Dimitris Berberidis

Welcome

I'm Dimitris, and I am currently a Post-Doctoral Fellow working with Prof. Leman Akoglu at the H. John Heinz III College at Carnegie Mellon University. I obtained my PhD in 2019 from the Electrical and Computer Engineering (ECE) Department at the University of Minnesota, under the supervision of Prof. Georgios B. Giannakis.

My research interests span the areas of Network Science, Machine Learning, and Statistical Signal Processing. Specifically, I am interested in the discovery of simple yet expressive models, and the development of flexible and scalable algorithmic frameworks, accompanied by efficient and portable software tools.

Currently I am focused on learning over graphs, and particularly on embedding, classifying and detecting anomalies on large and possibly multilayered networks that arise from real-world processes.

Publications

Journals

D. Berberidis and G. B. Giannakis, " Adaptive-similarity node embedding for Scalabel Learning over Graphs", IEEE Transactions on Knowledge and Data Engineering (to appear). ( arxiv )
D. Berberidis, A. N. Nikolakopoulos, and G. B. Giannakis, "Adaptive Diffusions for Scalable Learning over Graphs", IEEE Transactions on Signal Processing 2019.( arxiv ) (short version received Best Paper Award in KDD MLG '18)
D. Lee, D. Berberidis, and G. B. Giannakis, "Adaptive Bayesian Radio Tomography", IEEE Transactions on Signal Processing.( arxiv )
D. Berberidis and G. B. Giannakis, "Data-adaptive Active Sampling for Efficient Graph-Cognizant Classification,"", IEEE Transactions on Signal Processing, vol. 66, no. 19, pp. 5167-5179, October 2018
F. Sheikholeslami, D. Berberidis, and G. B. Giannakis, "Large-scale Kernel-based Feature Extraction via Budgeted Nonlinear Subspace Tracking,"", IEEE Transactions on Signal Processing, vol. 66, no. 8, pp.1967 – 1981 , July 2018.
Z. Wang, Z. Yu, Q. Ling, D. Berberidis, and G. B. Giannakis, "Decentralized RLS with Data-Adaptive Censoring for Regressions over Large-Scale Networks,"", IEEE Transactions on Signal Processing, vol. 66, no. 6, pp.1634 – 1648 , January 2018.
D. Berberidis, and G. B. Giannakis, "Data Sketching for Large-Scale Kalman Filtering,"", IEEE Transactions on Signal Processing, vol. 65, no. 14, pp. 3688-3701, 2017
D. Berberidis, V. Kekatos, and G. B. Giannakis, "Online censoring for large-scale regressions with application to streaming big data,"", IEEE Transactions on Signal Processing, vol. 64, no. 15, pp. 3854-3867, 2016

Conferences

A. N. Nikolakopoulos, D. Berberidis, G. Karypis, and G. B. Giannakis, "Personalized Diffusions for Top-N Recommendation", Proc. of ACM Conference on Recommender Systems(RecSys) , Copenhagen, Denmark, Sept 2019 (to appear).
D. Berberidis, A. N. Nikolakopoulos, and G. B. Giannakis, "AdaDIF: Adaptive Diffusions for Efficient Semi-supervised Learning over Graphs", Proc. of IEEE Intl. Conf. on Big Data, Seattle, WA, Dec. 2018.
D. Lee, D. Berberidis, and G. B. Giannakis, "Adaptive Bayesian Channel Gain Chartography", Proc. of Intl. Conf. on Acoust., Speech, and Signal Processing, Calgary, Canada, April 2018.
D. Berberidis, A. N. Nikolakopoulos, and G. B. Giannakis, "Random Walks with Restarts for Graph-Based Classification: Teleportation Tuning and Sampling Design", Proc. of Intl. Conf. on Acoust., Speech, and Signal Processing, Calgary, Canada, April 2018.
D. Berberidis and G. B. Giannakis, "Active Sampling for Graph-aware Classification", Proc. of GlobalSIP Conf., Monreal, Canada, December, 2017.
Z Wang, Z Yu, Q Ling, D. Berberidis, and G. B. Giannakis, "Distributed recursive least-squares with data-adaptive censoring", Proc. of Intl. Conf. on Acoust., Speech, and Signal Processing, New Orleans, LA, March 2017
D. Romero, D. Berberidis, and G. B. Giannakis, "Quickest Convergence of Online Algorithms via Data Selection", Proc. of Intl. Conf. on Acoust., Speech, and Signal Processing, Shanghai, China, March 20-25, 2016.
D. Berberidis and G. B. Giannakis, "Data Sketching for Large-Scale Kalman Filtering",Proc. of Intl. Conf. on Acoust., Speech, and Signal Processing, Shanghai, China, March 20-25, 2016.
F. Sheikholeslami, D. Berberidis, and G. B. Giannakis, "Kernel-based low-rank feature extraction on a budget for big data streams",Proc. of GlobalSIP Conf., Orlando, FL December, 2015.
D. Berberidis and G. B. Giannakis, "Budgeted Kalman Filtering and Smoothing for Economical Tracking with Big Distributed Data",Proc. of Asilomar Conf. on Signals, Systems, and Computers, Pacific Grove, CA, November 8-11, 2015.
D. Berberidis, G. Wang, V. Kekatos, and G. B. Giannakis, "Online Censoring for Large-Scale Regression", Proc. of Intl. Conf. on Acoust., Speech, and Signal Processing, Brisbane, Australia, April 19-24, 2015.
G. Wang, D. Berberidis, V. Kekatos, and G. B. Giannakis, "Online Reconstruction from Big Data via Compressive Censoring", Proc. of GlobalSIP Conf., Atlanta, GA, December 3-5, 2014.
D. Berberidis, G. Wang, G. B. Giannakis, and V. Kekatos, "Adaptive Estimation from Big Data via Censored Stochastic Approximation", Proc. of Asilomar Conf. on Signals, Systems, and Computers, Pacific Grove, CA, Novemeber 2-5, 2014.

Education

PhD in Electrical and Computer Engineering

MSc in Electrical and Computer Engineering

Engineering Diploma (5-year program, M.Eng.) in Electrical and Computer Engineering

Updated: October, 14, 2018