presented at FATML 2016, New York, NY, November 2016.
Fairness Constraints: Mechanisms for Fair Classification
M. B. Zafar, I. Valera, M. Gomez Rodriguez and K. P. Gummadi
AISTATS 2017, Fort Lauderdale, FL, April 2017.
[PDF] [arXiv] [Code]
Also presented at FATML 2015, Lille, France, July 2015.
Quantifying Search Bias: Investigating Sources of Bias for Political Searches in Social Media
J. Kulshrestha, M. Eslami, J. Messias, M. B. Zafar, S. Ghosh, K. P. Gummadi and K. Karahalios
CSCW 2017, Portland, OR, February 2017.
[PDF]

The Case for Temporal Transparency: Detecting Policy Change Events in Black-Box Decision Making Systems
M. Ferreira, M. B. Zafar and K. P. Gummadi
FATML 2016, New York, NY, November 2016.
[arXiv]
Listening to Whispers of Ripple: Linking Wallets and Deanonymizing Transactions in the Ripple Network
P. Moreno-Sanchez, M. B. Zafar and A. Kate
PETS 2016, Darmstadt, Germany, May 2016.
[PDF]
Message Impartiality in Social Media Discussions
M. B. Zafar, K. P. Gummadi and C. Danescu-Niculescu-Mizil
ICWSM 2016, Cologne, Germany, May 2016.
[PDF] [Data]
On the Wisdom of Experts vs. Crowds: Discovering Trustworthy Topical News in Microblogs
M. B. Zafar, P. Bhattacharya, N. Ganguly, S. Ghosh and K. P. Gummadi
CSCW 2016, San Francisco, CA, February 2016.
[PDF] [Web-service]

Strength in Numbers: Robust Tamper Detection in Crowd Computations
B. Viswanath, M. A. Bashir, M. B. Zafar, S. Bouget, S Guha, K. P. Gummadi, A. Kate and A. Mislove
COSN 2015, Palo Alto, CA, October 2015. (Best Paper Award)
[PDF]
Sampling Content from Online Social Networks: Comparing Random vs. Expert Sampling of the Twitter Stream
M. B. Zafar, P. Bhattacharya, N. Ganguly, K. P. Gummadi and S. Ghosh
ACM TWEB, June 2015.
[PDF]
Characterizing Information Diets of Social Media Users
J. Kulshrestha, M. B. Zafar, L. E. Noboa, K. P. Gummadi and S. Ghosh
ICWSM 2015, Oxford, UK, May 2015.
[PDF]

Inferring User Interests in the Twitter Social Network
P. Bhattacharya, M. B. Zafar, N. Ganguly, S. Ghosh and K. P. Gummadi
RecSys 2014, Silicon Valley, CA, October 2014. (Short paper)
[PDF]
Deep Twitter Diving: Exploring Topical Groups in Microblogs at Scale
P. Bhattacharya, S. Ghosh, J. Kulshrestha, M. Mondal, M. B. Zafar, N. Ganguly and K. P. Gummadi
CSCW 2014, Baltimore, MD, February 2014.
[PDF]

On Sampling the Wisdom of Crowds: Random vs. Expert Sampling of the Twitter Stream
S. Ghosh, M. B. Zafar, P. Bhattacharya, N. Sharma, N. Ganguly and K. P. Gummadi
CIKM 2013, Burlingame, CA, October 2013.
[PDF]
SplitBuff: Improving the Interaction of Heterogeneous RTT Flows on the Internet
S. Jabeen, M. B. Zafar, I. A. Qazi and Z. A. Uzmi
ICC 2013, Budapest, Hungary, June 2013.
[PDF]

Human vs. Algorithmic Decision Making: Bias, Fairness and Transparency (Teaching Assistant)
Max Planck Institute for Software Systems & Saarland University, Winter Semester 2015-16.
Database Systems (Teaching Assistant)
Saarland University, Summer Semester 2014.
Advanced Programming (Teaching Assistant)
LUMS School of Science and Engineering, Spring Semester 2012.