The control and administration of the affairs of the Society shall be vested in an Executive Committee consisting of the Officers, 2 Members-at Large, a Secretary, and Treasurer. For all purposes, the Executive Committee shall also constitute the Board of Directors of the Society. The officers of the Society shall serve on the Executive Committee during their term of office. The remaining members of the Executive Committee shall serve for a term of three years. The President of the Society shall be the Chair of the Executive Committee. For the purpose of establishing the Society leadership, staggering terms of each position may be set during the initial 3-year cycle of the Society.
Current members of the Society are eligible to vote. Voting will close December 7, 2026.
President-Elect Candidates
Ashley Naimi
I see causal inference as one of the most powerful unifying forces in science. Across the breadth of science, researchers confront causal questions, creating extraordinary opportunities for the Society for Causal Inference. I am honored to be a candidate for President-Elect because I believe SCI can become the intellectual and professional home for this increasingly diverse community, a place where methodologists and applied researchers come together to advance causal inference and science more broadly.
I have been involved with the causal inference community and its annual meetings since the Society’s early years. During that time, causal inference has grown enormously as both a methodological field and a framework for scientific inquiry. I would like SCI not simply to reflect that growth, but to help lead it by increasing the Society’s visibility, expanding its membership across disciplines, and strengthening connections with researchers and practitioners in government and the private sector.
Central to that effort is strengthening the connection between methodological development and substantive application. Some of the most productive conversations in causal inference occur when theoretical and applied researchers engage seriously with one another. As President, I would spearhead a number of initiatives towards these efforts.
The annual meeting already serves as a powerful venue to bring extraordinarily talented researchers together. As president, I will seek to expand opportunities for our members to engage with one another and bring together a broad range of methodological and applied research perspectives in pursuit of meaningful and impactful science. SCI should continue to be a place where new methods are developed and debated, old methods are re-envisioned, and where we ask how those methods perform when confronted with the messy nuances of applied work.
Training should also be central to SCI’s mission. I would like SCI to provide more opportunities for rigorous, accessible training in emerging methods to a variety of audiences, both at the annual meeting and throughout the year, and to make the extraordinary methodological expertise within the Society accessible to a broader community.
I would lead SCI to invest more deliberately in mentorship, creating opportunities for junior scholars to build relationships with senior researchers and fostering intellectual connections across disciplinary, methodological, and applied boundaries.
Finally, I believe SCI can play a larger role in shaping how causal inference is taught. Institutions across many fields are now grappling with what students and professionals should learn, and how training should be structured. SCI can become a resource for departments, government agencies, and the private sector developing standards, curricula, courses, and training programs, drawing on the collective expertise of its membership to help define rigorous, modern training in causal inference.
My own career has moved between methodological and applied research, teaching and mentorship, and graduate-program development. Those experiences have reinforced my belief that the future of causal inference depends on rigor coupled with intellectual openness, across disciplines, methodological traditions, and the divide between theory and application.
The scientific questions that unite us are much larger than the disciplinary boundaries that separate us. As President, I would work to make SCI the organization that brings that community together: broadening its reach, strengthening its intellectual community, and expanding opportunities for training and mentorship.
I earned my PhD in epidemiology, with a minor in biostatistics, from the University of North Carolina at Chapel Hill, and completed postdoctoral training in epidemiology and biostatistics at McGill University. Following faculty appointments at McGill and the University of Pittsburgh, I moved to Emory University, where I am now Professor of Epidemiology at the Rollins School of Public Health, with a secondary appointment in the Department of Data and Decision Sciences.
I have served as Associate Editor of the American Journal of Epidemiology since 2016, have been on the editorial board of Epidemiology since 2015, and have been a Methodological Editor of Fertility & Sterility since 2021. I have been a member of the Society for Causal Inference since its early days (Chapel Hill, 2017).
My research focuses on the development and application of causal inference methods to questions in reproductive, perinatal, and nutritional epidemiology. I have written several papers for disseminating causal inference methods to broad audiences, including “An Introduction to G Methods” and “Stacked Generalization: An Introduction to Super Learning.” As principal or co-principal investigator of several NIH grants, I have used and am using a range of causal inference methods to estimate effects in applied settings.
