RESEARCH

  • Artificial Intelligence and Data Science
  • Machine Learning, and Deep Learning
  • AI for Climate, Wildfire, Air Quality
  • AI for Earth Science
  • Predictive Analytics/Big Data Analytics
  • AI for Urban sustainability 
  • Health Analytics
  • Machine Learning in Image and Video Processing

PEOPLE

    Director

                                                    my2

                             Mohammad Pourhomayoun, PhD
                                          Founder and Director
                                            Associate Professor
                                Computer Science Department
                                Email: [email protected]

    Research Team:

MSH

Juya Ahmadi 
Graduate Student
MSH

Ambujan Nair
Graduate Student 
MSH

Kevin williams
Graduate Student

 

s1

Mohammed Kuko
Researcher
MSH

Amir ebrahimi
Graduate Student

 

MSH

Ryan Dunning
Graduate Student

 

MSH

Kabir Nagrecha
Research Associate

 

MSH

Pratyush Muthukuma
Researcher

 

MSH

Emmanuel Cocom
Undergrad Student

 

s1

Carlos Estebes
Undergrad Student

 

 

 

 

 

 

 

 

    Graduated MS Students:

  • Justin West (Spring 2021)
  • Kevin Marlis (Spring 2021) 
  • Erika Estrada Medina (Spring 2021)
  • Nikita Aggarwal (Spring 2021)  
  • Daniel Chang (Fall 2020) 
  • Andrew Garcia (Fall 2018)
  • Luis Fisher (Spring 2020)  
  • Pandian Rajaram (Spring 2020) 
  • Mohammed Kuko (Spring 2020) 
  • Safa Mahbub  (Summer 2019)
  • Apostolos Kalatzis (Spring 2019)
  • Abdullah Alqahtani (Fall 2018)
  • Vignesh Saravanan (Fall 2018)
  • Naveen Kumar  (Summer 2018)
  • Melanie Kwon  (Summer 2018)
  • Cheryl Jose  (Summer 2018)
  • Kae Sawada  (Spring 2018)
  • Haiyan Wang (Spring 2018) 
  • Steve Shim (Spring 2017)

 

RESEARCH PROJECTS:

- Predict What We Breathe: Using Artificial Intelligence and Machine Learning to Understand, Predict, and Manage Air Pollution:

  • Developing machine learning and data science methods to understand and address Health Effects/Risks of air pollution

pwwb

                                           

  PM2.5 Air Pollution Prediction in Next 24 hours in LA County
air pollution prediction

 

- Predictive Environmental Analytics for Equity and Environmental Justice and Climate Change:

  • Developing Data Analytics, AI, and machine learning models to support climate action plans                               

1

   

                                2

 

- Artificial Intelligence and Data Science to Address Coronavirus and COVID-19 Pandemic:
Best Paper Award

                                                

 

     - Machine Learning and Computer Vision for Traffic Management and Accident Prevention:

                         

 

                           

     - Machine Learning for Predicting, Detecting, and Managing Cancer: 

                                                 

pap

                  

nn

  

 

    - Predictive Analytics for Chronic Disease Management:
                                                                                  rhm1

 

    - Big Data Analytics for Understanding/Predicting the Genetic Basis of Disease:                                        
                                                                                  dna1
           
                                                                                  dna2
           dna4

 

    - Data Science for Remote Health Monitoring:
                                                                        rhm2
    - Context-Aware Analytics for Patient Monitoring: 
 
                                                                        w
              ar

    

    - Interactive Map for Traffic Data Analytics and Visualization:
                                                                             map

 

    -  Predictive Analytics for Marketing and Business Intelligence:

                                   

                                                                             dm

                

                                                                             f

               

                                                                    tw

              

 

OUR SPONSORS

 

       
                                                                             T
       
                                                                             l
      
                                                                             dot
       
                                                                             ita
    
                                                                             u
       
                                                                             m
      
                                                                             lac
      caltrans

 

TEACHING (Developed Courses)

CS4661:  Introduction to Data Science

CS4662:  Advanced Machine Learning

CS5661:  Advanced Topics in Data Science

 

PUBLICATIONS

 

