Newsletter Summer 2026: AWARE-AI / Universal AI at RIT

By the numbers:

90+ AWARE-AI trainees
26 stipend-funded trainees
70+ AI research publications
8 hackathons
9 trainee seed funding awards
5 NRT+ network alliance institutions
1 Universal AI summer lab rotation

Universal AI trainees Paige DeVries and Joe Merino stand on either side of a large outdoor sign spelling out RIT on a sunny day

Photo: Trainees Paige DeVries (left) and Joe Merino (right) from Gallaudet University on the first day of their 8-week lab rotation to RIT as part of the Universal AI program.

Message from the Director

Dear AWARE-AI Community,
This summer issue celebrates some of the numerous recent research advancements and other achievements of trainees, faculty, and staff in AWARE-AI. Recently, the AWARE-AI community has also reached some key milestones with over 70 publications and over 90 trainees.

Currently, we are enjoying the flurry of research activities associated with the first round of Universal AI summer lab rotations at RIT. This newsletter introduces Universal AI trainees Joe Merino and Paige DeVries, visiting from Gallaudet University (GU), who are conducting original innovative research on RIT’s campus, while being provided with technical and professional development opportunities. We also thank them for making extra time to help guide a project conducted by a team of undergraduate researchers. It is exciting to see the network of collaborations that has emerged already, thanks to this summer’s Universal AI lab rotations. RIT PhD students Cedric Bone and Rajesh Titung have also been instrumental contributors, in addition to faculty, staff, and GU partners.

A key extension of AWARE-AI is the NRT+ Network Alliance. It has grown to five NRT partners when Gallaudet joined Clemson, Cleveland State University, University of Wisconsin–Madison, and RIT in this initiative. We encourage you to read about the most recent NRT+ summit below. NRT+ faculty have also embarked on collective research envisioning efforts and the planning of next steps in the NRT+ partnership.

We have also seen many recent individual achievements. In addition to trainees who have graduated and accepted new positions, there are numerous examples of trainees publishing research in esteemed venues and accomplishing other activities, such as completing formal mentoring training, earning recognitions, or serving the broader community. We have also celebrated faculty colleagues who have earned tenure and promotion or been awarded grant support. Our team has expanded with new faculty affiliates, highlighted below in addition to featured trainees.

For Fall 2026, we will welcome our fifth full-year cohort, comprising 16 graduate students from PhD and MS STEM programs at RIT. Their AWARE-AI experience begins with the three-day AWARE-AI Onboarding Bootcamp, August 19-21, 2026. Incoming trainees on fellowship will pursue individual research projects and development plans in coordination with their research track mentors. The AWARE-AI team looks forward to a productive year together.

Finally, I want to thank AWARE-AI alumni and continuing trainees, the members of our faculty and staff team, external evaluator Dr. BaileyShea and her team, RIT leadership including Deans and the Vice President for Research Dr. Raffaelle, the AWARE-AI Internal Advisory Board and external Independent Advisory Committee, supporters, and other stakeholders who dedicate time to championing or enhancing AWARE-AI through their involvement.

Enjoy the rest of the summer and the kickoff of an exciting new academic year!

-Cissi, on behalf of the AWARE-AI / Universal AI at RIT team

Explore AWARE-AI at RIT

Four people sit at a table with laptops in front of them. Two of them are looking at something on a laptop screen while the other two are watching a presenter out of frame.

Photo: AWARE-AI trainees (from left to right) Karthik Subramanian, Odysseus Adamides, Victor Lockwood, and Rodney Sanchez during a session at the IIEEE Summer School on Telerobotics and Cyborg Technologies.

