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Maria Leonor Pacheco
marialeonorpg [at] gmail [dot] com
mlpacheco
google scholar
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I am an incoming Postdoctoral Researcher at Microsoft Research, NYC. In Fall 2023, I will join the Department of Computer Science at the University of Colorado Boulder as an Assistant Professor. I completed my PhD in Computer Science at Purdue University under the supervision of Prof. Dan Goldwasser.

My current research focuses broadly on neural-symbolic methods to model natural language discourse. From a modeling prespective, I am interested in the integration of structured knowledge and distributed language representations. From an applied perspective, I am interested in discourse analysis and computational social science. Most of my previous work has focused on analyzing conversations, argumentation, and narratives by modeling the textual content, the discourse structure, and the social context using neural-symbolic representations. I am a strong believer in interdisciplinary, collaborative work. Whenever appropriate, I ground my NLP work in relevant conceptual frameworks and theories developed in other disciplines (e.g. communication, social psychology).

I will be looking for PhD students to start in Fall 2023. Please, reach out if you think we could be a good match (and tell me why you think we would work well together!)
For more details, take a look at my research statement


News


Publications

Refereed Journals and Conferences (* Indicates co-first authorship)
A Holistic Framework for Analyzing the COVID-19 Vaccine Debate
ML Pacheco, T Islam, M. Mahajan, A. Shor, M Yin, L Ungar, D Goldwasser
In North American Chapter of the Association for Computational Linguistics, NAACL 2022. (to appear)
Tackling Fake News Detection by Continually Improving Social Context Representations using Graph Neural Networks
N Mehta, ML Pacheco, D Goldwasser
In Association for Computational Linguistics, ACL 2022. (to appear)
Automated Attack Synthesis by Extracting Finite State Machines from Protocol Specification Documents
ML Pacheco, M von Hippel, B Weintraub, D Goldwasser, C Nita-Rotaru
In IEEE Symposium on Security and Privacy, IEEE S&P 2022. (to appear)
Identifying Morality Frames in Political Tweets Using Relational Learning
S Roy, ML Pacheco, D Goldwasser
In Empirical Methods in Natural Language Processing, EMNLP 2021.
Modeling Content and Context with Deep Relational Learning
ML Pacheco, D Goldwasser
In Transactions of the Association for Computational Linguistics, TACL 2021.
Presented at NAACL 2021
Modeling Human Mental States with an Entity-based Narrative Graph
IT Lee, ML Pacheco, D Goldwasser
In North American Chapter of the Association for Computational Linguistics, NAACL 2021.
Randomized Deep Structured Prediction for Discourse-level Processing
M Widmoser*, ML Pacheco*, J Honorio, D Goldwasser
In European Chapter of the Association for Computational Linguistics, EACL 2021.
Also presented at the EMNLP 2020 Workshop on Structured Prediction for NLP
Weakly-Supervised Modeling of Contextualized Event Embedding for Discourse Relations
IT Lee, ML Pacheco, D Goldwasser
In Findings of the Association for Computational Linguistics, Findings of ACL: EMNLP 2020.
Identifying Collaborative Conversations using Latent Discourse Behaviors
A Jain, ML Pacheco, S Lancette, M Goindani, D Goldwasser
In ACL Special Interest Group on Discourse and Dialogue, SIGDIAL 2020.
Leveraging Textual Specifications for Grammar-based Fuzzing of Network Protocols
S Jero, ML Pacheco, D Goldwasser, C Nita-Rotaru
In Innovative Applications of Artificial Intelligence, IAAI 2019.
Adapting Event Embeddings for Implicit Discourse Relations
ML Pacheco, IT Lee, X Zhang, AK Zehady, P Daga, D Jin, A Parolia, D Goldwasser
In Computational Natural Language Learning, CoNLL Shared Task 2016.
Refereed Workshops (* Indicates co-first authorship)
Neural-Symbolic Modeling for Natural Language Discourse
ML Pacheco, D Goldwasser
ICML 2020 Workshop on Bridge Between Perception and Reasoning
Leveraging Representation and Inference through Deep Relational Learning
ML Pacheco, I Dalal, D Goldwasser
NeurIPS 2018 Workshop on Relational Representation Learning
Predicting Semantic Textual Similarity with Paraphrase and Event Embeddings
IT Lee, M Goindani, C Li, D Jin, K Johnson, X Zhang, ML Pacheco, D Goldwasser
In International Workshop on Semantic Evaluation, SemEval 2017
Introducing DRaiL: A Step Towards Declarative Deep Relational Learning
X Zhang*, ML Pacheco*, C Li, D Goldwasser
EMNLP 2016 Workshop on Structured Prediction for NLP

Teaching

  • Purdue University
    • CS180 - Problem Solving and Object Oriented Programming - Instructor and Head TA (Summer 2016, Fall 2016)
    • CS180 - Problem Solving and Object Oriented Programming - Graduate TA (Fall 2015, Spring 2016)

Academic and Instutional Service

  • Student Research Workshop Co-Chair, NAACL 2022
  • Reviewer for ACL Rolling Review, EMNLP 2021, ACL 2021, NAACL 2021, AAAI 2021, ACM Computing Surveys
  • Social Media Co-Chair, SIGDIAL 2021
  • Computer Science Representative, Graduate Women in Science Programs, Purdue University (2021-2022)
  • Diversity Chair, CS Graduate Student Board, Purdue University (2020-2021)
  • Graduate Student Representative, CS Department Diversity Task Force, Purdue University (2020-2021)
  • Global Ambassador, Purdue Graduate School (2018-2021)

Last Update: May, 2019.