  1. P. Muthukumar, Sh. Pathak, K. Nagrecha,D. Comer, N. Amini,J. Holm, M. Pourhomayoun, “High-Resolution Spatiotemporal PM2.5 Prediction with Deep Convolutional LSTM using Atmospheric and Ground-level Data”, Int. Conference on Data Science (ICDATA’22), 2022.
  2. K. Williams, M. Pourhomayoun, “Understanding the Health Consequences of Air Quality using Machine Learning”, Int. Conference on Data Science (ICDATA’22), 2022.
  3. P. Muthukumar,K. Nagrecha,D. Comer,Ch. Calvert,N. Amini,J. Holm, M. Pourhomayoun, “PM2.5 Air Pollution Prediction through Deep Learning Using Multisource Meteorological, Wildfire, and Heat Data”, Atmosphere Journal, 2022.
  4. Thomas Huang, Nga Chung, Alex Dunn, Erik Hovland, Jason Kang, Thomas Loubrieu, Jessica Neu, Joe Roberts, Sina Hasheminassab, Kevin Marlis, Liam Bindle, Lucas Estrada, Daniel Jacob, Randall Martin, Jeanne Holm, Mohammad Pourhomayoun, Daven Henze, Omar Nawaz, Chaowei Yang, Qian Liu, Title: An Advanced Open-Source Platform For Air Quality Analysis, Visualization, and Prediction, IGRASS 2022.
  5. Jeanne Holm, Jacqueline Le Moigne, Mohammad Pourhomayoun, “Creating Global Digital Twins To Improve Air Quality And Covid Outcomes,“ 20th Iaa Symposium On Building Blocks For Future Space Exploration And Development, 2022.
  6. Jeanne Holm, Jacqueline Le Moigne, Mohammad Pourhomayoun, “Federating Space, Air, And Ground Air Quality Data to Improve Outcomes in Cities Around The World” Iaf Symposium On Integrated Applications, Integrated Applications End-To-End Solutions,2022.
  7. P. Muthukumar, K. Nagrecha, E. Cocom, D. Comer, I. Burga, J. Taub, Ch. Calvert, N. Amini, J. Holm, and M. Pourhomayoun “Predicting PM2.5 Atmospheric Air Pollution using Deep Learning with Meteorological Data and Ground-based Observations and Remote-Sensing Satellite Big Data,” Sprinter Journal of Air Quality, Atmosphere & Health, 2021.
  8. J. Holm, J. Le Moigne, M. Cole, M. Pourhomayoun, Dawn Comer, Irene Burga, Jeremy Taub, Chisato Calvert, “Creating Global Digital Twins to Improve Air Quality and COVID Outcomes” In AGU Fall Meeting, 2021.
  9. T. Huang, N. T Chung, A. E Dunn, K. R Verhulst, J. Holm, M. Pourhomayoun, D. K Henze, R. Martin, L. Bindle “AQACF: A Platform for Air Quality Analysis, Visualization, and Prediction” In AGU Fall Meeting, 2021.
  10. P. Muthukumar, K. Nagrecha, E. Cocom, D. Comer, A. Lyons, I. Burga, Ch. Hasenkopf, J. Holm, and M. Pourhomayoun, Predicting PM2.5 Air Pollution using Deep Learning with Multisource Satellite and Ground-based Observations and Meteorological and Wildfire Big Data, In AGU Fall Meeting, 2021.
  11. M. Pourhomayoun, M. Shakibi, “Predicting Mortality Risk in Patients with COVID-19 Using Artificial Intelligence to Help Medical Decision-Making,” the Journal of Elsevier Smart Health, 2020.
  12. 7. K. Marlis, J. West, D. Comer, I. Burga, J. Taub, C. F. Calvert, J. Holm, and M. Pourhomayoun, “A Comprehensive Analysis of Air Pollution and Equity During COVID-19 in Los Angeles County,” The 17th International Conference on Data Science, ICDATA'21: July 26-29, 2021, USA.
  13. P. Muthukumar, E. Cocom, J. Holm, D. Comer, A. Lyons, I. Burga, Ch. Hasenkopf, and M. Pourhomayoun, “Real-time spatiotemporal NO2 air pollution prediction with deep convolutional LSTM through satellite image analytics”.  In AGU Fall Meeting Abstracts, 2020.
