Meet Our Team

2023

• Raymond Fok (University of Washington)
• John Giorgi (University of Toronto)‍
• Yue Guo (University of Washington)
• Joe (Chao-Chun) Hsu (University of Chicago)
• Hang Jiang (Massachusetts Institute of Technology)
• Jeongyeon Kim (Stanford University)
• Hyunji Lee (KAIST)
• Yoonjoo Lee (KAIST)
• Monica Munnangi (Northeastern University)
• Marissa Radensky (University of Washington)
• Nikhil Singh (Massachusetts Institute of Technology)
• Orion Weller (Johns Hopkins University)
• Fangyuan Xu (University of Texas at Austin)

2022

• Nayha Auradkar (University of Washington): Scientific Text Mining for Alt Text Content
• Hancheng Cao (Stanford University): The Death and Life of Great Research Artifacts
• Cathy Chen (University of California Berkeley): Language Model Generation to Unseen Layouts
• Chris Coleman (Northwestern University): Embedding Recycling
• Carl Edwards (University of Illinois at Urbana-Champaign): Hypothesis Generation in Biomedicine
• John Giorgi (University of Toronto): Retrieval in Multidocument Summarization
• Lucy Li (University of California Berkeley): Language-Driven Map of Science
• Yuze Lou (University of Michigan): Entity Linking in Scientific Tables
• Hyeonsu Kang (Carnegie Mellon University): Reference-driven Social Recommendations
• Tae Soo Kim (Korea Advanced Institute of Science & Technology): Localized Videos in Papers
• Kalpesh Krishna (University of Massachusetts Amherst): Guidelines for Human Evaluation in Long-form Summarization
• Rabeeh Mahabadi (EPFL - Swiss Federal Institute of Technology Lausanne)
• Srishti Palani (University of California San Diego): Reusing Related Work Sections
• Shaurya Rohatgi (Penn State University): Scientific Paper Clustering
• Nouran Soliman (Massachusetts Institute of Technology): Shareable Lists of Scientific Papers
• Qingyun Wang (University of Illinois at Urbana-Champaign): Knowledge Graph Link Prediction

‍

2021

• Tal August (University of Washington): Addressing barriers in medical literature for lay people
• Avi Caciularu (Bar-Ilan University): Token-level Contrastive Learning for Multi-hop Question Answering
• Sanjana Chintalapati (University of Washington): Increasing scientific figure accessibility with alt-text
• Mike D'Arcy (Northwestern University): Joint Inference for Scientific Knowledge Graph Representation
• Raymond Fok (University of Washington): Semantic Skimmer
• Varun Gangal (Carnegie Mellon University): Interpretable text generation with operations
• Zhipeng Hou (Northwestern University): Retrieve to achieve (better embeddings)
• Hyeonsu Kang (Carnegie Mellon University): Synthetic Social Recommendations for Improving Access and Mitigating Bias in Scientific Discovery
• Sheshera Myshore (University of Massachusetts Amherst): Explanation Informed Fine-grained Scientific Document Similarity
• Aakanksha Naik (Carnegie Mellon University): Improving Clinical Outcome Prediction Using Evidence from Medical Literature
• Napol Rachatasumrit (Carnegie Mellon University): Bootstrapping Reader Highlights
• Shaurya Rohatgi (Penn State University): Modeling and Inferring Academic Mentorship on Semantic Scholar
• Chantal Shaib (Northeastern University): BioWordPiece: Teaching WordPiece about morphology
• Dustin Wright (University of Copenhagen): Decomposing Scientific Claims to Verifiable Units
• Wen Xiao (University of British Columbia): Multi-document Summarization for Scientific Papers

2020

• Arie Cattan (Bar-Ilan University): Scientific Concept Induction
• Jay DeYoung (Northeastern University): Summarizing Evidence across Studies: Automating Systematic Review Generation
• Raymond Fok (University of Washington): Recovery for AI-Infused UIs
• Harmanpreet Kaur (University of Michigan): FeedLens: Trainable Research Feeds for Rapid Navigation of Paper List Objects
• Rafal Kocielnik (University of Washington): Motivating Scientific Reading Habits with Interventions Based on Text Mining and Behavioral Psychology
• Anne Lauscher (University of Mannheim): Citation Context Analysis Revisited
• Sean MacAvaney (Georgetown University): Analyzing Behavior of Neural IR Models
• Jason Portenoy (University of Washington): SciSight++: Visually exploring the network of CS authors, methods and tasks extracted from 10M papers
• Marissa Radensky (University of Washington): Exploring the Role of Local and Global Explanations in Recommender Systems
• Shivashankar Subramanian (University of Melbourne): An In-Depth Analysis of Author Disambiguation
• Mohit Yadav (University of Massachusetts Amherst): End-to-End Document-Level IE

2019

• Jim Chen (University of Washington): Building Better Topic Pages for All
• Mike D'Arcy (Northwestern University): RefBERT: Representing References in Scientific Documents
• Andrew Head (University of California Berkeley): Augmenting the Reading Experience for Scientific Papers from arXiv
• Sarthak Jain (Northeastern University): Structured Results Extraction
• Ben Lee (University of Washington): Explanation-Based Tuning of Opaque Machine Learners with Application to Paper Recommendation
• Susan (Xueqing) Liu (University of Illinois Urbana-Champaign): A Quantitative Study on Citation Preferences in Scientific Literature
• Pouya Pezeshkpour (University of California Irvine): Question Generation and Targeting for Assisted Flashcard Study of Scientific Papers
• David Wadden (University of Washington): SciFact: A Dataset for Verification of Scientific Claims

2018

• Christine Betts (University of Washington): GrapAL: Connecting the Dots in Scientific Literature
• Muthu Chandrasekaran (National University of Singapore): Aggregation of Tabular Empirical Results from Scientific Documents
• Xuezhe Ma (Carnegie Mellon University): Sci-Defi: Identifying Scientific Concept Definitions in Scholarly Documents
• Amandalynne Paullada (University of Washington): Improving Clinical Trial Information Extraction with Weak Supervision

2017

• Titipat Achakulvisut (University of Pennsylvania): Claim Extraction in Biomedical Publications Using Deep Discourse Model and Transfer Learning
• Ahmed Elgohary (University of Maryland): Relation Extraction from Scientific Documents
• Lucy Lu Wang (University of Washington): Ontology Alignment in the Biomedical Domain Using Entity Definitions and Context