Department of Computer Science

Martha Evens Distinguished Lecture Series in Computer Science


Martha Evens and Peter Johnson

Professor Emerita Martha Evens was among the earliest faculty members in the Illinois Institute of Technology's Department of Computer Science, tirelessly working to build the department over decades of dedicated teaching, research, and service. Her research in artificial intelligence and natural language processing was pivotal in the early development of computational lexicography and of intelligent tutoring systems, and she is the devoted and beloved teacher and mentor of hundreds of students.

To honor her legacy, her students and colleagues have endowed the annual Martha Evens Distinguished Lecture Series in Computer Science. Honorees are internationally renowned computer scientists whose contributions have broad impact both within and beyond the bounds of the discipline. 

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Previous Lecture

Speaker: Bonnie J. Dorr, Professor of Computer Science, University of Florida

Title: Human Language Technology Challenges and Applications


This talk presents challenges in human language technology that have led to innovative solutions at the intersection of computer science and formal linguistics for a range of applications, e.g., machine translation of human languages and cyber-aware language processing. Past, current, and future projects address a range of challenges: (a) brittleness of rule-based linguistic principles for large-scale processing; (b) shallowness of statistical methods for deep language understanding; (c) lack of “explainability” amidst ever-increasing numbers of black-box machine-learning (ML) variants (e.g., deep learning). Particular attention is paid to hybrid approaches that combine linguistic and statistical techniques to handle informal language and implicitly conveyed information. Applications include “ask detection” for defending against social engineering attacks and “stance detection” for extracting attitudes from social media. Crucial next steps include the design and implementation of an “explainable” representational formalism that accommodates broader scale ML approaches and supports the ability for developers and end users to understand what is going on inside the AI system. Expected questions for such systems range from “How can one detect and deter social engineering attacks?” to “How does one take the pulse of a community with respect to government interventions in a pandemic?” to “How does one predict ‘in real life’ behaviors from associated language usage on social media?”

Bonnie Dorr speaks during the Jan. 26, 2023 Martha Evens Distinguished Lecture Series in Computer Science

Bio: Professor Dorr joined the Department of Computer and Information Science and Engineering at the University of Florida in 2022 where she directs the Natural Language Research (NLP) Group. Her research focuses on deep language understanding, semantics, language processing using linguistically informed machine learning models, large-scale multilingual processing, explainable artificial intelligence (AI), social computing, and detection of underlying mental states. Her recent contributions have fallen squarely in the realm of cyber-NLP, for example, responding to social engineering attacks and detecting indicators of influence. She has an affiliate appointment at the Institute for Human and Machine Cognition, is Professor Emerita at the University of Maryland, former program manager at the Defense Advanced Research Projects Agency (DARPA), and former president of the Association for Computational Linguistics. She is a Sloan Fellow, NSF Presidential Faculty (PECASE) Fellow, AAAI Fellow, ACL Fellow, and ACM Fellow. In 2020 she was named by DARPA to the Information Science and Technology (ISAT) Study Group. She holds a Master's and a Ph.D. in computer science from the Massachusetts Institute of Technology, with a Bachelor's degree in computer science from Boston University.