  14. E. Cocom, P. Muthukumar, J. Holm, D. Comer, A. Lyons, I. Burga, Ch. Hasenkopf, and M. Pourhomayoun, “Particulate Matter Forecasting in Los Angeles County with Sparse Ground-Based Sensor Data Analytics”.  In AGU Fall Meeting Abstracts, 2020.
  15. P. Muthukumar, E. Cocom, J. Holm, D. Comer, A. Lyons, I. Burga, Ch. Hasenkopf, and M. Pourhomayoun, “Satellite Image Atmospheric Air Pollution Prediction through Meteorological Graph Convolutional Network with Deep Convolutional LSTM,” The 2020 International Conference on Computational Science and Computational Intelligence (CSCI'20), 2020.
  16. K. Nagrecha, L. Fisher, M. Mooney, E. Alavi, T. Rodriguez-Nikl, M. Mazari, M. Pourhomayoun, “As-Encountered Prediction of Tunnel Boring Machine Performance Parameters Using Recurrent Neural Networks,” The Journal of the Transportation Research Board 2020, and Transportation Research Board Annual Conference (TRB 2020), July 2020, https://doi.org/10.1177/0361198120934796.
  17. K. Nagrecha , P. Muthukumar, E. Cocom, J. Holm, D. Comer, A. Lyons, I. Burga, Ch. Hasenkopf, and M. Pourhomayoun, “Sensor-Based Air Pollution Prediction Using Deep CNN-LSTM,” The 2020 International Conference on Computational Science and Computational Intelligence (CSCI'20), 2020.
  18. E. Estrada Medina, M. Mazari, M. Pourhomayoun, “Deep Learning for Infrastructure Defect Monitoring and Forecasting,” The 25th International Conference on Image Processing, Computer Vision, & Pattern Recognition IPCV'21, July 26-29, 2021.
  19. L. Fisher, K. Nagrecha, M. Mooney, E. Alavi, S. Mokhtari, T. Rodriguez-Nikl, M. Mazari, M. Pourhomayoun, “Real-Time Prediction of Geological Composition using Recurrent Neural Networks and Shield Tunnel Boring Machine Data,” Journal Transportation Research Board Annual Conference (TRB 2020), (submitted, under review).
  20. M. Kuko and M. Pourhomayoun, “Single and Clustered Cervical Cell Classification with Ensemble and Deep Learning Methods,” Journal of Springer Information Systems Frontiers, 2020.
  21. Pratyush Muthukumar, Emmanuel Cocom, Jeanne Holm, Dawn Comer, Anthony Lyons, Irene Burga, Christa Hasenkopf, and M. Pourhomayoun, “Real-Time Spatiotemporal Air Pollution Prediction with Deep Convolutional LSTM through Satellite Image Analysis,” The 16th Int. Conference on Data Science (ICDATA’20), 2020.
  22. M. Pourhomayoun, M. Shakibi, Using Artificial Intelligence for Medical Condition Prediction and Decision-Making For COVID-19 Patients, Springer Nature: The 6th International Conference on Health Informatics & Medical Systems, 2020.
  23. G. Mahmoudinezhad, V. Mohammadzadeh, N. Amini, V. Toriz, M. Pourhomayoun, S. Heydarzadeh, A. Mylavarapu, E. Morales, J. Caprioli, K. Nouri-Mahdavi, “Local Macular Thickness Relationships between Two OCT Devices,” Elsevier Journal of Ophthalmology Glaucoma, 2020.
  24. Daniel R. Chang, David R. Chang, Mohammad Pourhomayoun, “Risk Prediction of Critical Vital Signs for ICU Patients Using Recurrent Neural Network,” The 2019 International Conference on Computational Science and Computational Intelligence, 2019, Las Vegas.
  25. K. Nagrecha, L. Fisher, M. Mooney, E. Alavi, T. Rodriguez-Nikl, M. Mazari, M. Pourhomayoun, “As-Encountered Prediction of Tunnel Boring Machine Performance Parameters Using Recurrent Neural Networks,” The Journal of the Transportation Research Board 2020, and Transportation Research Board Annual Conference (TRB 2020).
  26. M. Kuko and M. Pourhomayoun, “An Ensemble Machine Learning Method for Single and Clustered Cervical Cell Classification,” IEEE 20th International Conference on Information Reuse and Integration for Data Science, 2019.
