AI & Society College

The aim of the Faculty Innovation Fellowship is to incubate, catalyze and support innovative, faculty-led, academic initiatives that expand the range and depth of UAlbany’s AI-infused curriculum.  

This includes engaging students in the development of AI, the application of AI, critical inquiry into broader questions of AI’s significance for the human condition, and creative projects that deploy or comment on AI.  

Outputs may include the development of:

• Courses and academic programs
• Faculty training and upskilling (applicant could be the trainer or the trained)
• Microcredentials
• Creative projects, exhibitions, events
• Symposia or campus events
• Educational software or AI-tools for the classroom
• Teaching materials, textbooks

We are also open to applications that combine the above elements as well as suggestions for other kinds of initiatives. Priority will be given to projects that meaningfully engage experts across disciplines.

If you are not sure whether your project is appropriate, feel free to reach out to Hany Elgala at [email protected] or Mila Gasco Hernandez at [email protected].  

Tasks: Fellows will complete the project described in their application within the 2026-2027 Academic Year.

Mentoring: Fellows will meet every other week with their assigned mentor.

Participation: Fellows will be expected to take part in the AI & Society College and AI & Society Consortium events. In addition, fellows will be expected to participate in a videotaped interview with AI & Society College leadership for the College’s website and/or to write one to two articles/blog posts.

Progress and final reports: Fellows will be expected to report their progress at the end of the Fall 2026 semester and to write a detailed final report describing the work undertaken at the end of the Spring 2027 semester. 

We encourage applications from non-tenure-track, tenure-track and tenured faculty across academic units.

Applicants must submit a CV (maximum three pages) and a document that includes responses to the following prompts:

1. Describe the aim and scope of your project. (300 words maximum)
2. Describe the steps necessary to realize this project. (300 words maximum)
3. Do you have collaborators on this project on or off campus? (200 words maximum)
   • Preference will be given to projects that involve collaborations across disciplines and academic units.
4. What form of support would be most useful to support the completion of your project?  
   • You may select one course release (specify semester), or you may select one or more of the following options, with the total funding not to exceed the total of one course release ($6,000):
     • Research funds (specify use of research funds, including equipment, training, travel and supplies)
     • Graduate Assistant (specify number of hours)
     • Stipend or summer salary
     • Other (please specify)

Materials should be submitted to Dr. Mila Gascó-Hernandez at [email protected].

Applications are due by March 15, 2026, and decisions will be communicated by April 15, 2026. The fellowship will start on August 24, 2026.

The fellowship provides a $25,000 stipend as well as tuition waiver for one year to support PhD students as they work on their dissertations and pursue AI research aimed at addressing societal challenges.  

AI & Society Doctoral Dissertation Fellows will join a vibrant, interdisciplinary community of scholars dedicated to leveraging AI for positive social impact.

Fellows will be expected to:

• Teach one section of UUNI 118: Introduction to Artificial Intelligence, which is a one-credit, three- to four-week course. No previous specialized or technical training is required to teach this class, and fellows will be provided with all teaching materials.
• Present work-in-progress at AI & Society College roundtables with other fellows or at AI & Society College events, such as interdisciplinary research discussions
• Mentor undergraduate and master’s students working on AI & Society projects
• Contribute to the College’s development by monitoring the email account, posting on social media, organizing events, providing administrative support, and finding funding opportunities, among other tasks. A specific task will be given to each of the fellows, with assignments taking each fellow’s background and interest into account. Follow-up meetings with the director and/or associate director will be scheduled on a regular basis.
• Be ambassadors of the College by representing the College with integrity, engaging actively in its events and outreach, promoting a positive image in all interactions, and sharing experiences to inspire others 

We seek proposals on AI research from disciplines across UAlbany's nine schools and colleges. Successful proposals must demonstrate attention to the social or ethical implications of artificial intelligence.

This may include critical or historical reflection on AI’s significance for the human condition, artistic practice that deploys AI or critical analysis of the implications of AI for creative practice, and the application of AI for addressing real-world problems.  

Required Qualifications:

• Be a current UAlbany doctoral student in the final year(s) of a PhD program (preference will be given to fourth- and fifth-year PhD students)
• Demonstrate academic excellence and research potential
• Describe research focuses on AI in the context of societal impact

Preferred Qualifications:

• Involved in interdisciplinary collaboration and public engagement

Note: Applicants will not be eligible if they are already funded (for example, through graduate or research assistantships) or are already working at the allowed PhD student work hours. 

Applicants must submit:

• A research proposal (maximum two pages), outlining:
  • Project objectives and potential societal impact
  • Methodology and timeline
  • Interdisciplinary collaboration plans
• A one-page personal statement on their commitment to AI for social good and the fellowship expectations
• A CV (maximum three page)
• A letter of recommendation from their dissertation supervisor  

Fellows will be selected based on:

• Their academic record
• The rigor, originality and relevance of their proposed research
• Their interdisciplinary approach and collaborative potential
• Their commitment to responsible AI development and public engagement

Materials should be submitted to Dr. Mila Gascó-Hernandez at [email protected]. 

