The names below and on the ballot appear in the alphabetical order based on last names.
Steven Bethard is an associate professor at the College of Information Science at the University of Arizona whose research focuses on modeling the language of time and timelines, normalizing text to medical and geospatial ontologies, and information extraction models for clinical applications. He has been engaged in the NAACL community for many years: he was a program chair for NAACL 2024, was publication chair for NAACL 2021 and ACL 2020, was on the board of SIGLEX from 2016-2024, was an organizer of the SemEval workshop from 2016-2018, has been an organizer of the Clinical NLP Workshop since 2016, is an area chair for ACL Rolling Review, and is a standing reviewer for TACL.
As NAACL treasurer, I would work closely with ACL treasurer David Yarowsky and ACL business manager Jenn Rachford (the latter of whom I worked closely with during the organization of NAACL 2024) to ensure that NAACL can continue to support the efforts beyond the main NAACL conference that it has in the past: the North American Computational Linguistics Open Competition (NACLO) for engaging high school students, the Regional Americas Fund (RAF) for strengthening computational linguistics broadly across the Americas, and the Frederick Jelinek Memorial Summer Workshop on Speech and Language Technology (JSALT) for encouraging hands-on collaboration on challenging NLP problems.
My future goal as NAACL treasurer would be to examine our current income and expenditures to allow us to expand our support of initiatives like NACLO, RAF, and JSALT, to expand our support for travel and/or registration to our flagship conference from underrepresented regions, and to make our financial spending profile appropriately reflect the recent transition from “North America” to “Nations of the Americas” by encouraging support of events in previously underfunded regions of the Americas.
Malihe Alikhani is an Assistant Professor of AI and Social Justice at the Khoury College of Computer Sciences at Northeastern University and a member of the Northeastern Ethics Institute. Her research focuses on designing inclusive and equitable language technologies that communicate effectively across diverse populations, with a particular emphasis on underserved communities. By integrating insights from cognitive science, neuroscience, philosophy, policy, and social sciences with machine learning techniques, she develops computational models that capture the rich diversity of human interpretation and enhance the effectiveness of language as a communicative tool. Malihe Alikhani has co-chaired major workshops and conferences and received best paper awards from leading machine learning and NLP venues such as ACL and UAI. NSF, DARPA, NIH, Amazon, Google, and CDC have supported her research. She has led several diversity programs across the United States for undergraduate and high school students and currently serves as the Ethics Co-Chair for the ACL Rolling Review. She has collaborated with diverse communities and unions to design inclusive technologies and solutions. She also serves as an AI policy advisor in Congress, helping align technology development with ethical and societal priorities.
As a candidate for the NAACL Board, I am driven by a commitment to fostering a thriving, inclusive, and impactful NLP community. My vision for NAACL encompasses three key priorities:
Strengthening community connections and policy engagement: I am dedicated to building stronger relationships between the NLP community and underserved populations, ensuring that our research addresses the needs of those who stand to benefit the most from inclusive and accessible AI technologies. At the same time, I aim to deepen connections with policymakers to align our advancements with ethical and equitable priorities. By fostering collaboration between researchers, communities in need, and policy leaders, we can ensure that NLP technologies are developed and deployed to create meaningful societal impact.
Enhancing multilinguality and accessibility: A truly inclusive NLP community must actively support multilingualism, promoting research and resources for linguistically diverse populations and addressing the unique challenges faced by those who speak underrepresented or endangered languages. Additionally, we must do more to ensure our conferences and initiatives are accessible to everyone. This includes providing robust accommodations for deaf and hard-of-hearing participants, neurodivergent individuals, and others with specific needs. By prioritizing both language inclusivity and accessibility, we can create environments where all voices are heard, valued, and empowered.
Supporting new researchers and facilitating collaboration: I recognize the unique challenges faced by early-career researchers and new faculty in our field. My goal is to improve support structures, such as mentorship programs, interdisciplinary team-building initiatives, and resources that empower them to thrive. We can create opportunities for scientifically grounded, societally impactful, and groundbreaking research by fostering collaboration across disciplines and institutions.
Our NAACL community has already achieved so much to support its members, build bridges, and welcome diverse perspectives. I hope to build on these efforts and further strengthen our shared mission of advancing NLP in ways that are inclusive, equitable, and impactful.
Asli Celikyilmaz is a Senior Research Lead at Fundamentals AI Research (FAIR) at Meta. Formerly, she was Senior Principal Researcher at Microsoft Research (MSR) in Redmond, Washington. She is also an Affiliate Associate Member at the University of Washington. She has received Ph.D. Degree in Information Science from University of Toronto, Canada, and later continued her Postdoc study at Computer Science Department of the University of California, Berkeley. Her research interests are mainly in deep learning and natural language, specifically on improving LLM agent’s contextual understanding, reasoning, interaction capabilities, with recent focus on social reasoning. She is acting as TACL co-editor in chief since 2022. She is serving on the editorial boards of Transactions of the ACL (TACL) as area editor and Open Journal of Signal Processing (OJSP) as Associate Editor. She has received several “best of” awards including NAFIPS 2007, Semantic Computing 2009, CVPR 2019, EMNLP 2023.
I am excited to apply for the board membership position at the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL). I have been actively involved in the NLP and ML community for almost 20 years working in university and industry research labs all my career. I have a strong commitment to advancing the field and enabling a diverse and inclusive community.
I believe that NAACL (as well as all the ACL communities) plays a crucial role in shaping the future of NLP. To further strengthen NAACL’s impact, I would like to emphasize the importance of the following three initiatives:
Open Science and Ethical AI: As one of the community leaders and strong supporters, I would like to encourage openly sharing of the research artifacts including the datasets, models, and code, and strongly advocate for ethical guidelines in NLP research and development. Approaches such as incentives could be one step towards encouraging the community in this direction.
Diversity and Inclusion: NAACL should continue to support initiatives that promote diversity and inclusion. I would like to focus on the mentorship programs, outreach efforts, and bias mitigation techniques. In my current role, I am one of the advocates of the DEI efforts and would like to continue working with the NAACL members.
Bridging the Gap Between Academia and Industry: I would like to organize and take active role at workshops and panels at NAACL that facilitate collaboration between researchers and industry practitioners. Such activities has already been going on at ACL conferences and I am committed to taking active role in these efforts.
I am confident in my ability to contribute to NAACL’s mission and vision. I am eager to work with the board and the community to address the challenges and opportunities in NLP field. Thank you for considering my application.
Helena Gómez-Adorno is a Researcher at the Research Institute of Applied Mathematics and Systems (IIMAS) at the National Autonomous University of Mexico (UNAM). She has been actively involved in the NLP community, serving as co-program chair for NAACL 2024. Helena has previously participated as a Reviewer, Area Chair, and Senior Area Chair for NAACL conferences since 2019. Additionally, she has served on the organizing committee of other NLP conferences and in the Mexican NLP Summer School in 2020, 2021, and 2024. She received her Ph.D. in Computer Science from the National Polytechnic Institute (México) in 2018, where she introduced graph-based text representations for various natural language processing tasks. Her Ph.D. thesis was awarded the “Presea Lázaro Cárdenas 2019” for outstanding academic performance as an Engineering and Physical-Mathematical Sciences doctoral student. Her expertise led her to publications on topics related to text classification for authorship analysis, fake news detection, biomedical named entity recognition, and emotion classification, among others. Helena is also an “Honorary Visiting Researcher” at the Polytechnic School of the National University of Asunción (in Paraguay).
I am excited to submit my candidacy for the NAACL board. As a researcher from Latin America, affiliated with two Latin American universities, I can bring a unique perspective to the board, particularly in highlighting the challenges faced by researchers in the Global South. The disparities in access to resources, funding for conference attendance, and institutional publishing requirements shape a very different reality for many of us. This experience drives my commitment to fostering a more inclusive and diverse NAACL, one that addresses issues relevant to the broader American continent, both North and South.
The recent change to The Nations of the Americas Chapter of the Association for Computational Linguistics reflects a significant shift toward inclusivity, acknowledging that NLP challenges and advancements span the entire continent. This name change aligns perfectly with my initiative to increase participation from underrepresented regions, particularly in Latin America. It motivates my efforts to integrate the broader Americas by establishing stronger connections with NLP communities throughout the continent.