Much of my efforts are focused on teaching causal inference to the wider research community. I have taught advanced methods workshops at various conferences, and regularly deliver short courses to researchers across academia, government, and industry. I am the co-Editor (with Brian Whitcomb) of the American Journal of Epidemiology’s “Classroom” series, that focuses on dissemination of causal inference and other methods for empirical science.
Jason Roy
- One of the things I value most about the causal inference community is that it has always felt small in the best sense: people know one another, exchange ideas openly, and build collaborations across institutions and disciplines. From the early Mid-Atlantic Causal Inference Conference to ACIC and the Society for Causal Inference, our community has grown substantially while retaining much of that spirit. If elected president, I would support continued growth while preserving the collaborative character that has been central to the community’s success.A priority would be to work with SCI’s leadership and committees to create opportunities for students, early-career researchers, and first-time ACIC attendees to meet colleagues, share their work, and develop collaborations. I would also support efforts to broaden participation across disciplines and connect researchers developing causal methods with those applying them to substantive problems.Advances in machine learning and artificial intelligence, new sources of data, and increasing demand for causal evidence are creating opportunities for our field. Causal and statistical reasoning are more important than ever. SCI is well positioned to bring researchers from different methodological traditions and applied fields together to engage with these developments while keeping causal questions, study design, and assumptions at the center. As president, I would work to strengthen SCI’s role in these conversations through its conferences, educational activities, and connections with other research communities.I would bring to this role my experience in academic leadership, causal inference research, and education, with a focus on supporting SCI’s continued development as a society and a forum for scientific exchange.
- Jason Roy is Distinguished Professor of Biostatistics and Chair of the Department of Biostatistics and Epidemiology at Rutgers University. Previously, he was a faculty member at the University of Pennsylvania, where he was founding co-director of the Center for Causal Inference. His research focuses on Bayesian nonparametric methods for causal inference, including causal mediation and dynamic treatment strategies. He has extensive collaborations in pharmacoepidemiology, where he works on the design and analysis of studies using real-world healthcare data. He is a Fellow of the American Statistical Association and co-author of Bayesian Nonparametric Methods for Causal Inference and Missing Data (2023).Jason has a longstanding commitment to making causal inference methods accessible to researchers across disciplines. He developed A Crash Course in Causality on Coursera and received the American Statistical Association’s Causality in Statistics Education Award in 2021. He has taught numerous short courses and workshops nationally and internationally, published tutorials and software, and mentored students and early-career researchers working in causal inference. His leadership experience includes building academic programs and research teams at Rutgers, chairing the ASA’s Council of Sections Governing Board, and co-chairing the North American Biostatistics Chairs Executive Committee.
Member-at-Large Candidates
Rohit Bhattacharya
- Hi all!
I’m Rohit. I’ve been serving on the professional development committee of SCI for the last couple of years. In this capacity, I’ve helped organize some of the SCI programming that I hope you (or your students!) have found useful. This includes the mentorship roundtables at ACIC, and invited panels throughout the year for discussing grant writing tips and potential career pathways in causal inference.I’m excited to be running for member-at-large this year. Academia has changed a lot in the last couple years (we all know why.) The primary goals, though, have remained the same: (1) continue pursuing high-quality research that pushes the boundaries of causal inference, and (2) continue finding healthy ways to advise and mentor students, so they can achieve their own intellectual goals, and ideally, secure future employment. It is the case, however, that it is becoming increasingly difficult to uphold the systems that allow us to achieve these primary goals. Peer review systems are strained with AI-generated papers, and there is a concern whether advising and teaching styles need to radically change in order to prepare students for such a future.While ACIC is not a peer-reviewed conference itself nor is SCI a body that makes decisions on publication, I do believe these are avenues through which we can host productive discussions as a community on how to respond to these challenges. So, in my position, I would advocate for such efforts, while also supporting the regular functioning of ACIC as the rigorous conference that we all know and love, where we connect with other like-minded causologists*.* Causology is a term that came up accidentally during a sabbatical I had in Cambridge, UK. A friend (Sally Coleman) forgot what field I work in, and responded with “causology” to a question about it. Jessica Young and I loved the term, and we’ve been trying to make it a thing ever since 🙂
- I’m a computer scientist at Williams College working in causal inference. Despite my home department, I view ACIC, EuroCIM, and UAI to be my home conferences, all of which can be solidly classified as conferences about causal inference. My primary areas of research are in causal graphical models, missing data, and computational genomics. Working at a liberal arts school, I value the teaching and mentoring side of my job just as much as I value my research. In my free time, I enjoy playing the drums and, more recently, tennis!