  27. Hector Cruz, Siavash F. Aval, Keyur Dhawan, M. Pourhomayoun, Tonatiuh Rodriguez-Nikl, Mehran Mazari, “Non-Contact Surface Displacement Measurement for Concrete Samples Using Image Correlation Technique,” IEEE IPCV'19 - The 23rd Int'l Conf on Image Processing, Computer Vision, & Pattern Recognition, 2019.
  28. M. Pourhomayoun, H. Wang, M. Vahedi, H. Owens, M. Mazari, J. Smith, W. Chernicoff, “Real-Time Big Data Analytics for Traffic Monitoring and Management for Pedestrian and Cyclist Safety,” Proceeding of The International Conference on Big Data, Small Data, Linked Data and Open Data (ALLDATA 2019), 2019.
  29. L. Fisher, K. Nagrecha, M. Mooney, E. Alavi, S. Mokhtari, T. Rodriguez-Nikl, M. Mazari, M. Pourhomayoun, “Real-Time Prediction of Geological Composition using Recurrent Neural Networks and Shield Tunnel Boring Machine Data,” Transportation Research Board Annual Conference (TRB 2019).
  30. F. C. Day, M. Sarrafzadeh, M. Pourhomayoun, K. Sideris, M. A. Pfeffer, D. BellAn, “Feasibility Study of an EHR-Integrated Mobile Shared Decision Making Application,” Elsevier International Journal of Medical Informatics (IJMI), 2019.
  31. Y. Ma, Zh. Esna Ashari, M. Pedram, N. Amini, D. Tarquinio, K. Nouri-Mahdavi, M. Pourhomayoun, R. Catena, H. Ghasemzadeh, “CyclePro: A Robust Framework for Domain-Agnostic Gait Cycle Detection”, IEEE Sensors Journal (JSEN), Jan 2019.
  32. A. Kalatzis, B. Mortazavi, M. Pourhomayoun, “Interactive Dimensionality Reduction for Improving Patient Adhearence in Remote Health Monitoring,” The 2018 International Conference on Computational Science and Computational Intelligence (CSCI'18), Las Vegas, Dec 2018.
  33. J. S. Lim, H. Cruze, M. Pourhomayoun, M. Mazari, “Application of IoT for Concrete Structural Health Monitoring,” The 2018 International Conference on Computational Science and Computational Intelligence (CSCI'18), Las Vegas, Dec 2018.
  34. J. Garrido, M. Pourhomayoun, M. Mazari, “Multivariate Assessment and Spatiotemporal Visualization of Traffic Injury Frequency,” Transportation Research Board 98th Annual Conference (TRB 2019), Jan 2019, Washington, D.C.
  35. V. Saravanan, M. Pourhomayoun, M. Mazari, “A Proposed Method to Improve Highway Construction Quality Using Machine Learning,” The 2018 International Conference on Computational Science and Computational Intelligence (CSCI'18), Las Vegas, Dec 2018.
  36. K. Sawada, M. W. Clark, Z. Ye, N. Alshurafa, and M. Pourhomayoun, " Analyzing the Potential Occurrence of Osteoporosis and Its Correlation to Cardiovascular Disease Using Predictive Analytics," the International Journal On Advances in Life Sciences, vol 10 n 3&4 2018.
  37. M. R. Vahedi, K. B. MacBride, W. Wunsik, Y. Kim, C. Fong, A. J. Padilla, A. Zhong, S. Kulkarni, B. Jiang, S. Arunachalam, M. Pourhomayoun, “Predicting Glucose Levels in Patients with Type1 Diabetes Based on Physiological and Activity Data”, The 8th ACM MobiHoc2018 Workshop on Pervasive Wireless Healthcare Workshop (MobileHealth 2018), 2018.
  38. M. Kwon, M. Kuko, V. Martin, T. H. Kim, S. E. Martin, M. Pourhomayoun, “Multi-label Classification of Single and Clustered Cervical Cells Using Deep Convolutional Networks,” The 14th Int. Conference on Data Science (ICDATA’18), 2018.
  39. S. Yoo , A. Kalatzis, N. Amini, M. Pourhomayoun, “Interactive Predictive Analytics for Enhancing Patient Adherence in Remote Health Monitoring”, The 8th ACM MobiHoc2018 Workshop on Pervasive Wireless Healthcare Workshop (MobileHealth 2018), 2018.