If elected to the NAACL board, I would work to:
Increase Latin American community participation by establishing funds for regional workshops organized in collaboration with North American institutions to stimulate collaborations and disseminate NAACL in LATAM. Implement mentorship programs for LATAM students and provide resources such as paper writing workshops.
Promote the participation of underrepresented communities in NAACL on two fronts: 1) Strengthen workshops and initiatives like WiNLP, student workshops, LatinX, and Queer, among others, by connecting with regional initiatives like BRAIC, SIMBig, Iberamia, CLEI, etc. and 2) Encourage the inclusion of broader research areas on the Main Conference through special calls that involve the collaboration from institutions of both the Global South and North, this will facilitate that the underprivileged researcher has ties to stronger institutions that can cover registration fees and not only rely on diversity and inclusion grants. I will also advocate for continuing with a diverse selection of keynote speakers at NAACL conferences, as it has already been in the lasts NAACL editions.
Streamline the organization of NAACL conferences, inspired by my experience as NAACL 2024 (Mexico City) co-program chair. I would focus on integrating event programming with registration processes and creating clear guidelines and toolkits to assist future organizing committees.
Integrate the Latin American industry into NAACL. We can implement many strategies, but first, I would establish an advisory board composed of leaders from major Latin American NLP and technology companies to provide insights into regional needs for shaping conference themes, shared tasks, and other NAACL initiatives relevant to the industry. This integration will contribute to generating resources that will allow financing the participation of LATAM researchers in NAACL.
Philipp Koehn has been a professor for computer science at Johns Hopkins University since 2014, coming from an equivalent position at the University of Edinburgh where he spent almost a decade in the School of Informatics. He is especially interested in machine translation but also speech translation and multilingual aspects of large language models. He is very interested in building real world applications with a positive impact on the world. He founded the Special Interest Group on Machine Translation (SIGMT) and served as its president. He has been organizing the Workshop/Conference on Machine Translation (WMT) for two decades. He wrote two text books on machine translation and over 200 research papers. He served as general chair for EMNLP 2009 and will be general chair for ACL 2026.
NAACL has been at the forefront of advancing research and scholarship in natural language processing and computational linguistics since its inception. I will strive to maintain the quality of research publications in the NAACL conferences and its high level of academic, educational, societal, and economic impact. Specific concerns that I would like to address are:
Broaden the geographic scope of NAACL. Also in view of current and expected problems with visa requirements, I would like to see more conferences to be located outside the United States and fulfill the promise of renaming NAACL as the “Nations of Americas Chapter”.
Working on solutions for hybrid conferences. While the center of gravity has firmly moved back to in-person conferences, I believe that it is important to have avenues for virtual presentations of research results, especially for researchers that do not have the financial means to attend in person. This may take the form of a separate virtual satellite conference or other creative solutions, since the current overlapping virtual/in-person conference design does not work well.
Open research. The field has already moved quite successfully towards increasingly open source repositories for experimental code and data resources alongside research publications. Supporting such efforts should be a strong aspect of NAACL’s mission to dissemination of research results and research collaboration.
Yunyao Li is a Director of Machine Learning at Adobe Experience Platform (AEP), where she leads strategic GenAI initiatives such as AI Assistant in AEP to bring the power of generative AI and knowledge graphs to enterprise. Previously, she was the Head of Machine Learning at Apple Knowledge Platform, where she led the R&D of next-generation solutions for a web-scale knowledge graph to power features such as Siri and Spotlight. Before joining Apple, she was a Distinguished Research Staff Member and Senior Research Manager at IBM Research - Almaden, leading the building and delivery of core language technologies to over 20 IBM products and solutions.