Applications are due by March 15, 2026, and decisions will be communicated by April 15, 2026. The fellowship will start on August 24, 2026.

About Rawan Abdelaal 

Rawan Abdelaal is a PhD student in curriculum and instruction at the University at Albany. 

She holds a bachelor’s degree in biotechnology from the City College of New York and a master’s degree in curriculum development and instructional technology from UAlbany. 

Her research explores the relationship between artificial intelligence (AI) and computational thinking (CT) at the intersection of science education. 
 

About Rawan Abdelaal's Dissertation

With the rapid advancement of AI and its ubiquitous presence in daily life, she seeks to investigate and develop methods that promote ethical, critical and effective uses of AI in K–12 classrooms, empowering educators and students to engage thoughtfully and responsibly with intelligent technologies. 

About Karan Bhasin

Karan Bhasin is a PhD candidate in Quantitative Economics and Econometrics at the University at Albany, SUNY.

His research lies at the intersection of monetary economics and applied econometrics, with a focus on how economic agents process information and update their expectations — insights that are critical for understanding inflation dynamics, fiscal policy, and macroeconomic stability.

Karan’s work has been featured in The Economist and The Wall Street Journal and has also appeared in leading policy platforms such as the Brookings Institution, VoxEU and Econofact, reflecting its broad relevance to both academic and policy audiences.

He has held research and policy roles at the International Monetary Fund, World Bank, Empire State Development (New York State), and MyGov, Government of India, bringing a global and applied perspective to his academic work. 

Currently, Karan is exploring the use of natural language processing (NLP) techniques to identify and quantify policy shocks, leveraging textual data to uncover latent signals in economic policymaking.
 

About Karan Bhasin's Dissertation

This thesis investigates the behavior of professional forecasters using data from the Blue-Chip Economic Indicators, applying a Bayesian learning framework that incorporates forecaster inattention. We address a central challenge in macroeconomic policy evaluation: identifying unanticipated monetary policy shocks. Unlike the natural sciences, macroeconomics cannot rely on controlled experiments to establish causality. 

To overcome this limitation, we deploy Large Language Models (LLMs) to systematically extract unanticipated shocks from textual data. By conditioning LLMs on specific sources and temporal contexts, we constrain their information set and improve the precision of causal inference. 

This methodology offers a robust tool for policymakers and researchers to evaluate the effects of monetary interventions and to better understand how professional forecasters respond to economic developments. Moreover, we introduce a novel identification strategy for forecaster inattention that utilizes both individual and consensus forecast revisions. 

Our analysis reveals that zero forecast revisions tend to overstate inattention, and that inattention is horizon-specific, driven in part by the regularity of statistical data releases. Persistent forecast disagreement is attributed to heterogeneous interpretations of news, although periods of club-convergence emerge during large economic shocks.

About Anastasios Karnazes

Anastasios Karnazes is a PhD candidate in English Studies at UAlbany, researching the material transformation from book technologies to artificial intelligence (AI) systems and its effects on aesthetic production. 

He is the author of Rainbow Sonnets 20, published by The Song Cave, and founder of Theaphora, an experimental book and game publisher. His work has been covered in Artforum, ARTnews, Spike Magazine, and Forbes.
 

About Anastasios Karnazes' Dissertation

This dissertation positions artificial intelligence as the exhaustion point of book logic — the moment when Enlightenment systems of knowledge production, replication, and distribution culminate in computational infrastructure and become fully legible as a unified financial, political, and aesthetic project. 

The work traces how information compression functions transformed through the printing press, encyclopedia, digital storage, networked infrastructure, and cloud computing to the memory systems undergirding AI development, arguing that this transformation refracts into dual domains: the collapse of financial systems into speculative bubbles and the aesthetic-cultural reconfigurations that respond to this trajectory. 

Drawing on both historical analysis of dissemination infrastructures and documentation of experimental work in publishing and text editor development, the dissertation demonstrates the prefiguring relationship between literary production mechanisms and computational intelligence systems, positioning AI not as revolutionary break but as the terminal form through which the book's historical trajectory becomes visible.

The College encourages undergraduate students interested in artificial intelligence to explore the following courses:

• UUNI 118: Introduction to Artificial Intelligence
• CINF 135: Concepts of Artificial Intelligence

Visit the Schedule of Classes to explore upcoming course offerings.

Microcredentials are a collection of courses and certificates that help learners build in-demand skills and competencies.

• AI Plus Fundamentals: This for-credit program includes undergraduate courses, which can stack towards a degree.
• Artificial Intelligence for Business: This for-credit program includes graduate courses, which can stack towards a degree. 

Visit the Professional and Continuing Education (PaCE) website to learn more about microcredentials. 

Google and SUNY have partnered to give SUNY students, faculty and staff free access to Google AI learning opportunities.  

Visit the Free Google AI Certificates at SUNY webpage for more information.