Select Achievements

AWARE-AI trainee and PhD candidate Calvin Nau is the first author of a research article in the journal Decision Analysis. The article was co-authored with AWARE-AI faculty Katie McConky, Ali Baheri, Cecilia Alm, Reynold Bailey, and additional researchers at SUNY Buffalo.
AWARE-AI affiliate Richard Lange and research track co-lead Alexander Ororbia received a new NSF award titled Advancing NeuroAI through Biologically-Plausible Self-supervised Learning."\
AWARE-AI trainee and PhD student Muhammad Raees presented research at the 2026 CHI conference in Barcelona. Congratulations to Muhammad and his co-authors for being honored with a Best Paper Honorable Mention Award!
AWARE-AI trainee and Data Science MS alumni Gaurank Maheshwari presented a student abstract/poster at the 2026 AAAI Conference in Singapore.
The HCI for AI research track lead Jamison Heard, co-lead Garreth Tigwell, and track affiliate Roshan Peiris were awarded tenure and promotion. Congratulations to all!
We are excited about AWARE-AI’s publication footprint in the journal publication spaces. Over the last few years, AWARE-AI trainees have been authors of articles in impactful journals such as ACM Transactions on Accessible Computing, ACM Transactions on Human-Robot Interaction, Frontiers in Computational Neuroscience, Decision Analysis, Proceedings of the ACM on Computer Graphics and Interactive Techniques, IEEE Access, IEEE Transactions on Affective Computing, IEEE Transactions on Human-Machine System, Journal of Computing and Information Science and in Engineering, Machines, Sensors, Robotics, Scientific Reports, and Transactions on Machine Learning Research. Congratulations to these trainees and their co-authors!
AWARE-AI trainees Rodney Sanchez, Victor Lockwood, Sophia Caruana, Karthik Subramanian, and Odysseus Adamides participated in the IEEE Summer School on Telerobotics and Cyborg Technologies, which was organized by AI hardware research track lead Dr. Ferat Sahin on RIT’s campus in July 2026. In addition, HCI/HRI for AI research track lead Jamison Heard delivered a lecture titled Shared-Control with Reinforcement Learning: Sensing the Operator and Closing the Loop to summer school participants.
To better support the Universal AI project and its trainees, AWARE-AI Project Coordinator Angie Armstrong is attending ASL classes through the NSLARC Faculty and Staff Sign Language Program, offered by the National Technical Institute for the Deaf.

Trainee Rajesh Titung stands at a table displaying a laptop, monitor, and peripheral devices related to research

Photo: AWARE-AI trainee Rajesh Titung presented his AWARE-AI research during a tour by members of the Board of Trustees of RIT’s new Research Lab building.

Trainee Spotlights

Paige DeVries - Universal AI Lab Rotation

Paige DeVries is a hearing graduate student at Gallaudet University with a masters degree in interpretation and research that has been working in the Human Computer Interaction (HCI) field for approximately four years. Their research interests center on accessibility, especially for Deaf and Hard of Hearing (DHH) people. They believe that incorporating accessibility from the outset is the best approach for both developers and users. Developing with accessibility in mind leads to higher quality products and fewer challenges, and it also avoids substantially greater costs, in contrast to remediation after development.

Paige is fluent in American Sign Language (ASL) and well versed in American Deaf culture. They are learning more about Human Robot Interaction at RIT this summer and conducting research around it. They are conducting an exploratory, two-part study hoping to determine DHH familiarity and comfortability with robots as well as ask what an ideal interaction would look like. As robots become more common, this project looks at those who do not use speech so we can build in accessibility from the start into those products.

Joe Merino - Universal AI Lab Rotation

Jose "Joe" Merino is a Deaf researcher and a full stack web developer with a MA in ASL Linguistics from Gallaudet University. He is completing his final semester in the Accessible Human-Centered Computing and Policy MS graduate program before beginning his PhD in the same field in Fall 2026. As an NRT-IPP Universal-Al trainee, Joe embodies the interdisciplinary vision of the program. His work integrates computer vision, large language models (LLMs), human-centered design, and policy to improve AI systems for signed language communities that have historically been underserved by mainstream AI research and development. His research focuses on sign language recognition and accessible AI, including the development of an LLM-assisted communication tool that is expected to be patented later this summer.

During his 8-week lab rotation at RIT as part of his NRT-IPP Universal AI training, Joe has been exploring the effects of head-mounted displays (HMDs) on ASL user interactions with social robotics with PhD student Cedric Bone, Dr. Cecilia O. Alm and Dr. Reynold Bailey. For example, HMDs like the Apple Vision Pro occlude part of the face, where non-manual markers such as eye-brow position, mouth morphemes, and head movements convey both grammar and affect in ASL. The HMD also adds physical weight to the signer. It is unknown whether wearing the headset changes the signer’s cognitive load, perceived usability, or self-perception of their ASL use. This study aims to establish UX baselines for signing in XR that provide the first steps toward a systematic understanding of how XR hardware affects the user’s self-perception of their signing experience.

In his free time, Joe also enjoys playing soccer, traveling, and working on his car.