Ashkan Ertefaie
Dear Colleagues,
I am running for Member-at-Large of the Society for Causal Inference because I value a community where researchers across disciplines can exchange ideas, question assumptions, and learn from one another. SCI brings together people with different methodological perspectives and substantive interests, and I would welcome the opportunity to help strengthen those connections.
If elected, I would make strengthening ACIC’s financial sustainability a priority. Working with the Board and conference organizers, I would help develop a coordinated sponsorship program involving pharmaceutical and technology companies whose work draws on causal inference. Drawing on approaches used by other scientific conferences, this could include sponsorship packages that combine conference visibility with recruiting and networking opportunities, alongside dedicated support for student travel. I would also help maintain continuity in sponsor outreach across conference years, with the goal of making funding more predictable, keeping participation affordable, and preserving scientific independence.
I would work to broaden opportunities for participation, particularly for students, early-career researchers, and members whose institutions have smaller causal inference communities. Mentoring activities and opportunities for discussion at ACIC and throughout the year could help members build lasting professional connections.
I would also support educational activities that bring methodological and applied researchers into closer conversation. Sessions organized around real research questions could illustrate how different causal approaches address the same problem, clarify their assumptions, and identify gaps that warrant further research.
My research, teaching, mentoring, and editorial work have given me opportunities to engage with a wide range of perspectives in causal inference. As Member-at-Large, I would bring that experience to the Board, listen carefully to members’ priorities, and help translate their ideas into practical activities. I would be grateful for the opportunity to serve SCI and contribute to an inclusive and intellectually engaged community.
Best regards,
Ashkan Ertefaie
Ashkan Ertefaie is a tenured Associate Professor in the Division of Biostatistics at the University of Pennsylvania’s Perelman School of Medicine. He earned his PhD in Statistics from McGill University in 2011 and completed postdoctoral training at the University of Michigan and the Wharton School of the University of Pennsylvania. Before joining Penn, he served on the faculty of the University of Rochester.
Ashkan’s research focuses on causal inference, semiparametric methods, and individualized treatment strategies. He develops statistical methods for observational studies and randomized trials, with particular interests in unmeasured confounding, longitudinal data, and sequential treatment decisions. His collaborative research spans substance use, Parkinson’s disease, and environmental health, connecting methodological developments with questions in clinical and public health research.
Teaching, mentoring, and professional service are central to Ashkan’s academic work. He has taught graduate courses in causal inference, semiparametric theory, and statistical inference and has mentored doctoral students and postdoctoral fellows. He serves as an Associate Editor for several journals, including the Journal of the American Statistical Association, Biometrics, and Biostatistics. He values opportunities to bring researchers with different backgrounds and perspectives into conversation and to support the next generation of causal inference researchers.
Secretary Candidates
Andrej Srakar
- Dear Colleagues,
I would be very pleased to serve the Society for Causal Inference as Secretary.
SCI has developed into an important international community for researchers and practitioners working on causal inference across statistics, economics, epidemiology, computer science, and other fields. As the Society continues to grow, I believe that good communication, continuity, and connections among its members will become increasingly important. I would like to contribute to this work by bringing my experience in coordinating international scientific communities and activities to the Society.
