Daniel P. Palomar

Picture


Professor
Department of Electronic & Computer Engineering (ECE) and
Department of Industrial Engineering & Decision Analytics (IEDA)
Hong Kong University of Science and Technology (HKUST)
Clear Water Bay, Kowloon, Hong Kong

E-mail: palomar@ust.hk
Homepage: https://www.danielppalomar.com
GitHub: https://github.com/dppalomar
YouTube: https://www.youtube.com/danielpalomar
Google Scholar: link
Phone: +852 2358 7060;  Fax: +852 2358 1485
Office: 2398 (lifts 17-18)
I am a Professor in the Department of Electronic and Computer Engineering at the Hong Kong University of Science and Technology (HKUST), which I joined in 2006. I received the Electrical Engineering degree and the Ph.D. degree from the Technical University of Catalonia (UPC), Barcelona, Spain, in 1998 and 2003, respectively, and I was a Fulbright Scholar at Princeton University during 2004-2006. I have held several visiting research appointments, namely, at King's College London (KCL), London, UK; Technical University of Catalonia (UPC), Barcelona; Stanford University, Stanford, CA; Telecommunications Technological Center of Catalonia (CTTC), Barcelona; Royal Institute of Technology (KTH), Stockholm, Sweden; University of Rome "La Sapienza", Rome, Italy; and Princeton University, Princeton, NJ.

​My current research interests include applications of optimization theory, graph methods, and signal processing in financial systems and big data analytics.

I am an IEEE Fellow and, among others, I have been awarded with the 2004/06 Fulbright Research Fellowship and the 2004, 2015, and 2020 Young Author Best Paper Awards by the IEEE Signal Processing Society.

I have served as Associate Editor of IEEE Transactions on Information Theory, Associate Editor of IEEE Transactions on Signal Processing, Guest Editor of the IEEE JSTSP 2016 Special Issue on "Financial Signal Processing and Machine Learning for Electronic Trading," Guest Editor of the IEEE Signal Processing Magazine 2010 Special Issue on “Convex Optimization for Signal Processing,” Guest Editor of the IEEE Journal on Selected Areas in Communications 2008 Special Issue on “Game Theory in Communication Systems,” the Lead Guest Editor of the IEEE Journal on Selected Areas in Communications 2007 Special Issue on “Optimization of MIMO Transceivers for Realistic Communication Networks.” I was the General Co-Chair of the 2009 IEEE Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) and have served as part of the Organizing Committee of ICASSP 2015, SPAWC 2015, and EUSIPCO 2011.

[CV]
Videos of HKUST: HKUST campus DJI 2013, HKUST campus DJI 2015, HKUST campus DJI Phantom 4 2016, history HKUST, HKUST corporate video, student diversity.

Some recent news:

  • Dec. 16, 2020: News at HKUST
  • Dec. 12, 2020: Our paper has received the 2020 Young Author Best Paper Award by the IEEE Signal Processing Society!!
Ying Sun, Prabhu Babu, and Daniel P. Palomar, “Majorization-Minimization Algorithms in Signal Processing, Communications, and Machine Learning,” IEEE Trans. on Signal Processing, vol. 65, no. 3, pp. 794-816, Feb. 2017.Jiaxi Ying, José Vinícius de M. Cardoso, and Daniel P. Palomar, “Nonconvex Sparse Graph Learning under Laplacian Constrained Graphical Model,” Advances in Neural Information Processing Systems (NeurIPS), Dec. 2020. [2-min video] [slides] [poster] [R package]
  • July 11, 2020: R package ​imputeFin for imputation of financial time series updated with outlier detection.
  • May 13, 2020: check out my YouTube channel in the making. Subscribe to be notified of my upcoming posted talks.
  • Dec. 12, 2019: R package for imputation of financial time series with missing values published in CRAN:  ​imputeFin (GitHub)
  • Dec. 3, 2019: archives of my two courses can be found on my web: PhD course Convex Optimization and MSc course Portfolio Optimization with R.
  • Nov. 22, 2019: R package for covariance matrix estimation under heavy tails published in CRAN: fitHeavyTail (GitHub).​​
  • Nov. 6, 2019: Invited talk at Apple Inc.: "A Unified Framework for Structured Graph Learning via Spectral Constraints," Silicon Valley, California, USA
  • Sep. 4, 2019: graph paper “Structured Graph Learning Via Laplacian Spectral Constraints” accepted in NeurIPS [2-min video] [slides] [arxiv] [R package].​
  • Sept. 2, 2019: Tutorial “Portfolio Optimization in Financial Markets,” European Signal Processing Conference (EUSIPCO), A Coruña, Spain.
  • June 19, 2019: R package for portfolio backtesting published in CRAN: portfolioBacktest (GitHub).​
  • May 17, 2019: Talk in  R/Finance 2019 on the package riskParityPortfolio.
  • May 8, 2019: R package for graph learning via spectral constraints published in CRAN: spectralGraphTopology (GitHub).
  • Dec. 25, 2018: R package for the design of risk parity portfolios published in CRAN: riskParityPortfolio (GitHub​). 600 downloads in 3 days!!
  • Dec. 21, 2018: Invited Talk “Imputation of Time Series with Missing Values under Heavy-Tailed AR Model via Stochastic EM,” International Workshop on Mathematicl Issues on Information Sciences (MIIS), The Chinese University of Hong Kong, Shenzhen, China.
  • Nov. 28, 2018: Invited Talk “Imputation of Time Series with Missing Values under Heavy-Tailed AR Model via Stochastic EM,” Big Data Challenges for Predictive Modeling of Complex Systems, Institute of Mathematical Research, University of Hong Kong, Hong Kong.
  • Fall 2018 semester: teaching the new course MAFS6010R – Portfolio Optimization with R​ as part of the MSc in Financial Mathematics in the Math department at HKUST.
  • June 14, 2018, Invited Talk “Financial Engineering Playground: Signal Processing, Robust Estimation, Kalman, HMM, Optimization, et Cetera,” Aalto University, Finland.
  • June 11, 2018, Plenary Talk “Financial Engineering Playground: Signal Processing, Robust Estimation, Kalman, HMM, Optimization, et Cetera,” IEEE Statistical Signal Processing Workshop (SSP), Freiburg, Germany.
  • 2018 Monograph on Financial Engineering:
​Konstantinos Benidis, ​Yiyong Feng, and Daniel P. Palomar, Optimization Methods for Financial Index Tracking: From Theory to Practice, Foundations and Trends® in Optimization, Now Publishers, 2018.
  • May 17, 2018: R package for computation of sparse portfolio to track an index published in CRAN: sparseIndexTracking​ (GitHub​).
  • Dec. 20, 2017: R package for computation of sparse eigenvectors published in CRAN: sparseEigen (GitHub).
  • Dec. 11, 2017: Plenary Talk “A Signal Processing and Optimization Perspective on Financial Engineering,” IEEE Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), Curaçao, Dutch Antilles.
  • Nov. 13-15, 2017: Invited Speaker at the db Global Quant Conference, Deutsche Bank, Hong Kong.
  • 2016 Monograph on Financial Engineering:
​Yiyong Feng and Daniel P. Palomar,  A Signal Processing Perspective on Financial Engineering, Foundations and Trends® in Signal Processing, Now Publishers, vol. 9, no. 1-2, 2016. [pdf]
  • 2015-16 Research Excellence Award at HKUST.
  • 2015 Young Author Best Paper Award (co-author) by the IEEE Signal Processing Society.
  • Oct. 2015: Guest Editor on the Special Issue on Financial Signal Processing and Machine Learning for Electronic Trading in  IEEE Journal of Selected Topics in Signal Processing.
  • Aug. 2015: Invited Talk at ICIAM 2015, Beijing, China.
  • June-July 2015: Organizing Committee for SPAWC 2015,Stockholm, Sweden.
  • April 2015: Organizing Committee for ICASSP 2015, Brisbane, Australia.
  • June 2014: Promoted to Full Professor.
  • Jan. 2013: Became Fellow of the Institute for Advanced Study (IAS) at HKUST.
  • Nov. 2012: Elected IEEE Fellow for “contributions to convex optimization-based signal processing for communications”.
  • July 18-24, 2012: Invited Speaker at the Workshop on Advances in Wireless Communications (WAWC'12), Univ. of Electronic Science and Technology of China (UESTC), Chengdu, China. (Organized by Geoffrey Li and Shaoqian Li.)
  • July 13-17, 2012: Invited Speaker at the Workshop on Advances in Wireless Communications (WAWC'12), Southeast Univ., Nanjing, China. (Organized by Zhi Ding and Xiaohu You.)
  • July 7-13, 2012: Invited Speaker at the International Workshop on Mathematical Issues in Information Sciences (MIIS'12), Xi'an, China. (Organized by Tom Luo and Hong Wei Liu.)
  • Jan. 2012: The research center CTTC-HK becomes operative in Hong Kong.
  • Aug-Sept. 2011: Organizing committee of EUSIPCO 2011, Barcelona, Spain.
  • March 2011: Invited Instructor at the 2011 Winter School of Information Theory, Barcelona, Spain.
  • Aug. 2010: Consultant of research center CTTC-HK in Hong Kong.
  • Dec. 2010: Invited Speaker at the 2010 Workshop on Applications of Optimization in Science and Engineering, Institute for Pure and Applied Mathematics (IPAM), UCLA campus, LA, USA.
  • Aug 2010: Presented tutorial “Convex Optimization, Game Theory, and Variational Inequality Theory in Multiuser Communication Systems” in EUSIPCO 2010, Aalborg, Denmark.
  • July 2010: Promoted to Associate Professor.
  • Jan. 2010: Chair of the IEEE Hong Kong Information Theory Society.
  • May 2010: Guest editor of a special issue in the IEEE Signal Processing Magazine on “Convex Optimization for Signal Processing.”
  • March 2010: Invited Speaker at the 2010 Workshop on Distributed Decision-Making and Control, LCCC, Lunds University, Sweden.
  • Dec. 2009: Publication of the edited the book “Convex Optimization in Signal Processing and Communications” by Cambridge University Press together with Yonina Eldar.
  • Dec. 2009: General Co-Chair of the 2009 IEEE Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) in Aruba.
  • June 2009: Organizing Committee of SPAWC 2009, Perugia, Italy.
  • Feb. 2009: Key Note Speaker at the Australian Communication Theory Workshop (AusCTW2009), University of New South Wales, Sydney, Australia.
  • Feb. 2009: Taught an intensive one-day seminar on “Convex Optimization with Applications to Communications” at the University of New South Wales, Sydney, Australia.
  • Highly cited paper (ISI Web of Knowledge) status for my 2003 IEEE Trans. SP paper (coauthored by Lagunas and Cioffi) on majorization theory and convex optimization applied to MIMO transceiver design.
  • Dec. 2008: Taught an intensive 18-hour course on “Convex Optimization for Wireless Communications and Signal Processing” at the National Chiao Tung Univ., Hsinchu, Taiwan. (Co-taught with Ken Ma.)
  • July 2008: Plenary Speaker at the 2008 IEEE Workshop on Signal Proc. Advances in Wireless Comm. (SPAWC), Recife, Brazil.
  • April 2008: Invited Speaker at the “Panel for Convex Optimization and Applications,” ICASSP 2008, Las Vegas, USA.
  • Dec. 2007: Invited Speaker at the 2007 Workshop on Optimization and Signal Processing (WOSP), Hong Kong.