Ron Bekkerman
About Me
Dr. Ron Bekkerman is the Director of the Leir Research Institute for Business, Technology, and Society at NJIT.
Ron is a technology executive, educator, and expert in AI, machine learning, and big data science. Most recently serving as the CTO of Cherre, Ron has previously been a data science professor, a venture capitalist, a startup founder, and an industrial researcher. He has published over 40 papers, initially focusing primarily on machine learning and later expanding into various disciplines where his big data expertise unlocked new research opportunities. Ron serves on the advisory board of NJIT Institute for Data Science and on the organizing committee of KDD - the #1 data science academic conference.
Ron is a technology executive, educator, and expert in AI, machine learning, and big data science. Most recently serving as the CTO of Cherre, Ron has previously been a data science professor, a venture capitalist, a startup founder, and an industrial researcher. He has published over 40 papers, initially focusing primarily on machine learning and later expanding into various disciplines where his big data expertise unlocked new research opportunities. Ron serves on the advisory board of NJIT Institute for Data Science and on the organizing committee of KDD - the #1 data science academic conference.
Journal Article
Ron Bekkerman, Maxime C Cohen, Xiaoyan Liu, John Maiden, Dmitry Mitrofanov. 2024. "The impact of the opportunity zone program on residential real estate." Manufacturing \& Service Operations Management, vol. 26, no. 6, pp. 2142--2159.
Ron Bekkerman, Eliezer M Fich, Natalya V Khimich. 2023. "The effect of innovation similarity on asset prices: Evidence from patents’ big data." Best Paper Award The Review of Asset Pricing Studies, vol. 13, no. 1, pp. 99--145.
Ron Bekkerman, Donal Warde, Maxime C. Cohen. 2023. "Using Data Science to Predict the Impacts of Gentrification." AFIRE Summit, vol. 12, pp. 54--63.
Ron Bekkerman, Maxime C. Cohen, Edward Kung, John Maiden, Davide Proserpio. 2021. "Restricting Airbnb Rentals Reduces Development." Harvard Business Review.
Eran Raveh, Yuval Ofek, Ron Bekkerman, Hertzel Cohen. 2020. "Applying Big Data visualization to detect trends in 30 years of performance reports." Evaluation, vol. 26, no. 4, pp. 516--540.
Ron Bekkerman, Eliezer M Fich, Natalya V Khimich. 2023. "The effect of innovation similarity on asset prices: Evidence from patents’ big data." Best Paper Award The Review of Asset Pricing Studies, vol. 13, no. 1, pp. 99--145.
Ron Bekkerman, Donal Warde, Maxime C. Cohen. 2023. "Using Data Science to Predict the Impacts of Gentrification." AFIRE Summit, vol. 12, pp. 54--63.
Ron Bekkerman, Maxime C. Cohen, Edward Kung, John Maiden, Davide Proserpio. 2021. "Restricting Airbnb Rentals Reduces Development." Harvard Business Review.
Eran Raveh, Yuval Ofek, Ron Bekkerman, Hertzel Cohen. 2020. "Applying Big Data visualization to detect trends in 30 years of performance reports." Evaluation, vol. 26, no. 4, pp. 516--540.
SHOW MORE
Conference Paper
“Data science for the real estate industry”
KDD, 2020.
“What are they up to? Distilling the Twitter Stream of Subpopulations”
KDD Workshop, 2018.
“Visualizing Wikipedia for Interactive Exploration”
KDD Workshop, 2017.
“Bimodal invitation-navigation fair bets model for authority identification in a social network”
WebConf, 2012.
“Learning to rank social update streams”
SIGIR, 2012.
KDD, 2020.
“What are they up to? Distilling the Twitter Stream of Subpopulations”
KDD Workshop, 2018.
“Visualizing Wikipedia for Interactive Exploration”
KDD Workshop, 2017.
“Bimodal invitation-navigation fair bets model for authority identification in a social network”
WebConf, 2012.
“Learning to rank social update streams”
SIGIR, 2012.
SHOW MORE
Book
Ron Bekkerman, Mikhail Bilenko, John Langford. "Scaling up machine learning: Parallel and distributed approaches." Cambridge University Press, 2012.
Chapter
Ron Bekkerman, Martin Scholz. "Parallelizing Information-Theoretic Clustering Methods." pp. 262. Scaling Up Machine Learning, 2011.
Monograph
“Combinatorial markov random fields and their applications to information organization”
PhD Thesis, University of Massachusetts at Amherst, 2008.
PhD Thesis, University of Massachusetts at Amherst, 2008.
Technical Report
“Unsupervised non-topical classification of documents”
Department of Computer Science, University of Massachusetts, Amherst, 2006.
“Automatic categorization of email into folders: Benchmark experiments on Enron and SRI corpora”
Department of Computer Science, University of Massachusetts, Amherst, 2004.
“Using bigrams in text categorization”
Department of Computer Science, University of Massachusetts, Amherst, 2004.
Department of Computer Science, University of Massachusetts, Amherst, 2006.
“Automatic categorization of email into folders: Benchmark experiments on Enron and SRI corpora”
Department of Computer Science, University of Massachusetts, Amherst, 2004.
“Using bigrams in text categorization”
Department of Computer Science, University of Massachusetts, Amherst, 2004.