Sanjay Purushotham

News

December 2022: Paper to appear at SDM 2023 : Multi-state Survival Analysis using Pseudo value-based Deep Neural Networks
November 2022: Paper at SIGSPATIAL 2022 : VDAM: VAE based domain adaptation for cloud property retrieval from multi-satellite data
May 2022: Paper at KDD 2022 : Fair and interpretable models for survival analysis
June 2022: Paper at KDD DSHealth 2022 : FedPseudo: Pseudo value-based Deep Learning Models for Federated Survival Analysis
June 2022: Paper at KDD DSHealth 2022 : Pseudo value-based Deep Neural Networks for Multistate Survival Analysis
June 2022: Paper at ICML 2022: The 1st Workshop on Healthcare AI and COVID-19 : Thermal Face Contrastive GAN (TFC-GAN): A Framework For Visible-to-Thermal Face Translation
January 2022: Journal paper in Computer and Geosciences : A review of Earth Artificial Intelligence
December 2021: Paper at SPIE 2022: Benchmarking domain adaptation for semantic segmentation
December 2021: Paper at AAAI 2022 - Trustworthy AI for Healthcare workshop: A Pseudo Value Based Interpretable Neural Additive Model for Survival Analysis
November 2021: AAAI Fall Symposium Series paper: PseudoNAM: A pseudo value based interpretable neural additive model for survival analysis
October 2021: NeurIPS 2021 paper - Intelligent Sight and Sound: A Chronic Cancer Facial Pain Dataset
August 2021: Journal paper in Nature Scientific Reports: MedFuseNet: Attention-based Multimodal deep learning model for Visual Question Answering in the Medical Domain
May 2021: Conference paper at IEEE ICIP 2021: Generating Thermal Human Faces for Physiological Assessment using Thermal Sensor Auxiliary Labels
Feb. 2021: Paper at ISMRM 2021 Annual Meeting : Improved Outcome prediction in mild Traumatic Brain Injury using Latent Feature Extraction from Volumetric MRI
December 2020: Paper at AAAI 2021 : DeepPseudo: Pseudo Value Based Deep Learning Models for Competing Risk Analysis
October 2020: Paper at IEEE BigData 2020 : Deep Domain Adaptation based Cloud Type Detection using Active and Passive Satellite Data
September 2020: Paper at AAAI Fall Symposium Series 2020 : The Use of AI for Thermal Emotion Recognition: A Review of Problems and Limitations in Standard Design and Data
July 2020: Paper at KDD 2020 DS Health : Deep Learning for Competing Risk Analysis
July 2020: Covid-19 Paper at KDD 2020 epiDAMIK workshop :Exploratory analysis of covid-19 tweets
July 2020: Paper at KDD 2020 DeepSpatial workshop : Deep Multi-Sensor Domain Adaptation
Feburary 2020: Paper at WSDM 2020 Health Day Explainable Methods for Visual Question Answering in Medical Domain

Selected Publications

(Full publications at Google Scholar)

