The names below and on the ballot appear in the alphabetical order based on last names.
Graham Neubig is an associate professor at the Language Technologies Institute of Carnegie Mellon University. His research focuses on natural language processing, with a particular interest in fundamentals, applications, and understanding of large language models for tasks such as question answering, code generation, and multilingual applications. His final goal is that every person in the world should be able to communicate with each-other, and with computers in their own language. He also contributes to making NLP research more accessible through open publishing of research papers, advanced NLP course materials and video lectures, and open-source software. He has previously been the Chief Technical Officer of ARR, and served on the NAACL board for 4 years. He was one of the initiators of several workshops, including the Workshop on Neural Machine Translation.
My major goals as NAACL chair are two-fold:
I believe my past experience as the initiator of several workshops, member of the NAACL board, role in handling the logistics of ARR, and participant in several grassroots NLP initiatives run by language communities (such as Masakhane and AmericasNLP), have left me well prepared to take on these tasks.
Jessy Li is an associate professor in the Department of Linguistics at the University of Texas at Austin. She received her PhD in 2017 from the Department of Computer and Information Science at the University of Pennsylvania. Her research looks into models for discourse processing, natural language generation, and methods to better understand social discourse. She has received the NSF CAREER award for her work on discourse and text simplification. Jessy has been a (Senior) Area Chair for many *ACL and AAAI conferences, a (Senior) Action Editor for ACL Rolling Review, and an Associate Editor for the Dialogue & Discourse journal. She was honored as an Outstanding Area Chair (EMNLP 2020) and an Outstanding Senior Program Committee Member (AAAI 2020). She was a Program Co-Chair for SIGDIAL 2022, and has served on the SIGDIAL board from 2019–2021 and from 2023–2025. She has also been a co-organizer for the Workshop on Computational Approaches to Discourse (CODI) since its inauguration in 2020, and co-organized the First Workshop on Natural Language Processing for Programming co-located with ACL 2021.
It is the NAACL secretary’s responsibility to communicate within the NAACL executive committee and to the community broadly, e.g., to organize meetings, ballots, and to maintain and update media outlets. As we brace for the changing era we are in now, we have also witnessed an uptick of the frequency of major policy changes at ACL over recent years. Thus it is critical to have more timely and transparent communication than ever before. I will commit to:
As part of the NAACL board, I will additionally work on the following:
Dr. Saif M. Mohammad is a Senior Research Scientist at the National Research Council Canada (NRC). He received his Ph.D. in Computer Science from the University of Toronto. Before joining NRC, he was a Research Associate at the Institute of Advanced Computer Studies at the University of Maryland, College Park. His research interests are in Natural Language Processing (NLP), especially Lexical Semantics, Emotions and Language, Computational Creativity, AI Ethics, NLP for psychology, and Computational Social Science. He is currently an associate editor for Computational Linguistics, JAIR, and TACL, and Senior Area Chair for ACL Rolling Review. He also served as chair of the Canada–UK symposium on Ethics in AI, co-chair of SemEval 2017-19, workshops co-chair for ACL 2020, and co-organizer of WASSA 2017-2018. Webpage: http://saifmohammad.com
As scientists, we want our work to be valued. As people, we want to be part of a community. If elected secretary, I will push hard for initiatives that move the needle in these directions.
We have to make reviewing a positive and enriching experience for all involved: for example, incorporating the recent EMNLP direct discussion between reviewers and authors which really helped a lot of authors feel heard. We need to reframe our conferences to be welcoming to all scholarly investigations at the intersection of language and computation. They have traditionally over-valued new computational methods, at the expense of work that produces and investigates datasets, work that proposes new evaluations, work that explores ethics and practical applicability, work that explores problems of the global south, etc. I believe that this should change.
NAACL has had great initiatives such as the Emerging Regions Fund for some time now, but we need to redouble our efforts to nurture vibrant local NLP communities, working on various indigenous and local languages, and on problems that matter to them – aiding in the eventual creation of Central and South American chapters.
I also believe we need to rethink our conference formats. Despite recent initiatives like BoF and Affinity groups, they are far too focused on the author/presenter, and not so much on the attendee. We have relied too much on a great location to draw attendees to conferences. However, with virtual attendance being so beneficial for those who cannot travel, we need to center the attendees (in-person and virtual) and think hard about how our conference formats can be fun, interactive, and foster a sense of belonging and community for all.