Sophia Caruana - AWARE-AI

Sophia Caruana is a second year PhD student in Cognitive Science. She works in the Computational Linguistics and Speech Processing lab with Dr. Cecilia Alm. She graduated from Nazareth University in 2024 with a major in Ethical Data Science and minors in Math, Psychology, and Philosophy. Sophia primarily studies computational characterization of conflict de-escalation in human-human and human-robot dialogues. She has also applied her interdisciplinary knowledge to work for the Air Force Research Laboratory (AFRL), and visited CCNY in New York to present her work. Moreover, she has a passion for undergraduate mentorship and teaching; she served as a PhD student mentor in the UR2PhD program and has guest lectured at Nazareth University and RIT. She is currently the GRA for the REU Site in Computational Sensing for Human-centered AI at RIT. Upon graduation, she is interested in pursuing an academic career.

Grant Bosworth - AWARE-AI

Grant Bosworth is a PhD student in the Department of Electrical and Computer Engineering in the Kate Gleason College of Engineering. His research focuses on system-level design and integration of robots in manufacturing environments and embedded system design. Grant works with Dr. Sunwoong Kim as his primary advisor, and Dr. Ferat Sahin as his mentor in the AWARE-AI program in the AI hardware research track, working in the Multi-Agent Bio-Robotics Lab (MaBL). His current work focuses on proximity sensing using stereo depth estimation for collaborative robotics. Grant has completed an internship with Oculi in downtown Rochester, attended several conferences and symposia including the Asilomar Conference on Signals, Systems, and Computers, and the NSF AI Spring School where he successfully earned the 2026 MATRIX AI Scholar: Neuro-Inspired AI for the Edge credential, NRT+ summits at Cleveland State University and University of Wisconsin-Madison. Grant participates in the AWARE-AI Trainee Council, coordinating activities such as field trips and research talks for AWARE-AI participants. He was recently awarded funding through the NY SMART I-Corridor Tech Hub NY THRIVE program.

Faculty Spotlights

Richard Lange

Richard Lange is an Assistant Professor in Computer Science at RIT, where he joined in 2023. He is also affiliated with the Cognitive Science PhD program, the Center for Cognitive Science, and the University of Rochester's Center for Visual Science. He leads the Best Of NeuroScience and AI (BONSAI) Lab, where he and his students work to find a shared and mathematically principled understanding of how both biological and artificial neural networks function.

Current research in the BONSAI Lab focuses on designing more robust methods for representing visual and other sensory data in neural networks by designing new architectures and deriving training methods inspired by work in cognitive science and neuroscience. This research is supported by the NSF. At the same time, the lab is working on improving methods for quantifying similarities and differences between machine learning models and brains. Ultimately, this research serves both the goal of engineering more capable, robust, and brain-like AI systems as well as reverse-engineering how the human brain works.

Prior to joining RIT, Dr. Lange graduated from Dartmouth College in 2013, where he majored in Computer Science and Engineering. He earned his PhD in Brain and Cognitive Sciences and Computer Science from the University of Rochester in 2020, where his research centered on testing Bayesian theories of visual perception in the primate brain. He held a postdoctoral research position at the University of Pennsylvania from 2020 to 2023, where he pivoted from a focus on neuroscience to a focus on machine learning.

Outside of work, Dr. Lange can be found tinkering in the makerspace, gaming online or tabletop, or out on the paddle tennis court or disc golf course.

Pengfei Li

Pengfei Li joined the faculty of the Rochester Institute of Technology in 2025, where he serves as an Assistant Professor in the School of Information. Before joining RIT, he earned his PhD in Computer Science from the University of California, Riverside, advised by Prof. Shaolei Ren. He also received an M.S.E. in Robotics from Johns Hopkins University and a B.E. in Electrical Engineering from Zhejiang University. During his doctoral studies, he completed a summer internship at Nokia Bell Labs, where he worked on digital twins for autonomous warehouse operations.

Pengfei Li’s research focuses on building responsible machine learning systems for real-world decision-making. His work spans algorithm design and computer system applications. A core theme of his research is to combine the predictive power of machine learning with the reliability of classical online algorithms. He studies how ML predictions can be safely integrated into sequential decision-making systems. A key goal is to preserve provable guarantees for robustness, safety, and fairness. This is especially important when predictions become unreliable due to distribution shifts, delayed feedback, or adversarial inputs. His work also applies these ideas to sustainable and equitable AI systems, examining the energy, water, and resource demands of large-scale AI deployment and designing algorithmic tools to mitigate their environmental and social impacts.

At RIT, he plans to advance research on trustworthy and socially responsible AI systems. His future research will focus on reliable generative AI, decision-focused learning, and learning-augmented algorithms for resource-efficient computing infrastructures. Through this work, he aims to build AI systems that can support complex real-world decisions while remaining robust, interpretable, resource-efficient, and aligned with societal needs.

News

2026 Winter Symposium

Presenter speaks in front of a large screen displaying AI assistive technology concepts, including a virtual assistant graphic, a person using smart glasses, and text about adaptive assistance through AI sensing and display technologies

Photo: Keynote speaker Dr. Yuhang Zhao from the University of Wisconsin–Madison presented during the first of four days of the 2026 AWARE-AI Winter Symposium.

In January 2026, we hosted our four-day AWARE-AI Winter Symposium. This annual event represented a conference-level undertaking coordinated by Dr. Reynold Bailey with support from AWARE-AI staff member Angie Armstrong and the entire AWARE-AI team.

The symposium opened with sessions on financial literacy for graduate students, mentorship, outreach, and effective mentoring of undergraduate researchers. We were also delighted to welcome back AWARE-AI alumni Dr. Saurav Singh (PhD/KGCOE; now at Microsoft) and Dr. Emily Kuang (PhD/GCCIS; now at York University), who joined us virtually to reflect on their graduate experiences and share insights on the transition from graduate school to research careers.

The symposium featured two distinguished keynote speakers. Dr. Yuhang Zhao from the University of Wisconsin–Madison delivered an engaging presentation on context-aware systems that empower people with disabilities, demonstrating how advances in AI and sensing technologies can improve accessibility and independence. Later in the week, Dr. Tiago Falk from the University of Quebec presented Signal Processing and Applied AI: Making Human-Machine Systems More Generalizable, Secure, and Sustainable for Real-World Deployment, highlighting emerging approaches for developing AI systems that are robust, trustworthy, and effective in real-world settings. Attendees also benefited from tutorials on social robotics and mixed-integer linear programming, presented by Dr. Jamison Heard and Dr. Bing Yan, respectively.

A central focus of the symposium was showcasing the breadth and impact of research conducted by AWARE-AI trainees. Graduate students presented their work across all research tracks, with topics including multi-agent reinforcement learning, human-robot interaction, robotic safety, and conversational AI to support international students. These presentations sparked lively discussions and provided trainees with valuable feedback from faculty and peers.

Following reflections from graduate students who participated in the AI-PROWIL international research experience in Sweden, the final day of the symposium was led by the AWARE-AI Trainee Council. The council organized invited talks on AI for environmental sensor networks and statistical reasoning for hybrid systems, as well as an educational field trip that extended trainees' learning beyond the classroom while providing an informal setting to strengthen professional relationships and build community.

NRT+ Summit at University of Wisconsin-Madison

The NRT+ Summit, held March 23-25, 2026, at the University of Wisconsin–Madison, brought together faculty, trainees, researchers, and industry professionals for three days of research exchange, professional development, networking, and collaborative project development. The event strengthened connections across institutions while fostering new interdisciplinary collaborations.

The program featured two keynote talks: James Pikul presented From Muscles to Metabolism: Rethinking Energy, Actuation, and Intelligence in Robots, while Bilge Mutlu shared insights on Designing for Integration: Bringing Embodied AI into the Real World. A part of the NRT+ Summit was co-located with UWM’s INTEGRATE Symposium, which featured an additional keynote on drone technologies for agricultural research, in addition to research lightning talks, trainee posters, and industry panels on robotics applications and careers with representatives from Johnson & Johnson, Teradyne Robotics, NVIDIA, Amazon Robotics, and Intrinsic.

A room full of people sit at tables watching two overhead screens during a presentation.

Photo: Bilge Mutlu (WISC) presents his research talk, "Designing the Integration: Bringing Embodied AI into the Real World" during the NRT+ Summit hosted by UW-Madison.

A highlight of the summit was a three-part proposal mini-workshop, where trainees formed interdisciplinary cross-institutional teams, developed research ideas, and presented their proposals during a trainee competition. The workshop provided trainees with valuable experience in proposal development, team science, and research communication while fostering connections across institutions and research areas. In parallel, NRT+ faculty participated in a separate collaborative proposal development activity, which has led to continued work on two interdisciplinary research proposals.

Experiential learning was another important element of the three-day program. Participants toured the UW–Madison Dairy Cattle Center, offering a view of an application environment in which emerging technologies may intersect with agricultural research and practice. On the final day, participants also toured engineering and computer science research laboratories at UW-Madison, gaining further exposure to the university’s research environment and facilities. The overall event successfully combined technical exchange, collaboration, career exploration, and networking while creating new opportunities for interdisciplinary research.

Three people stand on a in front of a projector screen next to a podium, smiling. The person in the center is holding an award certificate.

Photo: Team Project Proposal Competition 1st place team. From left to right: Rodney Sanchez (RIT), Erin Clark (CSU), and Austin LaHue (CU). [not pictured, team member Jack Zupfer (UW-M)].

Four people stand on a in front of a projector screen next to a podium, smiling. One person on the left looks towards the projector screen while holding an award certificate.

Photo: Team Project Proposal Competition, 2nd place team from left to right: Jack Hobbs (CU), Chirayu Salgarkar (RIT), Avery Gump (UW-M), and Luci Duncan (CSU).

Three people stand in front of tiered concrete and grass terrace. A clock tower and mountain rise in the background.

Photo: Dr. Cecilia Alm (AWARE-AI director), Cedric Bone (AWARE-AI trainee), and Angie Armstrong (project coordinator) outside the CoorsTek Center Atrium, Colorado School of Mines, Boulder, CO.

NRT Annual Conference at Colorado School of Mines

Concurrent to the NRT+ summit in Wisconsin, AWARE-AI director Dr. Cecilia Alm, PhD student trainee Cedric Bone, and project coordinator Angie Armstrong traveled to Colorado School of Mines in Boulder for the NRT Annual Meeting. Trainee Cedric Bone participated in sessions for trainees and also presented a poster about his research in the AI software research track. Dr. Alm presented on Outcomes from the Rochester-Dublin Mobility Program during a session dedicated to Fostering International Research Experiences, and co-presented a poster on the AWARE-AI program with PC Angie Armstrong. In addition, the three AWARE-AI team members also attended breakout sessions for trainees, project coordinators, and PIs, respectively.

Seven people stand in front of tiered concrete and grass terrace. A clock tower and mountain rise in the background.

Photo: The Universal AI team from GU and RIT represented at the NRT Annual Conference - Joe Merino (GU, trainee), Jonah Winninghoff (GU, evaluator), Cedric Bone (RIT, trainee), Raja Kushalnagar (GU, PI), Charmaine Mendonsa (GU, PC), Cecilia Alm (RIT lead and Co-PI), and Angelique Armstrong (RIT, PC) outside the CoorsTek Center Atrium, Colorado School of Mines, Boulder, CO.

The AWARE-AI team was also fortunate to spend time with Universal AI partners from Gallaudet University; PI Dr. Raja Kushalnagar, project coordinator Charmaine Mendonsa, evaluator Jonah Winninghoff, and PhD student trainee Joe Merino. This provided an opportunity for the Universal AI team to connect and to meet with Joe in person prior to him traveling to RIT for his summer lab rotation.

The event provided opportunities to network, learn, and share experiences with other NSF research training programs at US universities. It was also an opportunity for initiating potential future partnerships and strengthening ongoing collaborations. Reflecting on his experience, Cedric noted that “It was a well run conference that connected grad students across disciplines, opened doors to potential collaborations, and showed us the shared skills and funding realities behind research in many different fields.”

Imagine RIT 2026

Visitors gather around a yellow quadruped Spot robot outside another robotics demonstration in a campus innovation space.

Photo: Dr. Ferat Sahin (AWARE-AI hardware research track lead) and Robot Dynamics’ Spot Robot interact with visitors during Imagine RIT.

The Imagine RIT: Creativity and Innovation Festival is an annual event enabling wide-reaching community outreach and engagement. AWARE-AI once again participated in this event, showcasing the impactful work and accomplishments of its trainees and researchers over the previous year. A highlight of the event was the strong presence of robotics, with attendees engaging with a variety of interactive demonstrations - from the Clearpath Jackal robot giving stickers to children to the Booster K1 (Mabel) robot attracting attention in an RIT tiger-themed outfit.

Clearpath Jackal mobile robot with a Kinova robotic arm displayed at a Universal AI exhibit table, featuring information about AI, robotics, and technology research at an RIT technology showcase.

Photo: AWARE-AI PhD trainees Calvin Nau and Cedric Bone interact with visitors using a robotic arm during Imagine RIT.