  40. K. Sawada, M. W. Clark, Z. Ye, N. Alshurafa, and M. Pourhomayoun, “Predictive Analytics to Determine the Potential Occurrence of Genetic Disease and their Correlation: Osteoporosis and Cardiovascular Disease,” the Proceeding of The Tenth International Conference on Bioinformatics, Biocomputational Systems and Biotechnologies, 2018.
  41. H. Wang, H. Owens, J. Smith, W. Chernicoff, M. Mazari, M. Pourhomayoun, “An End-to-End Traffic Vision and Counting System Using Computer Vision and Machine Learning: The Challenges in Real-Time Processing”, Proceeding of Int. Conf. on Advances in Signal, Image & Video Processing, 2018.
  42. J. Sunthonlap, P. Nguyen, H. Wangy, M. Pourhomanyoun, Y. Zhu, Z. Ye “SAND: A Social-Aware and Distributed Scheme for Device Discovery in the Internet of Things,” International Conference on Computing, Networking and Communications (ICNC), 2018.
  43. L. Fisher, H. Yu, M. A. Mooney, M. Mazari, T. Rodriguez-Nikl, M. Pourhomayoun, “Predicting Soil Structure And Condition Using Recurrent Neural Network (RNN)” abstract at UTC-UTI Workshop, 2018.
  44. E. Sokolova, A. Nguyen, K. Gamboa, K. Lam, K. Macias,  D. Somers, H. Owens, J. Holm, M. Pourhomayoun, Parameterized Model for Mobility Project Scoring and Estimation of Benefits, ESRI-UC 2018.
  45. K. Sawada, M. W. Clark, N. Alshurafa, and M. Pourhomayoun, “Analyzing the Mutation Frequencies and Correlation of Genetic Diseases in Worldwide Populations Using Big Data Processing, Clustering, and Predictive Analytics,” International Conference on Computational Science and Computational Intelligence, 2017.
  46. S. Shim, M. Pourhomayoun, “Predicting Movie Market Revenue Using Social Media Data,”  IEEE Int. Conference on Information Reuse & Integration (IRI 2017), 2017.
  47. A. Emrani, M. Pourhomayoun, “Applying Machine Learning Techniques to Recognize Arc in Vehicle 48 Electrical Systems,” IEEE Conf. on Control and Modeling for Power Electronics (COMPEL 2017), 2017.
  48. D. Nguyen, E. Cohen, M. Pourhomayoun, N. Alshurafa, “SwallowNet: Recurrent Neural Network Detects and Characterizes Eating Patterns,” IEEE International Conference on Pervasive computing (Percom2017), 2017.
  49. M. Pourhomayoun, N. Alshurafa, F. Dabiri, C. Sideris, K. Yadav, L. Tseng, H. Ghasemzadeh, A. Nyamathi, M. Sarrafzadeh, “A Robust Remote Health Monitoring and Data Processing System for Rural Area with Limited Internet Access,” International Conference on Body Area Networks, BodyNets 2016, Italy, Dec 2016.
  50. M. Pourhomayoun, N. Alshurafa, F. Dabiri, E. Ardestani, A. Samiee, H. Ghasemzadeh, M. Sarrafzadeh, “Why Do We Need a Remote Health Monitoring System?  A Study on Predictive Analytics for Heart Failure Patients,” International Conference on Body Area Networks, BodyNets 2016, Italy, Dec 2016.
  51. Sh. Zhang, R. Alharbi, M. Pourhomayoun, N. Alshurafa, “Food Watch: Detecting and Characterizing Eating Episodes through Feeding Gestures,” International Conference on Body Area Networks, BodyNets 2016, Italy, Dec 2016 (Best Paper Award).
  52. B. Mortazavi, M. Pourhomayoun, S.I. Lee, S. Nyamathi, B. Wu, M. Sarrafzadeh, “User-Optimized Activity Recognition for Exergaming,” Elsevier Journal of Pervasive and Mobile Computing, 2016.
