Thematic Programs

Thematic Programs 2024-2025 Call for Proposals

If you have interests in transdisciplinary research but are not yet ready to submit a seed grant proposal, you may need a community through which you can get broader connections, enhance your skills, broaden your perspective, or generate ideas. To this end, the Data Science TAE is thrilled to launch a new initiative: thematic programs. Below is the call for proposals for thematic programs in 2024-2025. This will be an opportunity to acquire new skills, ignite innovative ideas, forge meaningful collaborations, and, most importantly, nurture a dynamic community of like-minded researchers. We warmly invite you to submit a proposal for a thematic program. Contact Xingye Qiao at (xqiao@binghamton.edu) if you have any questions. Proposal preparation requirements follow.

Thematic program proposals are due March 31, 2024 to Xingye Qiao (xqiao@binghamton.edu).

The Data Science TAE supports research across a spectrum of areas including foundational theories of data science, methodological advancements, and the interface between data science and such fields as social sciences, natural sciences, engineering, and the humanities. To further foster collaborations in emerging areas, we call for proposals of thematic programs for the academic year 2024-2025. A thematic program is a focused research initiative or series of activities centered around a specific theme or topic area that can last one semester or a whole academic year. The theme may be a standalone topic (e.g., “Large Language Models”, “Data Privacy and Security”), cross-cutting (e.g., “Uncertainty Quantification in AI”, “Societal Impacts of Data Science”, “Digital Humanities”), or an application (e.g., “AI for Mental Health”, “Precision Marketing”, “Text-based Inquiries”).  Potential activities in a thematic program may include seminars, invited speakers, collaborator visits, workshops, symposiums, data challenges or data competitions, grant writing meetings, etc. We anticipate the funding of up to two thematic programs each year. The call is open to faculty and graduate students of all disciplines. However, the organizing committee must include at least one regular tenure-track or tenured faculty.

To apply, prepare a document of roughly 2–4 pages that includes the following:

  • Title and nature of the proposed program
  • Names and affiliations of the organizing committee members
  • A brief outline of how the program will be structured
  • Rationale and objectives of the program, including the relevance and the importance of the program, and who will be affected by the program beyond the organizers
  • List potential speakers the program expects to invite (if applicable.) Prior commitment from potential speakers is not required.
  • Intended outcomes and any plan for seeking external funding or more permanent designations in the short and long terms (e.g., campus organized research center, federal-designated center, etc., if applicable.)
  • A brief budget. The budget should be appropriate for the activities proposed and generally should not exceed $2,500 for semester-long programs and $5,000 for programs that last the academic year. Cost-sharing with departments, units, or programs on campus is encouraged.

Interested parties are encouraged to discuss their ideas with the steering committee of the Data Science TAE. A successful thematic program enables a more concentrated and in-depth exploration of specific topics and often draws together a community of researchers, practitioners, and students with shared interests, thereby fostering a sense of community and sustained engagement around the theme. Additionally, through a sequence of events, participants can develop new skills and knowledge pertinent to the theme. Thematic programs also have the potential to attract external experts and leaders in the field, offering participants access to state-of-the-art insights and global perspectives. From the collaborative networks formed, the established track record of collaboration, and the enhanced visibility and recognition gained through the program, a successful thematic program should allow its participants to be better positioned to apply for external funding.

Proposals will be evaluated by the Data Science TAE Steering Committee. A decision should be made by the end of April. Once a proposal is selected, the Steering Committee and the TAE staff will assist the organizing committee members in further development of the program, including budgeting, local arrangements, and the coordination of events.


For the 2024-2025 academic year, the following two thematic programs were awarded:

Transdisciplinary/Interdisciplinary Conversations towards a Digital Humanities Laboratory

Program webpage: https://sites.google.com/binghamton.edu/dhlabandincubator/home

Program description: The Digital Humanities Laboratory Collaborative facilitates ongoing discussions and work within the digital humanities community at Binghamton University. The DH Laboratory hosts campus conversations, guest speakers and hackathons to elevate and illuminate digital humanities work and methods and integrate them more fully into campus scholarship and initiatives. This program is ongoing in the current semester, fall 2024. Please check the webpage listed above for more information. 

Governing body:

John Cheng, Asian and Asian American Studies (jcheng@binghamton.edu)
Ruth Carpenter, Libraries (rcarpen@binghamton.edu)
Bradley Skopyk, History (bskopyk@binghamton.edu)
Kent Schull, History (kschull@binghamton.edu)

Data Science and Artificial Intelligence for Scientific Discoveries

Program description: The program will feature a series of invited lectures and a mini-workshop, with a portion of the invited speakers being jointly presented with the NERCCS 2025 conference (https://nerccs2025.github.io/). The mini-workshop will consist of presentations by Binghamton University faculty, blending research talks with survey, review, and tutorial-style talks. This structure aims to engage a broader audience, including those interested in, but not yet actively involved in, topics such as reinforcement learning for controlling nonlinear dynamic systems. By including more survey talks, we hope to inspire new participants and collaborations while encouraging transdisciplinary approaches. This program will launch in the spring 2025 semester.

Governing body:

Adnan Siraj Rakin, School of Computing (arakin@binghamton.edu)
Manoj Agarwal, School of Management (agarwal@binghamton.edu)
Weiying Dai, School of Computing (wdai@binghamton.edu)
Kenneth Chiu, School of Computing  (kchiu@binghamton.edu)
Michael Lawler, Physics, Applied Physics and Astronomy (mlawler@binghamton.edu)
Hiroki Sayama, School of Systems Science and Industrial Engineering (sayama@binghamton.edu)
Zeynep Ertem, School of Systems Science and Industrial Engineering  (zeynep@binghamton.edu)