Robert W. H. Fisher

Education

Ph.D. in Machine Learning, Carnegie Mellon University, 2016.

M.S. in Machine Learning, Carnegie Mellon University, 2012.

B.S. in Computer Science, Polytechnic Institute of NYU, Summa Cum Laude, 2005-2009.

Research Interests

Machine Learning

Weakly Labeled Data

Discourse Structure Analysis

Spectral Optimization

Sensor processing for audio, video, accelerometers, etc

Awards and Honors

Teaching Assistant of the Year for Carnegie Mellon University’s Machine Learning Department (2012)

National Science Foundation Graduate Fellow, 2010-2014

Recipient of American Rewards for College Scientists (ARCS) foundation award

Lemelson Scholar, 2007-2009

Recipient of Myron M. Rosenthal academic achievement award, 2007

Member of Honors College, Polytechnic University of NYU

Teaching & Work Experience

Post-doctoral fellow in the Institute for Complex Engineered Systems at Carnegie Mellon University

Supervised five separate undergraduate scholars as part of the Quality of Life Technology Research Experience for Undergraduates

PhD Software Engineering Internship with Google Pittsburgh, working with the shopping catalog quality team

Teaching Assistant, Multimedia Databases and Data Mining (15-826). Carnegie Mellon University. Course taught by Christos Faloutsos.

Teaching Assistant, Machine Learning (10-601). Carnegie Mellon University. Course taught by Roni Rosenfeld.

Guest lecturer, Design and Analysis of Algorithms (CS6033). Polytechnic Institute of NYU. Hosted by Boris Aronov.

Guest lecturer, Machine Learning (CS6923). Polytechnic Institute of NYU. Hosted by Lisa Hellerstein.

Selected Publications

Robert Fisher, Asim Smailagic, Reid Simmons, and Kimitake Mizobe. Using Latent Variable Autoregression to Monitor the Health of Individuals with Congestive Heart Failure. 15th International Conference on Machine Learn- ing and Applications (ICMLA). Anaheim, 2016. [PDF]

Doctoral Thesis: Exploring Weakly Labeled Data Across the Noise-Bias Spectrum [PDF]

Robert Fisher, and Reid Simmons. Weakly Supervised Learning of Dialogue Structure in MOOC Forum Threads. 14th International Conference on Machine Learning and Applications (ICMLA). Miami, 2015. [PDF]

Priyam Parashar, Robert Fisher, Reid Simmons, Manuela Veloso, and Joydeep Biswas. Learning Context-based Outcomes for Mobile Robots in Unstructured Indoor Environments. 14th International Conference on Machine Learning and Applications (ICMLA). Miami, 2015. [PDF]

Robert Fisher, and Reid Simmons. Spectral Semi-Supervised Discourse Relation Classification. 53rd Annual Meeting of the Association for Computational Linguistics (ACL). Beijing, China, July 2015. [PDF]

Robert Fisher, Reid Simmons, Cheng-Shiu Chung, Rory Cooper, Garrett Grindle, Annmarie Kelleher, Hsinyi Liu, and Yu Kuang Wu. Spectral Machine Learning for Predicting Power Wheelchair Exercise Compliance. 21st International Symposium on Methodologies for Intelligent Systems. Roskilde, Denmark, June 2014. [PDF]

Robert Fisher, and Reid Simmons. Understanding Language in Education with Contextual Information and Discourse Structure. 3rd Workshop on Intelligent Support for Learning in Groups (ISLG). International Conference on Intelligent Tutoring Systems (ITS). Hawaii, June 2014. [PDF]

Robert Fisher, Thomas Kollar, and Reid Simmons. Building and Learning from a Contextual Knowledge Base for a Personalized Physical Therapy Coach. Workshop on Robot Learning. International Conference on Machine Learning (ICML). Atlanta, June 2013. IEEE. [PDF]

Robert Fisher, and Reid Simmons. Active semi-supervised learning to utilize human oracles. Master’s Thesis. Carnegie Mellon University, Machine Learning Department. 2012. [PDF]

Robert Fisher, and Reid Simmons. Smartphone interruptibility using density-weighted uncertainty sampling with reinforcement learning. Proceedings of the Tenth Annual International Conference on Machine Learning and Applications (ICMLA). Hawaii, December 2011. IEEE. [PDF]

Chi Zhang, Robert Fisher, and Joel Wein. I Want to Go Home: Empowering the Lost Mobile Device. Proceedings of the Sixth IEEE International Conference on Wireless and Mobile Computing. Niagra Falls, October 2010. [PDF]

Robert Fisher, Dmitriy Drusvyatskiy, Joel Wein, and Cliff Stein. Scheduling Tasks on Parallel Machines with Network-Based Restrictions. Proceedings of the International Symposium on Combinatorial Optimization 2008. Warwick, UK 2008. [PDF]

Selected Talks

In-Context: Enabling Environmental Awareness on the Mobile Device, Machine Learning Lunch Seminar at CMU. Sponsored by Yahoo! Research

Other work

Here is an example of some work in activity recognition I have done