Greg Durrett is an associate professor of Computer Science at the University of Texas at Austin. He obtained his PhD in 2016 from the University of California, Berkeley, where he was advised by Dan Klein. Recently, his work has been recognized by a 2023 Sloan Research Fellowship and a 2022 NSF CAREER award. Greg and his collaborators have been publishing in the ACL community actively since 2011 in areas including textual reasoning, summarization, factuality of generation, question answering, and program synthesis (along with syntactic parsing and coreference resolution during his PhD). He served as Publication Chair for EMNLP 2021 and Faculty Advisor to the NAACL Student Research Workshop in 2019. Beyond that, he has organized 4 workshops for *CL conferences: Deep Learning for Low-resource NLP at EMNLP 2019, NLP for Programming at ACL 2021, and the Workshop on Natural Language Reasoning and Structured Explanations at ACL 2023 and ACL 2024. He has been a senior area chair for summarization and an area chair or reviewer in areas spanning interpretability, semantics, syntax, information extraction, and more.
NAACL has undergone a period of rapid change and growth. The boom period of the early deep learning area, with exponentially-growing paper submissions and conference attendance, has tapered off. We now face the challenges of a new and distinct boom period, that of large language models. While NAACL and the rest of *CL are poised to be leaders in this new era, careful management will be needed to ensure this is successful.
One of the principal new challenges is that the NLP community is losing its status as intellectual leader behind recent advances. For instance, OpenAI’s developments are largely external to the community, and core NLP areas like interpretability are being rebranded and coopted by others. By streamlining the current publication process, NAACL can attract a wider range of submissions and disseminate research to an even wider audience than it currently does.
I propose to support the following initiatives within NAACL, with the eventual aim of propagating such changes to the *CL conferences at large:
Remove the arXiv anonymity period. The results of the recent survey by ACL support a case for taking action here. I agree with the arguments put forth by Michael Saxon (https://saxon.me/blog/the-acl-anonymity-embargo-period-is-exclusionary-actually-an-early-career-researchers-perspective.html). The anonymity period was adopted as a compromise solution that no longer makes the right tradeoffs given changes in the publishing landscape. While I am strongly in favor of a fair review process and preserving double-blind review as an institution, the negative impacts of the specific anonymity policy, particularly on early-career researchers who would benefit from discussing their work, outweigh its benefit.
Continue to use OpenReview, but rethink ARR. The paper submission process should be simplified and receiving reviews should be tied to an accept or reject decision. We can follow a model of conferences like ICWSM and USENIX Security, which have multiple intakes for a single conference, giving multiple deadlines throughout the year while streamlining the experience for authors.
Continue to expand diversity initiatives. Widening NLP, DEI chairs for conferences, the Student Research Workshop, and more have had major positive impacts on our community. To improve access to our conference further, I strongly support the creation of an “ACLv” (fully virtual) conference, proposed by Barbara Plank and others, to expand access.
Continue the trend of NAACL’s increased engagement with Latin America. I strongly support continuing to host conferences in underserved regions. I am eager to hear input and discuss how to properly nurture such initiatives and grow the *CL presence there further.
Hanna Hajishirzi is a Torode Family Associate Professor at the University of Washington and a Senior Director of NLP at AI2. Her research spans different areas in NLP and AI, more recently on the science of language models and language models for science. Honors include an NSF CAREER, Sloan Fellowship, Allen Distinguished Investigator Award, Intel rising star award, UIUC alumni award. She has received a best paper and several honorable mention paper awards and has served as an area chair and senior area chair at NLP and Machine Learning conferences, including NAACL, EMNLP, ACL, AAAI, and NeurIPS.
As a board member, I am excited to work on these issues within the NLP community:
Modernize the reviewing and archiving process. The imposition of anonymity deadlines by NLP conferences has resulted in authors refraining from submitting some of their most influential papers to these forums. Conversely, a majority of machine learning and AI conferences permit the archiving of papers and facilitate open discussions subsequent to paper submissions. I hope to contribute to the modernization of the review process by advocating for the elimination of anonymity deadlines, thereby ensuring that NAACL remains the focal point of NLP-related research, including rapidly advancing research areas.
Promote open research. With all advances in language modeling, the NLP and scientific community needs access to open models, open data, and open evaluation settings to understand and advance the science of language models. I hope to advocate for open, well-document, and reproducible research papers from the community. Consequently, this bridges the academic and industry research gap.