Yunyao is an ACM Distinguished Member. She is a member of the inaugural New Voices program of the US National Academies and represented US young scientists at the World Laureates Forum Young Scientists Forum in 2019. Yunyao has served the CL/NLP and database communities with distinction. She regularly serves as organizer (e.g., track chair, workshop chair), senior committee member (e.g., ACL, NAACL, EMNLP, SIGMOD, and IJCAI), and editorial board member (e.g., TACL and PVLDB). She championed and co-chaired the inaugural Industry Track at NAACL’18, the first-ever industrial track in a major NLP conference. Its success has not only ensured its continuation in future NAACL conferences but also led to the industrial tracks at all major NLP conferences (ACL, COLING, and EMNLP). She has also given interdisciplinary tutorials (e.g., “Explainability for Natural Language Processing”) and organized workshops (e.g., workshops on Data Science with Human-in-the-Loop) to stimulate cross-pollination of research with different research communities. She serves on the Industry Advisory Board for the Master of Science in NLP program at UC-Santa Cruz and the Advisory Board for the CLASIC program at the University of Colorado Denver. She is currently an elected member of the NAACL Board for 2023-24. She received her undergraduate degrees from Tsinghua University and her master’s degrees and Ph.D. in Computer Science from the University of Michigan - Ann Arbor.
As the CL/NLP field experiences rapid growth with the advent of Large Language Models, I’m excited to address the associated opportunities and challenges. As a board member, my key priorities include:
Bridging academic and industry research: The rapid growth of language technologies, especially Large Language Models and their applications, affects both the research community and the daily lives of many people. As a board member, I will continue to support and advocate efforts to bridge academic and industry research and encourage more cross-pollination. I hope to promote a better understanding and appreciation of practical issues related to language technologies in non-trivial real-world systems and influence fundamental research that leads to the next generation of such technologies.
Promoting interdisciplinary work: I aim to continue stimulating more interdisciplinary research within the NAACL community by encouraging more interactions (e.g., invited talks, panels, tutorials, and workshops) with other related communities (e.g., Computer Vision, Visualization, Human-Computer Interaction, Data Management, Robotics, and Social Science).
Supporting growth of the community: As a board member, I would like to continue contributing to and strengthening existing community-building activities (e.g., Mexico Summer School, ACL mentoring, WiNLP) by supporting efforts to enable them for broader impact. In addition, I would like to extend such initiatives to attract more talents (e.g., undergraduates) from diverse backgrounds into the field and provide more support for the growth of senior PhD students, new faculty members, and junior industry researchers.
Tal Linzen is an Associate Professor of Linguistics and Data Science at New York University and a Research Scientist at Google. At NYU, he directs the Computation and Psycholinguistics Lab, which studies the connections between machine learning and human language comprehension and acquisition. Tal was one of the organizers of the first BlackboxNLP workshop in 2018, and was involved in two subsequent iterations of the workshop. He has also served as co-chair of CoNLL 2020, action editor for Computational Linguistics, and Senior Area Chair for a number of *ACL conferences.
I will support NAACL’s continuing efforts to include researchers from across the Americas. To accomplish this, we should lower student registration fees, expand fee waivers for researchers from lower income countries, and have more of our conferences in countries of the Americas other than the United States and Canada. To further improve accessibility, I am also supportive of experimenting with a fully virtual conference alongside or instead of the poorly attended virtual sessions of current hybrid conferences.
As our community has increased in size, there has been a proliferation of procedures around reviewing (e.g. the separation between the review and commitment phases, or the drawn out discussions with reviewers) and conference presentations (e.g. requests to upload posters for oral presentations). The complexity of and frequent changes in these procedures places a substantial burden even on the most committed researchers in the community, deters collaborators from other disciplines from contributing to the conference, and may even incentivize members of the community to submit their work elsewhere. I will advocate to simplify our procedures wherever possible.
I will advocate for the board’s decisions, as well as the ACL executive committee’s decisions, to be as transparent as possible and to reflect the values and preferences of the entire community.
Nanyun (Violet) Peng is an Associate Professor of Computer Science at The University of California, Los Angeles. She received her Ph.D. from the Center for Language and Speech Processing at Johns Hopkins University. Her research focuses on controllable and creative language generation, multilingual and multimodal models, and the development of automatic evaluation metrics, with a commitment to advancing robust and trustworthy natural language processing (NLP). She has received an Outstanding Paper Award at NAACL 2022, three Outstanding Paper Awards at EMNLP 2024, and Oral Paper selections at NeurIPS 2022 and ICML 2023, as well as several Best Paper Awards at workshops affiliated with premier AI and NLP conferences. She was also featured in the IJCAI 2022 Early Career Spotlight. Her research has been supported by prestigious funding sources, including the NSF CAREER Award, DARPA, IARPA, NIH grants, and multiple industrial research awards.
