Evangelia Spiliopoulou, Ph.D. candidate

Curriculum Vitae
Contact me: espiliop@cs.cmu.edu

Currently looking for full-time job opportunities!

My name is Evangelia Spiliopoulou and I am a Ph.D. candidate in NLP advised by Eduard Hovy. I am studying at Language Technologies Institute, Carnegie Mellon University.

My research focuses on the study of events and their outcomes, specifically targeted in low-resource or real-time scenarios. I am interested on the modeling / representation aspect; how can we take full advantage of what we already know (e.g., through LLMs) to solve problems in zero- or few-shot scenarios.

  • 2021-11-10 Our paper in collaboration with Dataminr: "A Novel Framework for Detecting Important Subevents from Crisis Events via Dynamic Semantic Graphs" was accepted at W-NUT, EMNLP 2021!
  • 2021-05-13 I passed my Thesis Proposal, under the title Modeling Event Implications via Multi-faceted Entity Representations! Many thanks to my committee for their valuable feedback: Yonatan Bisk, Lori Levin and Alan Ritter.
  • 2020-12-08 Presenting our work on Definition Frames at COLING'2020!
  • 2020-09-14 Our work on Event-Specific Bias Removal was accepted at EMNLP Findings!
  • 2020-05-25 Excited to start my internship with Dataminr!

  • Selected Research Projects

    Event Implications
    Current project, Thesis

  • How do events impact an entity‚Äôs state?
  • How can we teach LLMs what to learn, and apply it in unseen entities?

  • Detecting important sub-events from large-scale crisis events
    Completed in May 2021, internship with Dataminr

  • Detect sub-events from social media that may help in humanitarian aid efforts
  • Information is scattered across multiple posts, need to aggregate & combine
  • Importance of temporality and sub-event dependencies (i.e., each sub-event is dependent, on other sub-events)

  • Event-Specific Bias Removal
    Completed in May 2020

  • Detect critical tweets in real-time crisis scenarios
  • No data for the current event, few previous events of similar nature annotated
  • Data bias problem: use adversarial techniques to retain only the useful information for the task

  • Definition Frames
    Completed in March 2020

  • Design explainable entity representations via the use of definitions
  • Representations with structure help us identify which information is important: less data needed

  • Other Projects

    World Modelers, Sofia
    Funded by DARPA, Advisor: Eduard Hovy
  • Design & Implementation of SOFIA (code) and Project Management
  • Detect causal links & events from noisy documents, real-time

    Funded by DARPA, Advisor: Eduard Hovy
  • Detecting events & arguments from news articles
  • System integration for extraction of entities, relations, events and sentiments into ColdStart++ KBs
  • Final report and code

  • Relation Extraction & Classification
    Class Project, Fall 2017
  • Relation Extraction from scientific publications on NLP (SemEval 2018, task 7)

  • Multi-genre Natural Language Inference
    Class Project, Fall 2017
  • Classify sentence pairs as Inference/Contradiction/Neutral (multi-NLI corpus)

  • Linguistic Markers of Influence
    Class Project, Spring 2017
  • Classify sentence pairs as Inference/Contradiction/Neutral (multi-NLI corpus)

  • Document Clustering
    Class Project, Fall 2017
  • Using automatically extracted events as features to cluster documents according to topic (ECB+ dataset)

  • Health Insurance Analytics
    Funded by MetLife, Advisor: Anatole Gershman
  • Anomaly detection on health insurance data based on medical history, diagnosis & patient self-reports
  • Goal was to detect insurance fraud from disability claims

  • Information Extraction for Biologically-Inspired Design
    Design & Intelligence Lab, Georgia Tech, Advisor: Ashok Goel
  • Extract information from biology papers in the form of knowledge graphs
  • Knowledge graphs used for biologically-inspired design
  • Effort to commercialize our application in finance sector, via the NSF i-Corps program

  • Publications

    * = equal contribution


    SD^2G: A Novel Framework for Detecting Important Subevents from Crisis Events via Dynamic Semantic Graphs.
    In Proceedings of the Seventh Workshop on Noisy User-generated Text (W-NUT 2021).
    Evangelia Spiliopoulou, Tanay K. Saha, Joel Tetreault, Alejandro Jaimes.


    Event-Related Bias Removal for Real-time Disaster Events.
    In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings.
    Evangelia Spiliopoulou*, Salvador Medina Maza*, Eduard Hovy, Alexander Hauptmann.
    PDF & Code/Data

    Definition Frames: Using Definitions for Hybrid Concept Representations
    In Proceedings of the 28th International Conference on Computational Linguistics (COLING 2020).
    Evangelia Spiliopoulou, Artidoro Pagnoni and Eduard Hovy.
    PDF & Code/Data


    Event Detection Using Frame-Semantic Parser.
    In Proceedings of the Events and Stories in the News Workshop.
    Evangelia Spiliopoulou, Eduard Hovy and Teruko Mitamura.
    PDF & Code/Data

    Linguistic Markers of Influence in Informal Interactions.
    In Proceedings of the Second Workshop on NLP and Computational Social Science.
    Choudhary S., Prabhumoye S., Evangelia Spiliopoulou, Bogart C., Rose C. and Black A., W.

              Last updated Nov 16th 2021