Faculty
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| Dr. Cynthia Matuszek's research is in the intersection of robotics and natural language for HRI. She is an associate professor in UMBC's Computer Science and Electrical Engineering department and the founder of the IRAL research lab. | Dr. Frank Ferraro's research is focused on natural language processing, computational event semantics, and unlabeled, structured probabilistic modeling over very large corpora. He is an assistant professor in UMBC's Computer Science and Electrical Engineering department. |
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| Dr. Don Engel's research spans robotics, vision, and immersive human-robot interaction. He is UMBC's Assistant Vice President for Research, and an affiliate assistant professor of both physics and computer science. He is the founder of the AVAIL lab. | Dr. Edward Raff performs research in a number of areas, including machine learning, malware analysis, adversarial ML, fingerprint biometrics, and fairness in AI. He is a Chief Scientist with Booz Allen Hamilton, and a visiting affiliate professor at UMBC computer science. bit.ly/2zh9Dm3 |
Students
Ph.D.
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Christian Angel |
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Ryan Barron |
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Adam Berlier Grounded language conditioned probabilistic and causal reasoning for robot action planning in novel environments/scenarios. Reinforcement learning for stable policies in human-robot interaction. |
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Nadja Bzhilyanskaya |
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Kasra Darvish Designing probabilistic graphical models to train robots for interacting with humans using natural language. Multimodal representation learning and alignment. |
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Shubhashis Roy Dipta |
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Mohammad Eskandari |
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Padraig Higgins Improving telepresence with embodied capabilities. |
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Maithili Kadam |
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Mehdi Rezaee Using machine learning for event and language modeling, focusing on event representation. |
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Luke Richards Semantic parsing of grounded language to improve fairness and explainability. |
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Sai Vallurupalli |
Masters
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Aidan Newell |
Research Undergraduates
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Quentin Richards |
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Sianna Serio |
Alumnae
Ph.D.
- Nisha Pillai,Ph.D. computer science, 2021. Postdoc, Mississippi State University.
Thesis: Learning Natural Language from Probabilistic Perceptual Representations with Limited Resources. - Ashwin Ganesan, Ph.D. computer science, 2021. (Co-advised.)
Thesis: Low Resource Learning in Neural Dialog Systems. - John Winder, Ph.D. computer science, 2019. (Co-advised.) Johns Hopkins APL.
Thesis: Abstract Decision Making and Concept Formation for Adaptability and Generalization. - Ankur Padia, Ph.D. computer science, 2019. (Co-advised.)
Thesis: Joint Models to Refine Knowledge Graphs.
M.S.
- G. Youssouf Kebe, M.S. computer science, 2022.
Thesis: Speaker-Based Variability in Robotic Spoken Language Grounding. - Adam Grosse, M.S. computer science, 2022.
Thesis: Decompositional Semantics: Examining Semantic Proto Roles For Domain Transfer. - Michael Neary, M.S. computer science, 2021.
Thesis: Identifying Extraneous Elements of Novice Source Code. - Aishwarya Sapkale, M.S. computer science, 2020.
Thesis: Deep Comprehension of Visual Stories through Summarization and Question Answering. - Sarthak Mehta, M.S. computer science, 2020.
Thesis: Stratified Neural Models for Document Classification. - Patrick Jenkins, M.S. computer science, 2020.
Thesis: Transfer Learning of Grounded Language Models For Use In Robotic Systems. - Justin Rokisky, M.S. computer science, 2020.
Thesis: Using Web Images & Natural Language for Object Localization in a Robotics Environment. - Aishwarya Sapkale, M.S. computer science, 2020.
Thesis: Deep Comprehension of Visual Stories through Summarization and Question Answering. - Rishabh Sachdeva, M.S. computer science, 2020.
Thesis: Speech vs. Textual Data for Grounded Language Learning. - Caroline Kery, M.S. computer science, 2019.
Thesis: Esta es una Naranja Atractiva: Adventures in Adapting an English Language Grounding System to Non-English Data. - Rajat Patel, M.S. computer science, 2019.
Thesis: Joint Learning Framework For Learning Embeddings In A Shared Space to Improve Natural Language Processing Applications. - Isha Potnis, M.S. computer science, 2018.
Thesis: Sharing Learned Models Between Heterogeneous Robots: an Image Driven Interpretation. - Mayur Pate, M.S. computer science, 2018.
Thesis: Open Information Extraction for Code-Mixed Hindi-English Social Media Data. - Tim Lewis, M.S. computer science, 2018.
Thesis: Augmentative and Alternative Communication Interface with a Context-Based, Predictive Language Model. - Tejas Sathe, M.S. computer science, 2017.
Thesis: S.T.O.M.P.: Sentry Tele-Operation and Monitoring Protocol. - Gurpreet Singh, M.S. computer science, 2017.
Thesis: CARLTON: A Location Aware Helpdesk Agent. - Neil R. Bell, M.S. computer science, 2016.
Thesis: Human-Robot Object Exchange - a Comparative Study of Human Emotion Regarding Proximity and Success..
Undergraduates
- Monali Saraf, B.S. computer science, 2021.
- Aaleyah Lewis, B.S. computer science, 2021.
Now: University of Washington, Computer Science and Engineering Ph.D. program. - Fayokemi Ojo, B.S. computer science, 2020.
Now: Maryland Max Planck Ph.D. program. - Blair Witt, B.S. computer science, 2020.
- Phillip Hilliard B.S. computer science, 2019.
- Stephanie Milani, B.S. computer science, 2019.
Now: Carnegie Mellon University, Machine Learning Department Ph.D. Program. - Uchenna Osia, B.S. computer science, 2019.
Now: North Carolina State University, Computer Science Ph.D. program. - Megan Zimmerman, B.S. computer science, 2017.
Now: The National Institute of Standards and Technology (NIST). - Natacha Ngea, B.S. electrical and computing engineering, 2017.
Now: Harris Corporation.