Advocate for interdisciplinary research. Recently, language models have demonstrated notable efficacy in practical applications. However, there exists potential for substantial enhancement through interdisciplinary research, thereby extending the scientific foundations of language models into diverse domains such as medicine and to scientific discovery. I hope to promote and facilitate interdisciplinary research efforts that integrate various facets of AI and NLP into tangible real-world applications.
AI literacy for public, k-12 students, and undergraduates: It is an exciting time for the NLP field. I am enthusiastic about disseminating knowledge to both the general public and younger generations, elucidating the capabilities and limitations inherent to language models and the broader NLP field.
Dilek Hakkani-Tür is a Professor of Computer Science at University of Illinois Urbana-Champaign, focusing on enabling natural dialogues with machines. Prior to that, she was a researcher at Amazon, Google, Microsoft, International Computer Science Institute and AT&T Labs-Research. She received her PhD degree from Bilkent University in 2000. Her research interests include conversational AI, natural language and speech processing, spoken dialogue systems, and machine learning for language processing. She has over 80 patents that were granted and co-authored more than 300 papers in natural language and speech processing. She received several best paper awards for publications she co-authored on conversational systems, including her earlier work on active learning for dialogue systems, from IEEE Signal Processing Society, ISCA and EURASIP. She served as an associate editor for IEEE Transactions on Audio, Speech and Language Processing, member of the IEEE Speech and Language Technical Committee, area editor for speech and language processing for Elsevier’s Digital Signal Processing Journal and IEEE Signal Processing Letters, member of the ISCA Advisory Council, the Editor-in-Chief of the IEEE/ACM Transactions on Audio, Speech and Language Processing, an IEEE Distinguished Industry Speaker, program co-chair of NAACL 2021 and president of the SIGdial. She is a fellow of the IEEE and ISCA.
The past few years have been interesting for language processing in general, with a lot of advancements in the field. If elected, the areas I’d like to focus on include:
Dr. Zornitsa Kozareva is the CTO & Co-Founder of SliceX AI, whose mission is to make next-generation AI universally accessible to anyone, anywhere. Prior to that, Dr. Kozareva was the Head of Large Language Models at Facebook AI Research. Dr. Kozareva brings 15+ years of experience from big tech like Google where she led and managed Search and Intelligence efforts; Amazon where she oversaw the launch of Amazon Comprehend and Lex services, and Yahoo! where she drove Mobile Search and Advertisement. Dr. Kozareva was a Professor at University of Southern California spearheading research funded by DARPA & IARPA. In 2022 Dr. Kozareva was the EMNLP 2022 Program Chair. She serves on the University of California Santa Cruz Advisory Board. Her work is featured in Forbes, VentreBeat, GizBot. Dr. Kozareva is the recipient of the John Atanasoff Award given by the President of the Republic of Bulgaria in 2016 for her contributions and impact in science, education and industry.
We live in the most exciting times for NLP, where groundbreaking developments are occurring at a fast pace leading to transformative change in how we interact with and process natural language. If I am elected as NAACL Board Member, in addition to ensuring that we produce reproducible research, support interdisciplinary work and linguistic diversity, I would also want to focus on:
Manuel Mager is an Applied Scientist at Amazon Web Services (AWS) AI Labs. He is originally from Mexico and has a heritage as part of the Indigenous Wixarika community of Zoquipan (Father) and German (Mother). He made his studies at the Universidad Nacional Autonoma de Mexico (UNAM)[Mexico], Universidad Autonoma Metropolitana - Azapotzalco (UAM)[Mexico], and the University of Stuttgart [Germany]. With this background, he has focused his research on studying NLP approaches for the Indigenous languages of the America. His interests are modeling morphology, code-switching, and machine translation. As part of his current position, he is also working on information retrieval and large language models. He has co-founded and is still co-organizing the AmericasNLP workshops (2021-2024). He also publishes regularly on the main ACL/NLP venues, and volunteers as reviewer. Other volunteer positions he took part in are: D&I chair (ACL2021) and area chair (EMNLP 2023).