  53. N Alshurafa, C Sideris, M. Pourhomayoun, H Kalantarian, M Sarrafzadeh, JA Eastwood, “Remote Health Monitoring Outcome Success Prediction using Baseline and First Month Intervention Data,” IEEE journal of biomedical and health informatics, 2016.
  54. C. Sideris, M. Pourhomayoun, H. Kalantarian, M. Sarrafzadeh, “A Flexible Data-Driven Comorbidity Feature Extraction Framework,” Elsevier Journal on Computers in Biology and Medicine, 2016.
  55. H. Kalantarian, B. Mortazavi, M. Pourhomayoun, N. Alshurafa, M. Sarrafzadeh, “Probabilistic Segmentation of Time-Series Audio Signals using Support Vector Machines,” Elsevier Journal on Microprocessors and Microsystems, 2016.
  56. M. Pourhomayoun, E. Nemati, B. Mortazavi, M. Sarrafzadeh, "Context-Aware Data Analytics for Activity Recognition," International Conference on Data Analytics, DATA ANALYTICS 2015, July 19 - 24, 2015, France, (Best Paper Award).
  57. F. Day, M. Sarrafzadeh, S. Smith., M. Pourhomayoun, Sideris, K., Param, A., Ben-Hamou, J., Keeves, D., Pfeffer, M., Bell, D., "An EHR-Integrated Shared Decision Making Mobile App for Prostate Cancer Screening", American Medical Informatics Association (AMIA) 2015
  58. M. Pourhomayoun, N. Alshurafa, B. Mortazavi, H. Ghasemzadeh, K. Sideris, B. Sadeghi, M. Ong, L. Evangelista, P. Romano, A. Auerbach, A. Kimchi, M. Sarrafzadeh, "Multiple Model Analytics for Adverse Event Prediction in Remote Health Monitoring Systems," IEEE EMBS Conference on Healthcare Innovation & Point-of-Care Technologies, 2014.
  59. M. Pourhomayoun, P. Dugan, M. Popescu, and C. Clark, “Classification for Big Dataset of Bioacoustic Signals Based on Human Scoring System and Artificial Neural Network,” International Conference on Machine Learning (ICML), Atlanta, GA.
  60. M. Pourhomayoun, P. Dugan, M. Popescu, and C. Clark, “Bioacoustic Signal Classification Based on Continuous Region Features, Grid Masking Features and Artificial Neural Network,” International Conference on Machine Learning (ICML), Atlanta, GA.
  61. M. Pourhomayoun, Z. Jin and M.L. Fowler, “Accurate Localization of In-Body Medical Implants Based on Spatial Sparsity,” IEEE Transactions on Biomedical Engineering, Volume 61, Pages 590-597, 2014.
  62. H. Kalantarian, N. Alshurafa, M. Pourhomayoun, Majid Sarrafzadeh, " Power Optimization for a Wearable Devices", IEEE International Conference on Pervasive Computing and Communication (PerCom), 2015.
  63. P. Dugan, M. Pourhomayoun, Y. Shiu, A. Rice, C. Clark, “Using High Performance Computing to Explore Large Complex Bioacoustic Soundscapes: Case Study for Right Whale Acoustics”, Journal of Elsevier Procedia Computer Science, Volume 20, Pages 156–162.
  64. M. Pourhomayoun and M.L. Fowler, “Distributed Computation for Direct Position Determination,” IEEE Transactions on AES, 2014.
  65. B. Mortazavi, M. Pourhomayoun, H. Ghasemzadeh, R. Jafari, M. Sarrafzadeh, "Context-Aware Data Processing to Enhance Quality of Measurements in Wireless Health Systems - An Application to MET Calculation of Exergaming Actions", IEEE Internet Of Things Journal, 2014.
  66. M. Pourhomayoun, Z. Jin and M.L. Fowler, “Accurate Tumor Localization and Tracking in Radiation Therapy Using Wireless Body Sensor Networks,” Journal of ELSEVIER Computers in Biology and Medicine, 2014.
  67. M. Pourhomayoun, Z. Jin and M.L. Fowler, “Indoor Localization, Tracking and Fall Detection for Assistive Healthcare Based on Spatial Sparsity and Wireless Sensor Network,” International Journal of Monitoring and Surveillance Technologies Research, 2013.
  68. N. Alshurafa, J. Eastwood, J. Liu, W. Xu, M. Pourhomayoun, M. Sarrafzadeh, "Improving Compliance in Remote Health Monitoring System using Battery Optimization," IEEE Journal of Biomedical and Health Informatics (JBHI), 2014.
  69. M. Pourhomayoun, M.L. Fowler, “Cramer-Rao Bound for Frequency Estimation in Coherent Pulse Train with Unknown Pulses,” IEEE Transactions on AES, 2013.
  70. M. Pourhomayoun and M.L. Fowler, "Spatial Sparsity-Based Emitter Location: Multipath and Multiple Emitters," ACM Transaction on Sensor Networks, 2014 (Pending).
  71. N. Alshurafa, H. Kalantarian, M. Pourhomayoun, J. Liu, S. Sarin, M. Sarrafzadeh, "A Wearable Piezoelectric Sensor for Recognition of Nutrition-Intake using Spectrogram Analysis," IEEE Sensors Journal, 2014 (Pending).
  72. H. Kalantarian, N. Alshurafa, M. Pourhomayoun, S. Sarin, M. Sarrafzadeh, " Non-Invasive Detection and Classification of Food Intake using Audio Spectrograms," IEEE Sensors Journal, 2014.
  73. C. Sideris, M. Pourhomayoun, N. Alshurafa, B. Shahbazi, M. Sarrafzadeh, " Validating Severity of Condition Prediction Model built from Electronic Health Records on Remote Health Monitoring Patients", Elsevier Pervasive and Mobile Computing Journal (PMC) (Pending).
  74. P. Dugan, M. Pourhomayoun, Y. Shiu, A. Rice, C. Clark, “Using High Performance Computing to Explore Large Complex Bioacoustic Soundscapes”, Complex Adaptive Systems Conference.
  75. B. Mortazavi, M. Pourhomayoun, M. Chronley, S. I. Lee, Ch. Roberts, M. Sarrafzadeh, "Support Vector Regression for METs of Exergaming Actions", IEEE EMBS Conference on Healthcare Innovation & Point-of-Care Technologies, 2014.
  76. B. Mortazavi, M. Pourhomayoun, N. Alshurafa, S. Lee, M. Sarrafzadeh, "Determining the Single Best Axis for Exercise Repetition Recognition and Counting with SmartWatches", The 11th International Conference on Wearable and Implantable Body Sensor Networks (BSN2014), 2014.
  77. N. Alshurafa, M. Pourhomayoun, S. Nyamathi, L. Bao, B. Mortazavi, J. Eastwood, M. Sarrafzadeh, "Anti-Cheating: Detecting Self-Inflicted and Impersonator Cheaters for Remote Health Monitoring Systems with Wearable Sensors", The 11th International Conference on Wearable and Implantable Body Sensor Networks (BSN2014), 2014.
  78. H. Kalantarian, S. Sarin, N. Alshurafa, M. Pourhomayoun, M. Sarrafzadeh, "Real-Time Acoustic Classification of Food Intake," IEEE EMBS Conference on Healthcare Innovation & Point-of-Care Technologies, 2014.
  79. N. Alshurafa, J. Eastwood, M. Pourhomayoun, S. Nyamathi, J. Liu, R. Li, M. Sarrafzadeh, "A Framework for Predicting Adherence in Remote Health Monitoring Systems," Wireless Health Conf. (WH2014), 2014.
  80. C. Sideris, B. Shahbazi, M. Pourhomayoun, N. Alshurafa, M. Sarrafzadeh, "Using electronic health records to predict severity of condition for congestive heart failure patients", ACM UbiComp Workshop on Smart Health Systems and Applications (SmartHealthSys), 2014.
  81. N. Alshurafa, H. Kalantarian, M. Pourhomayoun, S. Sarin, M. Sarrafzadeh "Non-Invasive Monitoring of Nutrition using Spectrogram Analysis in a Wearable Necklace", IEEE EMBS Conference on Healthcare Innovation & Point-of-Care Technologies, 2014.
  82. B. Mortazavi, M. Pourhomayoun, S. Nyamathi, B. Wu, S. Lee, M. Sarrafzadeh, "Multiple Model Recognition for Near-Realistic Exergaming," IEEE International Conference on Pervasive Computing and Communications (PerCom), 2014 (submitted).
  83. M. Pourhomayoun, M.L. Fowler, Z. Jin, “A Novel Method for Tumor Localization and Tracking in Radiation Therapy,” IEEE Asilomar Conference on Signals, Systems, Monterey, CA, 2012.
  84. M. Pourhomayoun, Z. Jin and M.L. Fowler, “Spatial Sparsity Based Indoor Localization in Wireless Sensor Network for Assistive Healthcare Systems,” 34th IEEE International Conference of the Engineering in Medicine and Biology (EMBC2012), San Diego, CA, 2012.
  85. N. Alshurafa, J. Eastwood, W. Xu, J. Liu, M. Pourhomayoun, M. Sarrafzadeh, "Battery Optimization in Remote Health Monitoring Systems to Enhance User Adherence," International Conference on PErvasive Technologies Related to Assistive Environments (PETRA2014), May 2014.
  86. M. Pourhomayoun, M.L. Fowler and Z. Jin, “A Novel Method for Medical Implant In-Body Localization,” 34th IEEE International Conference of the Engineering in Medicine and Biology (EMBC2012), San Diego, CA, 2012.
  87. M. Pourhomayoun, M.L. Fowler and Z. Jin, “Robustness Analysis of Sparsity Based Tumor Localization under Tissue Configuration Uncertainty” IEEE Signal Processing in Medicine and Biology Symposium (SPMB12), New York, 2012.
  88. M. Pourhomayoun and M. L. Fowler, “Improving WLAN-Based Indoor Mobile Positioning Using Sparsity,” IEEE Asilomar Conference on Signals, Systems and Computers, Nov 2012.
  89. N. Alshurafa, J. Eastwood, M. Pourhomayoun, S. Nyamathi, W. Xu, J. Liu, H. Ghasemzadeh, M. Sarrafzadeh, "Remote Health Monitoring: Predicting Outcome Success based on Contextual Features," 36th IEEE International Conference of the Engineering in Medicine and Biology (EMBC2014), 2014.
  90. M. Pourhomayoun and M.L. Fowler, “Sensor Network Distributed Computation for Direct Position Determination,” IEEE Sensor Array and Multichannel Signal Processing Conference, Jun 2012.
  91. M. Popescu, P. Dugan, M. Pourhomayoun, and C. Clark, “Bioacoustic Periodic Pulse Train Signal Detection and Classification using Spectrogram Intensity Binarization and Energy Projection,” International Conference on Machine Learning (ICML), 2013.
  92. M. Pourhomayoun and M.L. Fowler, “Spatial Sparsity Based Emitter Localization,” IEEE Conference on Information Sciences and Systems (CISS2012), Princeton University, March 2012.
  93. M. Pourhomayoun and M.L. Fowler, “Cramer-Rao Lower Bounds for Estimation of Phase in LBI Based Localization Systems,” IEEE Asilomar Conference on Signals, Systems and Computers, Nov 2012.
  94. M. Pourhomayoun and M.L. Fowler, “De-Noising by Wiener Filter and Wavelet Based Methods for Emitter Localization Systems,” IEEE Conference on Information Sciences and Systems (CISS2012), Princeton University, March 2012.
  95. M. Pourhomayoun and M.L. Fowler, “An SVD Approach for Data Compression in Emitter Location Systems” IEEE Asilomar Conference on Signals, Systems and Computers, Monterey, CA, Nov 2011.
  96. M. Pourhomayoun and M.L. Fowler, “Exploiting Cross Ambiguity Function Properties for Data Compression in Emitter Location Systems,” IEEE Conference on Information Sciences and Systems, Johns Hopkins University, March 2011.
  97. M. Pourhomayoun and M.L. Fowler, “Data compression for complex ambiguity function for emitter location”, Proceedings of SPIE - Mathematics of Data/Image Coding, Compression, and Encryption, 2010.
  98. M. Pourhomayoun and M. DakhilAlian, "Improvement of Communication Protocols between Smart Card and Card Reader using ECC," 15th Iranian Conference on Electrical Engineering, 2007.