Education

Papers

Vessel trajectory prediction with recurrent neural networks: an evaluation of datasets, features, and architectures (Paper) (Code)
Published in Journal Ocean Engineering and Science, 2024
Slaughter, I., Laxmichand Charla, J., Siderius, M., Lipor, J.

On the limits of distinguishing seabed types via ambient acoustic sound (Paper)
Published in Journal of the Acoustical Society of America, 2023
Lipor, J., Gebbie, J., Siderius, M.

Adaptive Sampling for Seabed Identification from Ambient Acoustic Noise (Paper)
Published in IEEE CAMSAP, 2023
Sullivan, M., Gebbie, J., Lipor, J.

K-Subspaces for Sequential Data (Paper)
Published in IEEE CAMSAP, 2023
Sheng, W., Lipor, J.

Predicting Large Hydrothermal Systems (Paper)
Published in Geothermal Rising Conference, 2023
Mordensky, S.P., Burns, E.R., Lipor, J.J.

Cursed? Why One Does Not Simply Add New Data Sets to Supervised Geothermal Machine Learning Models (Paper)
Published in Geothermal Rising Conference, 2023
Mordensky, S.P., Burns, E.R., Lipor, J.J., DeAngelo, J.

Don’t Let Negatives Hold You Back: Accounting for Underlying Physics and Natural Distributions of Hydrothermal Systems When Selecting Negative Training Sites Leads to Better Machine Learning Predictions (Paper)
Published in Geothermal Rising Conference, 2023
Caraccioli, P.D., Mordensky, S.P., Lindsey, C.R., DeAngelo, J., Burns, E.R., Lipor, J.J.

When less is more: How increasing the complexity of machine learning strategies for geothermal energy assessments may not lead toward better estimates (Paper) (Data)
Published in Geothermics, 2023
Mordensky, S.P., Lipor, J.J., DeAngelo, J., Burns, E.R., Lindsey, C.R.

What Did They Just Say? Building a Rosetta Stone for Geoscience and Machine Learning (Paper)
Published in Geothermal Rising Conference, 2022
Mordensky, S.P., Lipor, J.J., Burns, E.R., Lindsey, C.R.

Predicting Geothermal Favorability in the Western United States by Using Machine Learning: Addressing Challenges and Developing Solutions (Paper) (Presentation)
Published in Stanford Geothermal Workshop, 2022
Mordensky, S.P., Lipor, J.J., DeAngelo, J., Burns, E.R., Lindsey, C.R.

A Graph-Based Approach to Boundary Estimation with Mobile Sensors (Paper) (Code)
Published in IEEE Robotics and Automation Letters/ICRA, 2022
S.O. Stalley, D. Wang, G. Dasarathy, and J. Lipor

A Novel Framework for Deep Learning from Pairwise Constraints (Paper)
Published in Asilomar 2020
W. Sheng and J. Lipor

Subspace Clustering Using Ensembles of K-Subspaces (Paper) (Code)
Published in Information & Inference, 2020
J. Lipor, D. Hong, Y. Tan, and L. Balzano

Clustering Quality Metrics for Subspace Clustering (Paper) (Code)
Published in Pattern Recognition, Vol. 104, August 2020 (please email me if you are interested in code/data)
J. Lipor and L. Balzano

Optimal Adaptive Sampling for Boundary Estimation with Mobile Sensors (Paper)
Published in Asilomar 2019
P. Kearns, J. Lipor, and B. Jedynak

Distance-Penalized Active Learning via Markov Decision Processes (Paper)
Published in IEEE Data Science Workshop 2019
D. Wang, J. Lipor, and G. Dasarathy

A Supervised Learning Approach to Water Quality Parameter Prediction and Fault Detection (Paper)
Published in IEEE Big Data 2018
K. Joslyn and J. Lipor

Improving K-Subspaces via Coherence Pursuit (Paper) (Code)
Published in IEEE Journal of Selected Topics in Signal Processing, 2018
A. Gitlin, B. Tao, L. Balzano, and J. Lipor

Quantile Search with Time-Varying Search Parameter (Paper)
Published in Asilomar 2018
J. Lipor and G. Dasarathy

Distance-Penalized Active Learning Using Quantile Search (Paper) (Code)
Published in IEEE Transactions on Signal Processing, 2017
J. Lipor, B. Wong, D. Scavia, B. Kerkez, and L. Balzano

Leveraging Union of Subspace Structure to Improve Constrained Clustering (Paper)
Published in ICML 2017
J. Lipor and L. Balzano

Margin-Based Active Subspace Clustering (Paper)
Published in IEEE CAMSAP 2015
J. Lipor and L. Balzano

Quantile Search: A Distance-Penalized Active Learning Algorithm for Spatial Sampling (Paper) (Expanded Version)
Published in Allerton 2015
J. Lipor, L. Balzano, B. Kerkez, and D. Scavia

Optimized Wavelength Selection for Molecular Absorption Thermometry (Paper)
Published in Applied Spectroscopy, Vol. 69, No. 4, pp. 464-472, April 2015
X. An, A.W. Caswell, J. Lipor, and S.T. Sanders

Robust Blind Calibration via Total Least Squares (Paper) (Code)
Published in IEEE ICASSP 2014
J. Lipor and L. Balzano

Closed Form Fourier-Based Transmit Beamforming for MIMO Radar (Paper) (Code)
Published in IEEE ICASSP 2014
J. Lipor, S. Ahmed, and M.-S. Alouini

Fourier-Based Transmit Beampattern Design Using MIMO Radar (Paper) (Code)
Published in IEEE Transactions on Signal Processing, Vol. 55, No. 8, pp. 4151-4161, May 2014
J. Lipor, S. Ahmed, and M.-S. Alouini

Seizure Detection using the Phase-Slope Index and Multichannel EcoG (Paper)
Published in IEEE Transactions on Biomedical Engineering, Vol. 59, No. 4, pp. 1125-1134, April 2012
P. Rana, J. Lipor, H. Lee, W. van Drongelen, M.H. Kohrmann, and B. Van Veen

Determining the Optimum Wavelength Pairs to use for Molecular Absorption Thermometry Based on the Continuous-Spectral Lower-State Engergy (Paper)
Published in Journal of Quantitative Spectroscopy & Radiative Transfer, Vol. 112, No. 14, pp. 2355-2362, September 2011
X. An, A.W. Caswell, J. Lipor, and S.T. Sanders

Potential Use of UNCD Membranes as Boradband Vacuum Windowd at W-Band Frequencies (Paper)
Published in Vacuum Electronics Converence, 2008
D.M. Springmann, H. Sung-jin, J.H. Booske, S.M. Drezdon, J. Lipor, D.W. van der Weide, K. Montgomery