Much of my academic service in recent years has involved precisely this kind of work. I currently coordinate YoungStatS, an international initiative of Young Statisticians Europe, and have been involved in developing its webinar and blog activities in cooperation with FENStatS, the Bernoulli Society, and the Institute of Mathematical Statistics. I also coordinate the Cultural Economics Online Seminar and serve on the Communications Board of the Association for Cultural Economics International. Within the Royal Statistical Society, I serve as a committee member and Meetings Secretary of the Emerging Applications Section and have been involved in the organization of its Discussion Paper Meetings. I have also organized and chaired international scientific meetings, including the 23rd European Young Statisticians Meeting in 2023.
These experiences have taught me how important the less visible organizational work of a scientific society can be. Clear communication, careful follow-up of decisions and activities, continuity between committees and boards, and making it easy for members from different countries and disciplines to participate all contribute to a healthy scientific community. As Secretary, I would be glad to contribute to SCI in these areas.
My own research interests include the mathematical foundations of causality and causal inference, alongside probability, statistics, econometrics, and artificial intelligence. I therefore particularly value the interdisciplinary character of SCI and the opportunity it provides for researchers with different methodological backgrounds to meet and exchange ideas. I would hope to contribute, in a practical and constructive way, to maintaining this character as the Society develops.
I would see the position of Secretary primarily as a service to the Society and its members. My experience in coordinating international projects, scientific meetings, seminars, and professional-society activities has prepared me well for this responsibility, and I would be honored to put that experience at the service of SCI.
Best Regards,
Andrej Srakar
- Andrej Srakar is a researcher at the Jozef Stefan Institute and a Lecturer at the School of Economics and Business, University of Ljubljana. His research interests lie at the intersection of probability, statistics, econometrics, and artificial intelligence, with particular interests in the mathematical foundations of causality and causal inference, Bayesian methods, and applications of quantitative methods in the social sciences. He is a member of the Society for Causal Inference and several other international statistical and scientific societies.
Srakar has extensive experience in international academic and professional-society service. He is Coordinator of YoungStatS, an international initiative of Young Statisticians Europe, and has developed its international webinar and blog activities in cooperation with FENStatS, the Bernoulli Society, and the Institute of Mathematical Statistics. He also coordinates the Cultural Economics Online Seminar and serves on the Communications Board of the Association for Cultural Economics International. Within the Royal Statistical Society, he is a committee member and Meetings Secretary of the Emerging Applications Section and has been involved in the organization of its Discussion Paper Meetings.
He has organized and chaired international scientific meetings, including the 23rd European Young Statisticians Meeting in Ljubljana in 2023, and has been involved in the organization of international conferences and seminars in statistics and related fields. His current work includes research on the mathematical foundations of causality and causal inference. He is scheduled to teach a short course on the Mathematical Foundations of Causality at the American Causal Inference Conference in 2027, and presented at the ACIC conferences in 2022, 2023 and 2026.
Falco Bargagli-Stoffi
- Dear Colleagues,Causal inference has been my intellectual home since the very beginning of my graduate studies, and I would be glad to give back to this community by serving as SCI Secretary.This is work I know and enjoy. I have served as Secretary of the Faculty Executive Committee at the UCLA Fielding School of Public Health, and currently serve as co-director of the university-wide Practical Causal Inference Lab at UCLA, where I work to bring researchers from different fields into causal inference. As SCI Secretary, I would focus on two things: keeping members informed and up-to-date about what the society decides and why, and making it easier for students, early career researchers, and colleagues from applied fields to find their way into SCI’s committees and activities beyond the annual meeting.Thank you for considering my candidacy.
Falco J. Bargagli-Stoffi is a faculty member in Biostatistics at the UCLA Fielding School of Public Health, where he leads the Precision Interventions Lab and co-directs the Practical Causal Inference Lab. His research develops causal inference methods for discovering heterogeneous effects, handling complex treatments, and accounting for interference and spatial structure, with applications to public health, environmental health, and medicine, often using large-scale data. He completed his undergraduate studies at the University of Florence, received a joint PhD from KU Leuven and IMT Lucca, and was then a postdoctoral fellow at Harvard. Outside of work, he loves trail running, hiking, gravel biking, and anything outdoors.