NAACL has been historically built around a USA and Canada centric view of community. However, this does not represent all countries, languages and communities from the region. Therefore, If I am elected as a chair on the board, I work towards:
Anna Rumshisky is an Associate Professor in the Department of Computer Science at the University of Massachusetts Lowell. She works on large language models, model interpretability & analysis, temporal reasoning, and natural language modeling for clinical informatics. She is currently a Visiting Academic at Amazon Alexa AI. She was previously a postdoctoral fellow at MIT CSAIL and received a PhD in Computer Science from Brandeis University in 2009. She is a recipient of the NSF CAREER award in 2017 and the best thematic paper award at NAACL-HLT 2019. Her research has been supported by the NSF, NIH, Army Research Office, National Endowment for the Humanities, among others. She has served as a Program Co-Chair for NAACL 2021, senior area chair for NeurIPS 2023 and ICLR 2024, area chair for ACL 2020, NAACL-HLT 2019, and COLING 2018, and co-organized a number of workshops, including Insights from Negative Results in NLP (Insights @ EMNLP 2020, EMNLP 2021, ACL 2022, EACL 2023), Evaluating Vector Space Representations for NLP (RepEval @ NAACL 2019), and the Clinical Natural Language Processing Workshop (COLING 2016, NAACL 2019, EMNLP 2020, NAACL 2022, ACL 2023).
As a board member, I would like to ensure that we work on the following issues:
Huan Sun is an endowed College of Engineering Innovation Scholar and a tenured associate professor in the Department of Computer Science and Engineering at The Ohio State University. Her research interests lie in natural language processing and artificial intelligence, especially language agents, large language model analysis and evaluation. Huan received Honorable Mentions for Best Paper Awards at ACL’23 (for two papers), 2022 ACM SIGMOD Research Highlight Award, BIBM Best Paper Award, Google Research Scholar and Google Faculty Award, NSF CAREER Award, OSU Lumley Research Award, and SIGKDD Ph.D. Dissertation Runner-Up Award, among others. Her team TacoBot won third place in the first Alexa Prize TaskBot challenge and was the only award-winning team in the US.
It’s a great honor for me to be considered as a NAACL board member. I will be committed to serving the NLP community if elected. My vision revolves around three core principles, which I believe are crucial for the continued growth and excellence of our community.
Facilitating discussions on conference policies: The policies governing paper submission (e.g., anonymity, arXiv), reviewing, and awards are at the heart of our community’s fairness and transparency. I aim to facilitate open and constructive dialogues to refine these policies. As a board member, I will work tirelessly to ensure that our conference policies are inclusive, equitable, and adaptive, especially given the fast pace of current research development. I will actively seek feedback from the community and advocate for policies that align with our collective values.
Promoting interdisciplinary work: Our field is undergoing a revolution driven by the advances in large language models (LLMs). On the one hand, it is crucial that we extend the reach of NLP beyond our traditional boundaries and harness its transformative potential to address real-world challenges in various domains such as healthcare, social justice, and environmental science. On the other hand, it is important for the NLP community to draw insights from other disciplines like psychology and neuroscience to develop innovative techniques. As a board member, I will support the creation of dedicated tracks, workshops, and incentives for interdisciplinary research. By fostering collaboration across domains, we can facilitate the growth of both NLP and other fields in a mutually beneficial manner .
Supporting students and low-resourced researchers: One of the most pressing issues in our community is the financial barrier that prevents many students and low-resourced researchers from participating in *CL conferences. Travel costs are often prohibitively high, and a limited budget from funding agencies leaves many deserving researchers unable to attend. If elected, I am committed to expanding travel support for students and low-resourced researchers (e.g., researchers who have papers to present but are transitioning between jobs or just start on a new position and have to support multiple students to attend), especially those from underrepresented groups. By seeking additional sponsorship and optimizing the allocation of resources, I hope to ensure that a more diverse and representative group of young researchers benefit from the invaluable experiences *CL conferences offer.
Rui Zhang is an Assistant Professor in the Computer Science and Engineering Department of Penn State University. He is a co-director of the PSU Natural Language Processing Lab. He served as an area chair at NAACL, EMNLP, NeurIPS, AACL, NLPCC, a tutorial chair at NAACL, and a mentor in ACL Year-Round Mentorship. He also co-organized several workshops including Structured and Unstructured Knowledge Integration at NAACL 2022, Multilingual Information Access at NAACL 2022, and Interactive and Executable Semantic Parsing at EMNLP 2020. His research interest lies in Actionable and Agentic Language Models, Trustworthy and Responsible Text Generation, and Efficient and Generalizable Methods. He received an Amazon Research Award, an eBay Research Award, and a Cisco Research Award. He received B.S. degrees from both Shanghai Jiao Tong University and the University of Michigan in 2015 and received his Ph.D. from the Computer Science Department at Yale University in 2020.
The very recent rapid advancement of NLP has opened up many challenges and opportunities for our community. If elected as a NAACL board member, I would like to be dedicated to the following initiatives: