photoML
Maria Leonor Pacheco
CS Department - Purdue University
Advisor: Prof. Dan Goldwasser
pachecog [at] purdue [dot] edu
mlpacheco
google scholar
CV

I am a PhD. candidate in Computer Science at Purdue University, where I work with Dr. Dan Goldwasser as part of the Purdue Natural Language Processing Group. My current research focuses broadly on neural-symbolic methods to model natural language discourse. I am interested in applications that can benefit from the integration of structured human knowledge and large-scale language analysis. Most of my previous work is in analyzing conversations, argumentation, and narratives by modeling the textual content, the discourse structure, and their social context. Whenever appropriate, I connect these analyses with relevant conceptual frameworks.

I am also actively involved in interdisciplinary collaborations with the Network and Dependable Systems and Security Lab at Northeastern University. This work focuses on leveraging NLP for network security.

📢 I’m on the job market! 📢 Please reach out if you think I’d be a good fit for your academic department or research group.


News


Publications

Refereed Journals and Conferences (* Indicates co-first authorship)
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.
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)