I am a third year PhD student in B. Thomas Golisano College of Computing and Information Sciences at Rochester Institute of Technology. I am working as a research assistant at Computational Biomedicine Lab (CBL) which is directed by my advisor, Dr. Linwei Wang. My primary research interest is in learning disentangled representation in generative models. I am currently working to disentangle inter-subject variations in biomedical images and signals.

TIMELINE EVENTS

August 2019 Our journal paper "Sequential Factorized Autoencoder for Localizing the Origin of Ventricular Activation From 12-Lead Electrocardiograms" is accepted in IEEE Transactions on Biomedical Engineering.
August 2019 Our paper "Improving Disentangled Representation Learning with the Beta Bernoulli Process" is accepted in ICDM 2019.
June 2019 Our paper "Semi-Supervised Learning by Disentangling and Self-Ensembling over Stochastic Latent Space" is accepted in MICCAI 2019.
Summer 2019 Internship at Verisk AI Lab as AI/ML Research Intern.
December 2018 Presented poster at BNP@NeurIPS and SOCML (highly recommended "unconference").
November 2018 Two papers accepted in ML4H@NeurIPS and BNP@NeurIPS.
Summer 2018 Mentor for Research Experience for Undergraduates (NSF-REU) program at RIT for the project "Multi-modal sensing and quantification of atypical attention in autism spectrum disorder."
November 2017 Our paper "Learning disentangled representation from 12-lead electrograms: application in localizing the origin of Ventricular Tachycardia" was accepted in the Health Intelligence Workshop, AAAI 2018.
June 2017 Our paper "Automatic Coordinate Prediction of the Exit of Ventricular Tachycardia from 12-lead Electrocardiogram" was accepted to CinC 2017. The paper was selected as a semi-finalist for Rosanna Degani Young Investigator Award.
Summer 2017 Mentor for Research Experience for Undergraduates (NSF-REU) program at RIT for the project "Attention and behavior of students in online vs. face-to-face learning contexts."
May 2017 Successfully defended the Ph.D. Research Potential Assesment.
May 2017 Our paper "Disentangling Inter-Subject Variations: Automatic Localization of Ventricular Tachycardia Origin from 12-Lead Electrocardiograms" was accepted to ISBI 2017.
August 2016 Joined Rochester Institute of Technology for Ph.D. in Computing and Information Sciences.

RESEARCH WORKS

    2019

    Prashnna K. Gyawali, B. Milan Horacek, John Sapp and Linwei Wang. "Sequential Factorized Autoencoder for Localizing the Origin of Ventricular Activation From 12-Lead Electrocardiograms". IEEE Transacations on Biomedical Engineering. (TBE).

    Prashnna K. Gyawali, Zhiyuan Li, Cameron Knight, Sandesh Ghimire, B. Milan Horacek, John Sapp and Linwei Wang. "Improving Disentangled Representation Learning with the Beta Bernoulli Process". IEEE International Conference on Data Mining (ICDM-19).

    Prashnna K. Gyawali*, Zhiyuan Li*, Sandesh Ghimire, and Linwei Wang. "Semi-Supervised Learning by Disentangling and Self-Ensembling over Stochastic Latent Space". International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI-19). * equal contribution [Code]

    Sandesh Ghimire, Prashnna K. Gyawali, Jwala Dhamala, John Sapp, B. Milan Horacek, and Linwei Wang. "Improving Generalization of Deep Networks for Inverse Reconstruction of Image Sequences". International Conference on Information Processing in Medical Imaging (IPMI-19).

    2018

    Prashnna K. Gyawali, Cameron Knight, Sandehs Ghimire, John Sapp, B. Milan Horacek and Linwei Wang. "Deep Generative Model with Beta Bernoulli Process for Modeling and Learning Confounding Factors". All of Bayesian Nonparametric workshop at NeurIPS 2018 (BNP@NeurIPS 2018).

    Sandesh Ghimire, Jwala Dhamala, Prashnna K. Gyawali, John Sapp, B. Milan Horacek and Linwei Wang. "Generative Modeling and Inverse Imaging of Cardiac Transmembrane Potential". International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI-18) (also MLH4@NeurIPS 2018).

    Prashnna K. Gyawali, B. Milan Horacek, John Sapp, and Linwei Wang. "Learning disentangled representation from 12-lead electrocardiograms: application in localizing the origin of Ventricular Tachycardia". Health Intelligence Workshop, 32nd AAAI Conference on Artificial Intelligence (AAAI-18). [Code]

    2017

    Prashnna K. Gyawali, Shuhang Chen, Huafeng Liu, B. Milan Horacek, John Sapp and Wang L. "Automatic Coordinate Prediction of the Exit of Ventricular Tachycardia from 12-lead Electrocardiogram". Computing in Cardiology (CinC-17).

    Erin Coppola, Prashnna K. Gyawali, Nihar Vanjara, Dan Giaime and Linwei Wang. "Atrial Fibrillation Classification from a Short Single Lead ECG Recording Using Hierarchical Classifier". Computing in Cardiology (CinC-17).

    Shuhang Chen, Prashnna K. Gyawali, Huafeng Liu, B. Milan Horacek, John Sapp and Linwei Wang. "Disentangling inter-subject variations: Automatic localization of ventricular tachycardia from 12-lead electrocardiograms". IEEE International Symposium on Biomedical Imaging (ISBI-17).

    2015

    Shailesh Acharya, Ashok K. Pant and Prashnna K. Gyawali. "Deep learning based large scale handwritten Devnagari character recognition". IEEE International Conference on Software, Knowledge, Information Management and Applications (SKIMA-15).   [Dataset]

    Ashok K. Pant, Prashnna K. Gyawali and Shailesh Acharya. "Automatic Nepali Number Plate Recognition with Support Vector Machines". IEEE International Conference on Software, Knowledge, Information Management and Applications (SKIMA).  [Dataset]