Visitors interact with a small humanoid robot dressed in a tiger costume at an RIT artificial intelligence exhibit featuring robotics and hands-on technology demonstrations

Photo: The robot Mabel greets visitors to the AWARE-AI exhibit space at Imagine RIT.

Two people interact with a technology demonstration in a lab, using hexagonal tiles and computer vision software displayed on a large screen.

Photo: Chirayu Salgarkar (AWARE-AI trainee) guides an Imagine RIT visitor interacting with his exhibit.

AWARE-AI Celebrates 2026 Graduates

AWARE-AI trainees, faculty, and staff gathered in May to celebrate the past year and recognize the graduating students completing their AWARE-AI traineeship, in addition to their PhD or MS degree programs. Recognized trainees included Bea Pulido, Connor Liu, Anisa Callis, and Farhan Hyder. We are thankful that alumni remain connected to the AWARE-AI community in various ways, including as presenters at the AWARE-AI Winter Symposium, or as part of the AWARE-AI research community and network.

A group of smiling graduate students and faculty pose for a group photo in front of a projection screen. The group is flanked on either side by two floor-to-ceiling glass doors.

Photo: AWARE-AI trainees and faculty gather for the 2026 End of Year Celebration. Back Row: Dr. Esa Rantanen (cognitive models for AI research track lead), trainees Connor Liu, Chirayu Salgarkar, Stephanie Patterson, Muhammad Raees, Grant Bosworth, Dr. Reynold Bailey (AI software research track lead), Rajesh Titung, Parth Kapur, Cedric Bone, Dr. Jamison Heard (HCI for AI research track lead), and Dr. Garreth Tigwell (HCI for AI co-lead). Front Row: Trainees Emily Rooney, Sophia Caruana, Gregory Ngeru, Mobina Ghorbaninejad, Anisa Callis, Dr. Cecilia Alm (AWARE-AI Director), Dr. Bing Yan (AI hardware research track co-lead), and Dr. Nasibeh Azadeh Fard. [Not pictured: Ferat Sahin (AI hardware research lead). Behind the camera: Angie Armstrong (project coordinator).]

Spotlight on Research Track: Cognitive Models for AI

Cognitive Work Analysis (CWA) is an inherently holistic analytical framework for study of the constraints and goals that shape information behavior in the workplace that simultaneously examines the environmental, organizational, and social activities, as well as individual dimensions. CWA consists of 6 distinct stages, each with a specific process, which yields a corresponding output, or product. Each output then serves as an input to the next process in a subsequent stage. Stages 3, Cognitive Transformation Analysis, 4, Cognitive Strategies Analysis, and 5, Cognitive Processing Analysis, focus on the reasons that a worker may select one strategy in preference to another or may transition between strategies during execution of a cognitive process, and identifies the Skills, Rules, or Knowledge (SRK) modes of cognition.

The research undertaken last year by the cognitive models for AI research track focused on automating much of the data collection and analysis involved in CWA. Track members designed an online (Qualtrics) survey for collection of data for the decision ladder (DL) analysis in stages 3-5 of CWA. The survey questions pertained to the nodes in the DL model and were also provided with branches for heuristic decision-making, skipping further processing in the left side of the ladder. The team also built an automated classifier that grouped survey responses into three decision categories according to the SRK framework.

The research team had created an experimental data analysis task, where participants were asked a question about a given dataset and tasked with writing Python code to perform the necessary analysis to answer the question. They could choose from three levels of difficulty for analysis and consult an AI copilot at any time when performing the task. The purpose of this experiment was to study decisions about when and how to use the AI assistance. About equal number of participants were classified as Skill-based and Rule-based and only one as Knowledge-based. Most participants either reported immediate procedural readiness or moved from observations toward a procedural task without substantial evidence of full knowledge-grounded deliberation. Participants most often described a compressed decision process: they reported what triggered the decision and how they acted, but usually did not articulate full option generation or goal comparison. The results validate the method for automated data collection and analysis for CWA as well as provide insights into the decision patterns in the use of agentic AI in problem-solving tasks, and will soon be submitted for publication in a prominent journal.

A group of graduate students seated at a table converse with another student standing with them and holding a device with dangling wires. Another group of students are sitting in group in the background

Photo: Student participants in the AWARE-AI Spring 2026 hackathon with faculty organizers Ferat Sahin, Jamison Heard, and Bing Yan.

Explore AWARE-AI at RIT