NAACL has seen remarkable growth as the NLP community expands in both size and scope, intersecting with domains like healthcare, law, and education. This interdisciplinary surge highlights the importance of fostering collaborations and ensuring that NAACL remains a space where cutting-edge research and diverse perspectives thrive. If elected to the board, I aim to address key challenges and opportunities to strengthen our community and its impact by focusing on the following areas:
Improving Peer Review Systems: The scalability and quality of peer review have become pressing issues in our growing field. Building on my experience with chairing ICLR 2025 and initiated reciprocal review, I will work with all NAACL board members to explore ways to introduce a similar system where authors actively participate as reviewers, and senior authors are incentivize to review. This approach fosters accountability, ensures a greater pool of informed reviewers, and reduce the overall review load for each participating reviewers (in ICLR 2025, we were able to reduce the maximum review load to 3 papers). Combined with mentorship programs and transparent review processes, this can significantly improve the quality and fairness of feedback.
Enhancing Diversity, Equity, and Inclusion (DEI) & Empowering Young Researchers: Supporting underrepresented groups and young researchers is critical to sustaining our community’s growth. I will advocate for initiatives such as targeted travel grants, year-long mentorship programs with 1-1 mentor-mentee arrangement to empower early-career researchers. By lowering barriers to participation, particularly for those in low-resourced regions, we can ensure that NAACL reflects the full diversity of voices and perspectives in NLP.
Bridging Industry and Academia: As interdisciplinary research becomes increasingly vital, NAACL must serve as a hub for collaboration between academia and industry. I propose creating industrial track for papers and workshops, and formalized panel sessions and networking platforms to facilitate knowledge exchange and communications. By fostering stronger connections, we can ensure that NAACL remains a leader in driving both academic and industrial research of NLP.
With these initiatives, I am committed to ensuring that NAACL continues to thrive as a dynamic, inclusive, and forward-thinking community.
Mihai Surdeanu is a professor in the Computer Science Department at University of Arizona (UA). Before UA, he was a research associate at Stanford University. He also participated in three NLP-centric startups. Dr. Surdeanu works on natural language processing systems that process and extract meaning from natural language texts such as question answering and information extraction. He focuses mostly on interpretable models, i.e., approaches where the computer can explain in human understandable terms why it made a decision, and machine reasoning, i.e., methods that approximate the human capacity to understand bigger things from knowing smaller facts. His work has been funded by several United States government organizations (DARPA, NSF, NIH), as well as private foundations (the Allen Institute for Artificial Intelligence, the Bill Melinda Gates Foundation). He served as (senior) area chair at many NLP conferences and co-organized several workshops, most recently the workshop on “Pattern-based Approaches to NLP in the Age of Deep Learning (Pan-DL).” Lastly, Dr. Surdeanu is a long-term contributor to open-source NLP software.
Should I be elected on the NAACL board, I will propose the following initiatives:
Advocate for the diversity of ideas. As highlighted by the recent EMNLP 2024 panel on “The Importance of NLP in the LLM Era,” the field of natural language processing seems to be in a state of “low entropy.” We are all aware of the limitations of large language models (LLMs). We should actively promote high-risk, high-reward research directions, particularly those exploring radically different architectures with the potential to formally address the known shortcomings of LLMs. To this end, I would like to propose adding a new rubric item on idea diversity to our review process. This would encourage reviewers and area chairs to support innovative and unconventional ideas, even when such approaches currently fall short of matching LLM performance.
Continue to focus on improving review quality. I support the exploration of initiatives aimed at improving review quality and timely submissions. For example, we might consider adopting the Transactions of the ACL framework for reviewing reviewers. Further, we could implement penalties for low-quality or missing reviews, such as temporarily suspending submission privileges for the corresponding reviewers. Finally, we should empower area chairs to request revisions to subpar reviews before these are shared with authors.
Encourage and support first-time conference attendance from students. The first conference I attended had a profound impact on my understanding of the entire research process. Since then, I have observed the same effect on many students in our lab. To encourage early exposure to the research “pipeline”—from ideation to the presentation of completed work—I propose offering a one-time, significant discount for students attending an *ACL conference for the first time.