	Neural Interaction Transparency (NIT): Disentangling Learned Interactions for Improved Interpretability Michael Tsang, Hanpeng Liu, Sanjay Purushotham, Pavankumar Murali and Yan Liu Neural Information Processing Systems (NIPS 2018)
	Hierarchical Deep Generative Models for Multi-Rate Multivariate Time Series Zhengping Che, Sanjay Purushotham, Guangyu Li, Bo Jiang, and Yan Liu International Conference on Machine Learning (ICML 2018) (Co-first authors)
	Recurrent Neural Networks for Multivariate Time Series with Missing Values Zhengping Che, Sanjay Purushotham, Kyunghyun Cho, David Sontag and Yan Liu Nature Scientific Reports, 2018
	Benchmarking Deep Learning Models on Large Healthcare Datasets Sanjay Purushotham, Chuizheng Meng, Zhengping Che, and Yan Liu Journal of Biomedical Informatics, 2018 (JBI 2018)
	Association of tumor differentiation grade and survival of women with squamous cell carcinoma of the uterine cervix Koji Matsuo, Rachel S Mandelbaum, Hiroko Machida, Sanjay Purushotham, Brendan H Grubbs, Lynda D Roman and Jason D Wright Journal of Gynecologic Oncology, 2018 (JGO 2018)
	Deep Multi-Instance Learning for Concept Annotation from Medical Time Series Data Sanjay Purushotham, Zhengping Che, Bo Jiang, Yan Liu NIPS Machine Learning for Health Workshop, 2017 (NIPS ML4H 2017)
	Variational Recurrent Adversarial Deep Domain Adaptation Sanjay Purushotham, Wilka Carvalho, Tanachat Nilanon and Yan Liu International Conference on Learning Representations (ICLR 2017) (*Co-first authors)
	Measuring and Predicting Tag Importance for Image Retrieval Shangwen Li, Sanjay Purushotham, Chen Chen, Yuzhuo Ren and C.-C. Jay Kuo IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017
	A Pilot Study in using Deep-learning to Predict limited Life-expectancy in Women with Recurrent Cervical Cancer Koji Matsuo, Sanjay Purushotham, Aida Moeini, Guangyu Li, Hiroko Machida, Yan Liu and Lynda D Roman American Journal of Obstetrics and Gynecology (AJOG), 2017
	Time-series Feature Learning with Applications to Healthcare Domain (Book Chapter) Zhengping Che, Sanjay Purushotham, David Kale, Wenzhe Li, Mohammad Taha Bahadori, Robinder Khemani and Yan Liu Mobile Health: Sensors, Analytic Methods, and Applications, 2017
	Mining Human Mobility to Quantify Performance Status Minh Nguyen, Zaki Hasnain, Sanjay Purushotham, Luciano Nocera, Paul Newton and Cyrus Shahabi IEEE International Conference on Data Mining (ICDM 2017)
	Personalized Group Recommender Systems for Location and Event Based Social Networks Sanjay Purushotham and C.-C.Jay Kuo ACM Transactions on Spatial Algorithms and Systems (TSAS), 2016
	Variational Adversarial Deep Domain Adaptation for Healthcare Time Series Analysis Sanjay Purushotham, Wilka Carvalho and Yan Liu NIPS Machine Learning for Healthcare Workshop (NIPS 2016)
	m-TSNE: A Framework for Visualizing High-Dimensional Multivariate Time Series Minh Nguyen, Sanjay Purushotham, Hien To and Cyrus Shahabi AMIA 2016 Workshop on Visual Analytics in Healthcare (AMIA 2016)
	Interpretable Deep Models for ICU Outcome Prediction Zhengping Che, Sanjay Purushotham, Robinder Khemani, and Yan Liu Proceedings of the American Medical Informatics Assocation Annual Symposium, 2016 (AMIA 2016)
	Normal / Abnormal Heart Sound Recordings Classification Using Deep Recurrent Neural Network Tanachat Nilanon, Sanjay Purushotham and Yan Liu Proceedings of the Computing in Cardiology, 2016 (CinC 2016)
	Distilling Knowledge from Deep Networks with Applications to Computational Phenotyping Zhengping Che, Sanjay Purushotham and Yan Liu Data Science Learning and Applications to Biomedical and Health Sciences Workshop, New York Academy of Sciences, 2016
	Distilling Knowledge from Deep Networks with Applications to Healthcare Domain Zhengping Che, Sanjay Purushotham and Yan Liu arXiv preprint arXiv:1512.03542, 2015 (extended paper of NIPS-MLHC 2015)
	Knowledge Based Factorized High Order Sparse Learning Models Sanjay Purushotham, Martin Renqiang Min, C.-C. Jay Kuo and Mark Gerstein NIPS 2015, Machine Learning in Computational Biology (MLCB) Workshop, Montreal, Canada, 2015 (NIPS 2015)
	Distilling Knowledge from Deep Networks with Applications to Phenotype Discovery Zhengping Che, Sanjay Purushotham and Yan Liu NIPS 2015 Workshop on Machine Learning in Healthcare (MLHC), Montreal, Canada, 2015 (NIPS 2015)
	Efficient Spatio-Temporal Sampling via Low-rank Tensor Sketching Qi (Rose) Yu, Sanjay Purushotham and Yan Liu NIPS Time Series Workshop 2015, Montreal, Canada, 2015 (NIPS 2015)
	Modeling Group Dynamics for Personalized Group-Event Recommendation Sanjay Purushotham and C.-C. Jay Kuo 2015 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction, Washington DC, USA, 2015 (SBP 2015)
	Studying User Influence in Personalized Group Recommenders in Location Based Social Networks Sanjay Purushotham and C.-C. Jay Kuo NIPS 2014, Personalization: Methods and Applications Workshop, Montreal, Canada, 2014 (NIPS 2014)
	Collaborative Group-Activity Recommendation in Location-Based Social Networks Sanjay Purushotham, Junaith Shahabdeen, Lama Nachman and C.-C. Jay Kuo 3rd ACM SIGSPATIAL GeoCrowd, Dallas, Texas, USA, 2014 (SIGSPATIAL 2014) (Best Paper Award)
	Factorized Sparse Learning Models with Interpretable High Order Feature Interactions Sanjay Purushotham, Martin Renqiang Min, C.-C. Jay Kuo, Rachel Ostroff 20th ACM SIGKDD International Conference on Knowledge Discovery and Data mining, New York, USA, 2014 (KDD 2014)
	Collaborative Topic Regression with Social Matrix Factorization for Recommendation Systems Sanjay Purushotham, Yan Liu and C.-C. Jay Kuo 29th International Conference on Machine Learning, Edinburgh, Scotland, 2012 (ICML 2012)
	Hierarchical Bag-of-Words Model for Joint Multi-View Object Representation and Classification Xiang Fu, Sanjay Purushotham, Daru Xu, Jian Li and C.-C. Jay Kuo APSIPA Annual Summit & Conference, Hollywood, USA, 2012 (APSIPA 2012)
	Picture-in-Picture Copy Detection Using Spatial Coding Techniques Sanjay Purushotham, Qi Tian and C.-C. Jay Kuo ACM Multimedia, AIEMPro Workshop, Scottsdale, Arizona, USA, 2011 (ACM MM 2011)
	Video Genre Inference based on Camera Capturing Models, (Book Chapter) Ping-Hao Wu, Sanjay Purushotham and C.-C. Jay Kuo Chapter 7 in Video Search and Mining, Studies in Computational Intelligence, Vol. 287/2010
	Separation of Professional and Amateur Video in Large Video Collections Ping-Hao Wu, Tanaphol Thaipanich, Sanjay Purushotham and C.-C. Jay Kuo IEEE Pacific-Rim Conf. on Multimedia, Bangkok, Thailand, Dec. 2009 (PCM 2009)

Posters and Demo

Predicting Survival of mCRPC Patients Aastha, Sanjay Purushotham, Paymaneh Malihi, Yan Liu, and Peter Kuhn Ming Hsieh Institute Symposium, University of Southern California, 2018
Medical Time Series to Concepts Sanjay Purushotham, Bo Jiang, Zhengping Che and Yan Liu SoCal Machine Learning Symposium (SCMLS 2017)
Variational Adversarial Deep Domain Adaptation for Healthcare Time Series Analysis Sanjay Purushotham, Wilka Carvalho and Yan Liu SoCal Machine Learning Symposium (SCMLS 2016) (Oral and Poster) (Best Poster Runnerup Award)
Distilling Knowledge from Deep Networks with Applications to Computational Phenotyping Zhengping Che, Sanjay Purushotham and Yan Liu Computer Science PhD Day, University of Southern California, USA, 2016
Measuring and Predicting Tag Importance for Image Retrieval Shangwen Li, Sanjay Purushotham, Chen Chen, Yuzhuo Ren and C.-C. Jay Kuo 6th Annual Ming Hsieh Department of Electrical Engineering Research Festival, USA, 2015
Factorized Sparse Learning Models with Interpretable High Order Feature Interactions Sanjay Purushotham, Martin Renqiang Min, C.-C. Jay Kuo and Rachel Ostroff 9th Annual Machine Learning Symposium, New York Academy of Sciences, New York, USA, 2015
Factorized Sparse Learning Models with Interpretable High Order Feature Interactions Sanjay Purushotham, Martin Renqiang Min, C.-C. Jay Kuo and Rachel Ostroff AISTATS/MLSS Poster, Reykjavik, Iceland, 2014
Collaborative Topic Regression with Social Matrix Factorization for Recommendation Systems Sanjay Purushotham, Yan Liu and C.-C. Jay Kuo Google PhD Summit, Los Angeles, USA, 2013
Collaborative Topic Regression with Social Matrix Factorization for Recommender Systems Sanjay Purushotham, Yan Liu and C.-C. Jay Kuo 3rd Annual Ming Hsieh Department of Electrical Engineering Research Festival, USA, 2013
Two Parallel Solvers for Lasso Sanjay Purushotham and Tomer Levinboim Scientific and Visualization course, USC, 2012 (Best Poster Award)
Group-Activity Recommendation Sanjay Purushotham, Junaith Shahabdeen and Lama Nachman Intel Labs CountryFair Research Festival, Oregon, USA, 2012 (Poster & Demo)
Socially Aware Activity: Group Recommendations Sanjay Purushotham, Junaith Shahabdeen and Lama Nachman Intel's Annual IDF Festival in San Francisco, CA, 2012 (Poster & Demo)
Picture-in-Picture Copy Detection Using Spatial Coding Techniques Sanjay Purushotham, Qi Tian and C.-C. Jay Kuo 2nd Annual Ming Hsieh Department of Electrical Engineering Research Festival, USA, 2012

Predicting Survival of mCRPC Patients

Aastha, Sanjay Purushotham, Paymaneh Malihi, Yan Liu, and Peter Kuhn
Ming Hsieh Institute Symposium, University of Southern California, 2018

Medical Time Series to Concepts

Sanjay Purushotham, Bo Jiang, Zhengping Che and Yan Liu
SoCal Machine Learning Symposium (SCMLS 2017)

Variational Adversarial Deep Domain Adaptation for Healthcare Time Series Analysis

Sanjay Purushotham, Wilka Carvalho and Yan Liu
SoCal Machine Learning Symposium (SCMLS 2016) (Oral and Poster) (Best Poster Runnerup Award)

Distilling Knowledge from Deep Networks with Applications to Computational Phenotyping

Zhengping Che, Sanjay Purushotham and Yan Liu
Computer Science PhD Day, University of Southern California, USA, 2016

Measuring and Predicting Tag Importance for Image Retrieval

Shangwen Li, Sanjay Purushotham, Chen Chen, Yuzhuo Ren and C.-C. Jay Kuo
6th Annual Ming Hsieh Department of Electrical Engineering Research Festival, USA, 2015

Factorized Sparse Learning Models with Interpretable High Order Feature Interactions

Sanjay Purushotham, Martin Renqiang Min, C.-C. Jay Kuo and Rachel Ostroff
9th Annual Machine Learning Symposium, New York Academy of Sciences, New York, USA, 2015

Factorized Sparse Learning Models with Interpretable High Order Feature Interactions

Sanjay Purushotham, Martin Renqiang Min, C.-C. Jay Kuo and Rachel Ostroff
AISTATS/MLSS Poster, Reykjavik, Iceland, 2014

Collaborative Topic Regression with Social Matrix Factorization for Recommendation Systems

Sanjay Purushotham, Yan Liu and C.-C. Jay Kuo
Google PhD Summit, Los Angeles, USA, 2013

Collaborative Topic Regression with Social Matrix Factorization for Recommender Systems

Sanjay Purushotham, Yan Liu and C.-C. Jay Kuo
3rd Annual Ming Hsieh Department of Electrical Engineering Research Festival, USA, 2013

Two Parallel Solvers for Lasso

Sanjay Purushotham and Tomer Levinboim
Scientific and Visualization course, USC, 2012 (Best Poster Award)

Group-Activity Recommendation

Sanjay Purushotham, Junaith Shahabdeen and Lama Nachman
Intel Labs CountryFair Research Festival, Oregon, USA, 2012 (Poster & Demo)

Socially Aware Activity: Group Recommendations

Sanjay Purushotham, Junaith Shahabdeen and Lama Nachman
Intel's Annual IDF Festival in San Francisco, CA, 2012 (Poster & Demo)

Picture-in-Picture Copy Detection Using Spatial Coding Techniques

Sanjay Purushotham, Qi Tian and C.-C. Jay Kuo
2nd Annual Ming Hsieh Department of Electrical Engineering Research Festival, USA, 2012

News

December 2022: Paper to appear at SDM 2023 : Multi-state Survival Analysis using Pseudo value-based Deep Neural Networks

November 2022: Paper at SIGSPATIAL 2022 : VDAM: VAE based domain adaptation for cloud property retrieval from multi-satellite data

May 2022: Paper at KDD 2022 : Fair and interpretable models for survival analysis

June 2022: Paper at KDD DSHealth 2022 : FedPseudo: Pseudo value-based Deep Learning Models for Federated Survival Analysis

June 2022: Paper at KDD DSHealth 2022 : Pseudo value-based Deep Neural Networks for Multistate Survival Analysis

June 2022: Paper at ICML 2022: The 1st Workshop on Healthcare AI and COVID-19 : Thermal Face Contrastive GAN (TFC-GAN): A Framework For Visible-to-Thermal Face Translation

January 2022: Journal paper in Computer and Geosciences : A review of Earth Artificial Intelligence

December 2021: Paper at SPIE 2022: Benchmarking domain adaptation for semantic segmentation

December 2021: Paper at AAAI 2022 - Trustworthy AI for Healthcare workshop: A Pseudo Value Based Interpretable Neural Additive Model for Survival Analysis

November 2021: AAAI Fall Symposium Series paper: PseudoNAM: A pseudo value based interpretable neural additive model for survival analysis

October 2021: NeurIPS 2021 paper - Intelligent Sight and Sound: A Chronic Cancer Facial Pain Dataset

August 2021: Journal paper in Nature Scientific Reports: MedFuseNet: Attention-based Multimodal deep learning model for Visual Question Answering in the Medical Domain

May 2021: Conference paper at IEEE ICIP 2021: Generating Thermal Human Faces for Physiological Assessment using Thermal Sensor Auxiliary Labels

Feb. 2021: Paper at ISMRM 2021 Annual Meeting : Improved Outcome prediction in mild Traumatic Brain Injury using Latent Feature Extraction from Volumetric MRI

December 2020: Paper at AAAI 2021 : DeepPseudo: Pseudo Value Based Deep Learning Models for Competing Risk Analysis

October 2020: Paper at IEEE BigData 2020 : Deep Domain Adaptation based Cloud Type Detection using Active and Passive Satellite Data

September 2020: Paper at AAAI Fall Symposium Series 2020 : The Use of AI for Thermal Emotion Recognition: A Review of Problems and Limitations in Standard Design and Data

July 2020: Paper at KDD 2020 DS Health : Deep Learning for Competing Risk Analysis

July 2020: Covid-19 Paper at KDD 2020 epiDAMIK workshop :Exploratory analysis of covid-19 tweets

July 2020: Paper at KDD 2020 DeepSpatial workshop : Deep Multi-Sensor Domain Adaptation

Feburary 2020: Paper at WSDM 2020 Health Day Explainable Methods for Visual Question Answering in Medical Domain

Selected Publications

Posters and Demo

Predicting Survival of mCRPC Patients

Medical Time Series to Concepts

Variational Adversarial Deep Domain Adaptation for Healthcare Time Series Analysis

Distilling Knowledge from Deep Networks with Applications to Computational Phenotyping

Measuring and Predicting Tag Importance for Image Retrieval

Factorized Sparse Learning Models with Interpretable High Order Feature Interactions

Factorized Sparse Learning Models with Interpretable High Order Feature Interactions

Collaborative Topic Regression with Social Matrix Factorization for Recommendation Systems

Collaborative Topic Regression with Social Matrix Factorization for Recommender Systems

Two Parallel Solvers for Lasso

Group-Activity Recommendation

Picture-in-Picture Copy Detection Using Spatial Coding Techniques

Teaching

IS 427: Introduction to Artificial Intelligence

IS 460/660: Healthcare Informatics-I

IS 777: Statistical Learning for Data Analytics

IS 698/800: Selected Topics in Machine Learning: Advanced deep learning techniques

CSCI 567: Machine Learning

EE 569: Digital Image Processing

EE 669: Data Compression

CSCI 686: Big Data Analytics