I am a fifth-year graduate student in the MS/Ph.D. program in Computer Science at the University of Massachusetts Amherst and a member of Dr. Shlomo Zilberstein's Resource Bounded Reasoning (RBR) Lab. During the summer of 2015, I was a visiting researcher at the University of Tokyo in Dr. Alex Fukunaga's laboratory. Below I provide some brief information about my research and myself, and you can click on the bracketed phrase [...] next to each section title for more elaborate details.
M.S. Computer Science - University of Massachusetts Amherst (February 2016)B.S. Computer Science with Honors - Wake Forest University (May 2012)B.S. Mathematics with Honors - Wake Forest University (May 2012)
2017 Educational Advances in Artificial Intelligence (EAAI) New and Future Educator Program Award Recipient2015 National Science Foundation East Asia and Pacific Summer Institutes (NSF EAPSI) Fellowship Recipient / Japan Society for the Promotion of Science (JSPS) Summer Research Fellow2014 National Science Foundation Graduate Research Fellowship Program (NSFGRFP) Honorable Mention2013 National Science Foundation Graduate Research Fellowship Program (NSFGRFP) Honorable Mention
My research interests lie at the intersection of various areas including: artificial intelligence planning; plan, activity, and intent recognition; human-computer/robot interaction; topic modeling; knowledge representation; and statistical-relational methods. The broad focus of my research is artificial intelligence for human-computer/robot interaction, aiming to develop systems that adaptively interact with human users through understanding their actions in the environment. My approaches to this are very interdisciplinary based on my wide range of interests.
I am a member of the Resource Bounded Reasoning (RBR) Lab run by Dr. Shlomo Zilberstein at the University of Massachusetts Amherst. During the summer of 2015, I was a visiting researcher in Dr. Alex Fukunaga's laboratory at the University of Tokyo. I was also an original member of the STatistical Relational Artitificial Intelligence Team (STRAIT) run by Dr. Sriraam Natarajan at the Wake Forest Baptist Health medical center (the lab is now at Indiana University Bloomington and named the Indiana University Statistical Relational AI (IU STARAI) Team). My current projects are listed below; please feel free to click on any of them for some more details. For past projects, please click [Past Projects] above.
|Project Title||Brief Description||Advisors and Collaborators|
|Generalized Plan and Activity Recognition Models||Developing domain-inspecific models for integrated plan and activity recognition tasks||Dr. Shlomo Zilberstein, Hee-Tae Jung, Dr. Roderic Grupen, and Dr. Hanna Wallach|
|Integrated Planning and Plan Recognition||Using classical planning techniques to integrate plan recognition and planning tasks||Alex Fukunaga, Dr. Shlomo Zilberstein, and Shuuwa Miura|
|Learning Physical Therapy by Demonstration||Developing a framework for teletherapy where robots learn physical therapists' strategies||Hee-Tae Jung, Dr. Roderic Grupen, Takeshi Takahashi, and Jay Ming Wong|
|Restating the Collatz Conjecture||Insight into an unsolved math problem by utilizing properties of the sequences of integers it generates to find equivalent problems||Dr. Stephen Robinson, Dr. Jeremy Rouse, and Marvin Jones|
Below is a list of recent publications that I co-authored. Click [Full List] above for a list of all publications. Public copies will be withheld until the publications are publicly available from the respective venue.
Different fields of research have different venues for publication which can lead to confusion in interdisciplinary work. Click here for information about how various fields publish their findings.
Eaton, Eric; Koenig, Sven; Schulz, Claudia; Maurelli, Francesco; Lee, John; Eckroth, Joshua; Crowley, Mark; Freedman, Richard G.; Cardona-Rivera, Rogelio E.; Machado, Tiago; and Williams, Tom. "Blue Sky Ideas in Artificial Intelligence Education from the EAAI 2017 New and Future Educator Program." AI Matters, In press, 2017. Contributed the subarticle titled "Making AI Concepts More Accessible." [pdf coming soon!]
Freedman, Richard G. and Zilberstein, Shlomo. "Integration of Planning with Recognition for Responsive Interaction Using Classical Planners." Proceedings of the Thirty-first AAAI Conference on Artificial Intelligence, In Press, 2017. [pdf coming soon!]
Freedman, Richard G. and Zilberstein, Shlomo. "Safety in AI-HRI: Challenges Complementing User Experience Quality." The AAAI Fall Symposium Series: Artificial Intelligence for Human-Robot Interaction, p. 42-45, 2016. [pdf]
Freedman, Richard G. and Zilberstein, Shlomo. "Using Metadata to Automate Interpretations of Unsupervised Learning-Derived Clusters." Proceedings of the First Workshop on Human is More Than a Labeler, 2016. [pdf]
Freedman, Richard G.. "Integrating Planning and Recognition to Close the Interaction Loop." Doctoral Consortium for the Twenty-Sixth International Conference on Automated Planning and Scheduling, 2016. [pdf]
Freedman, Richard G.. "Integrating Planning and Recognition to Close the Interaction Loop." Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016. (Extended Abstract for Doctoral Consortium) [pdf]
Freedman, Richard G. and Fukunaga, Alex. "Integration of Planning with Plan Recognition Using Classical Planners (Extended Abstract)." Artificial Intelligence for Human-Robot Interaction: Papers from the AAAI Fall Symposium, p. 48-50, 2015. [pdf]
Freedman, Richard G.; Jung, Hee-Tae; and Zilberstein, Shlomo. "Temporal and Object Relations in Unsupervised Plan and Activity Recognition." Artificial Intelligence for Human-Robot Interaction: Papers from the AAAI Fall Symposium, p. 51-59, 2015. [pdf]
Freedman, Richard G. and Zilberstein, Shlomo. "Automated Interpretations of Unsupervised Learning-Derived Clusters for Activity Recognition." Workshop on Learning for Human-Robot Collaboration, 2015. [pdf] (updated version presented at the BeyondLabeler 2016 Workshop paper)
Jung, Hee-Tae; Freedman, Richard G.; Takahashi, Takeshi; Wong, Jay-Ming; Zilberstein, Shlomo; Grupen, Roderic A.; and Choe, Yu-Kyong. "Adaptive Therapy Strategies: Efficacy and Learning Framework." Proceedings of the IEEE/RAS-EMBS International Conference on Rehabilitation Robotics, 2015. [pdf]
Jung, Hee-Tae; Freedman, Richard G.; Foster, Tammie; Choe, Yu-Kyong; Zilberstein, Shlomo; and Grupen, Roderic A. "Learning Therapy Strategies from Demonstration Using Latent Dirichlet Allocation." Proceedings of the Twentieth International Conference on Intelligent User Interfaces, p. 432-436, 2015. [pdf]
Freedman, Richard G.; Jung, Hee-Tae; and Zilberstein, Shlomo. "Temporal and Object Relations in Plan and Activity Recognition for Robots Using Topic Models." Artificial Intelligence for Human-Robot Interaction: Papers from the AAAI Fall Symposium (Technical Report FS-14-01), p. 70-72, 2014. [pdf]
Freedman, Richard G.; Jung, Hee-Tae; Grupen, Roderic A.; and Zilberstein, Shlomo. "How Robots Can Recognize Activities and Plans Using Topic Models." Artificial Intelligence and Robotics (AIRob): Papers Presented at the Twenty-Eighth AAAI Conference on Artificial Intelligence (Technical Report WS-14-01), p. 22-28, 2014. [pdf (extended version of the ICAPS 2014 Paper)]
Freedman, Richard G.; Jung, Hee-Tae; and Zilberstein, Shlomo. "Plan and Activity Recognition from a Topic Modeling Perspective." Proceedings of the Twenty-Fourth International Conference of Automated Planning and Scheduling (ICAPS), p. 360-364, 2014. [pdf] [talk]
Freedman, Richard G. and Robinson, Stephen B. "A Restatement of the Collatz Conjecture with Insights into Its Orbits Using a New Discrete Dynamical System." To be published in Pi Mu Epsilon Journal. [pdf coming soon!]
Freedman, Richard G.; Guo, Jingyi; Turkett, William H.; Pauca, V. Paúl. "Hierarchical Modeling to Facilitate Personalized Word Prediction for Dialogue." Plan, Activity, and Intent Recognition: Papers from the AAAI 2013 Workshop, p. 2-9, 2013. [pdf with fixed figures (some edges were missing in the models)]
Freedman, Richard G.; de Salvo Braz, Rodrigo; Bui, Hung; Natarajan, Sriraam. "Initial Empirical Evaluation of Anytime Lifted Belief Propagation." International Workshop on Statistical Relational AI, 2012. [pdf]
Due to the research opportunities I was fortunate to have as an undergraduate student, I strongly believe in undergraduate involvement in research. Considering the life-changing impact it had on me, I want to make sure that other undergraduate students have a chance to try it in case it would really interest them. There seem to be very few chances for undergraduate students to do research outside of REU Programs and institutions with small graduate student bodies.
When first starting my undergraduate career, I was planning to pursue the videogame industry. I was drawn to their development by the blend of mathematics and computer science needed to make them, the creativity behind experimenting with unique play mechanics and designing the story/characters/places/etc., and the smiles that they brought to so many faces when people played. Believe it or not, research also has the blend of computer science with mathematics as well as many other areas of study, creativity to bring our dreams and imaginations into reality, and the power to make many people smile. Additionally, research provides an opportunity to explore the unknown and try to develop an understanding for that which we do not yet completely understand.
In the Spring 2017 semester, I will be a co-instructor for Artificial Intelligence (CMPSCI 383) with Kris[tina] Fedorenko at UMass Amherst. The current version of the course website is available here.
In the Fall 2015 semester, I was the instructor of a first-year seminar (CMPSCI 191) entitled "Introduction to Computational Thinking through the History of Videogames" at UMass Amherst.
In the Spring 2015 semester, I was the teaching assistant (TA) for Creative Game Design and Development (CMPSCI 397G) at UMass Amherst. You can view our class's Scratch page. It contains a demo game I wrote to show examples of multiple design concepts and development features, and we hope to include more tutorials and showcase some student projects in the future.
In the Spring 2014 semester, I was the teaching assistant (TA) for Artificial Intelligence (CMPSCI 383) at UMass Amherst.
In addition to promoting undergraduate exposure to research, I am an advocate of improved science, technology, engineering, and mathematics (STEM) education in the K-12 grade school curricula. These are the fields of the future, and we need to start introducing them to students at a much younger age. There are currently many cultural biases against them that can easily be avoided if we encouraged students to pursue STEM fields, taught younger students the fundamental skills and techniques such as computational thinking and abstraction, and removed the false stereotypes that STEM fields are "too hard to be worth trying."
Materials that I create for educational and outreach workshops/presentations are usually made available afterwards. These range from slides to tutorials and sometimes videos. More recent resources that I have produced are listed below. The complete list may be accessed by clicking [More Resources] above.
I created a reference sheet for the "Writing Scientific Documents in LaTeX" workshop that shows LaTeX commands to use for common buttons found in Microsoft Word menus. The sheet may be found here.
New England Regional Developers (NERD) Summit 2015 at the University of Massachusetts Amherst, MA (September 11-13, 2015)
Freedman, Richard G. and Jones, Marvin C. "Graphics Programming with Processing." An introduction to programming and to simple computer graphics with the Processing programming language. [code examples] [video]
I updated my LaTeX Cheat Sheet for REUMass Amherst 2013. You can download the sheet here and its source code (to see how we used the LaTeX commands) here.
Wake@Hanes Google CS4HS Teacher Workshop 2012 at Wake Forest University, NC (August 9-10, 2012)
Freedman, Richard G. "Higher/Lower Guessing Game: Winning via Efficient Searching." A presentation that teaches binary search through a fun children's game. [Slides]
Freedman, Richard G. "Creative Writing with a Fork in the Road." A lesson plan to introduce younger students to nonlinear thinking and cause-and-effect using Choose-Your-Own-Adventure stories. It was written for Scratch 1.4, but it may also be used with Scratch 2.0. [Lesson Plan] [Scratch demo]
I interact with many people both at UMass Amherst and other universities. Click [More People] above for more people both in and outside of UMass Amherst.
Research Advisor at UMass Amherst: Dr. Shlomo Zilberstein
Students Mentored at UMass Amherst: Timothy (Timm) Allman, Justin Purcell
Students Mentored at Wake Forest: Amanda Chou, Yilin (David) Yang
Although I love research, I also enjoy international travel and learning about other cultures, making/playing games (board, card, and digital), comic books (both Western and Eastern), and various other forms of art including, but definitely not limited to, playing the clarinet, drawing, illusionary arts (also called magic), casual photography, and poetry. I get the opportunity to exercise most these hobbies when I create games, both digital and analog.
University of Massachusetts Amherst College of Information and Computer Sciences
University of Tokyo Graduate School of Arts and Sciences (English) (Japanese)
Dr. Alex Fukunaga's Lab
Wake Forest University Department of Computer Science
Wake Forest University Department of Mathematics
IU STARAI Team
User Interfaces and Scheduling and Planning (UISP) Workshop 2017
Artificial Intelligence for Human-Robot Interaction (AI-HRI) 2016