Newsletter December 2022

By the numbers:

4 representatives in the newly launched Trainee Council
11 research posters presented at the AI@RIT Summit
2 teams (10 trainees) in the BR41N.IO Hackathon
18 students in the new Human Factors in AI course

AWARE-AI at the NSF NRT annual meeting (from left to right): Chelsea BaileyShea, external evaluator; Arianna Giguere, trainee; Leslie Weber, project coordinator; Cecilia Alm, director.

Photo: AWARE-AI at the NSF NRT annual meeting (from left to right): Chelsea BaileyShea, external evaluator; Arianna Giguere, trainee; Leslie Weber, project coordinator; Cecilia Alm, director.

Message from the Director

The AWARE-AI program is now in the midst of its first full cohort year, and I am delighted to provide an update about recent AWARE-AI activities. In addition to activities piloted last spring, the program has expanded its reach with additional offerings. For example, the program held a new multiday bootcamp onboarding event in August, launched the first of its annual seed grant proposal competitions, and hosted two visits by Air Force Research Lab divisions. AWARE-AI trainees and faculty also prominently participated in the October AI@RIT Summit on campus.

In addition, AWARE-AI was represented at the 2022 NSF NRT annual meeting at Virginia Tech by trainee and Ph.D. student Arianna Giguere, project coordinator Leslie Weber, evaluator Chelsea BaileyShea, and me. Arianna participated in sessions for trainees and she also presented a poster about her project in the human-sensing AI software research track. Reflecting on her experience, Arianna noted that "the NSF NRT annual meeting gave me the opportunity to interact with other researchers across the country who are equally as interested in advancing scientific knowledge and impacting society for the better. I left the conference with new connections that could turn into future collaborations, and presenting my research to others helped increase my excitement about my work back in the lab." On behalf of the AWARE-AI faculty team, I also presented a poster about the AWARE-AI program to the NRT community and served as a panelist at the meeting. We brought back valuable learning experiences for the rest of the team, and forged new connections with other training programs at US universities and in Ireland. We are exploring new opportunities with these peer programs.

Our team is now preparing for next semester as well as the next academic year. The AWARE-AI program is already open for applications for traineeships for the coming 2023-2024 academic years. We welcome students from 15 PhD and Master’s programs at RIT to submit applications, and there are benefits and incentives for all to apply. We encourage interested students to attend our in-person open house on February 1, 2023, and to contact us at awareainrt@rit.edu with information requests. Applicants should submit their application materials, through the program website, before the deadline on March 1, 2023.

We are excited about AWARE-AI’s winter retreat that will take place January 17-20, with a schedule that spans talks by distinguished keynote speakers, technical sessions, career-advancement professional development, competency development centered on diversity and inclusion, dissemination of trainees’ research in AWARE-AI’s four research tracks, and opportunities for networking and interaction. The team is also working toward expanding its partnership programs that enable trainee internship experiences and visits to minority-serving institutions. We welcome new partners to join us!

On behalf of AWARE-AI trainees, faculty, and staff, thank you for being involved or supporting the success of this program. We look forward to comments and suggestions for the team. You can reach us by emailing awareainrt@rit.edu, stopping by GOL-2279, or calling 585-475-2372.

Happy winter holidays from AWARE-AI,

-Cissi

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Select Achievements

Trainee Arianna Giguere presented on her research track project Multimodal Modeling of Driving Behavior in the Presence of Distraction at the NSF NRT Annual Meeting 2022 at Virginia Tech.

Photo: Trainee Arianna Giguere presented on her research track project Multimodal Modeling of Driving Behavior in the Presence of Distraction at the NSF NRT Annual Meeting 2022 at Virginia Tech.

AWARE-AI members presented 11 research posters at the AI@RIT Summit in October. In addition, Dr. Alm delivered a keynote on Humans in Artificial Intelligence: Human-centered AI and Preparing the AI Workforce.
Dr. Kristen Shinohara served as Technical Program Co-chair for ASSETS 2022 and her research track colleagues Dr. Garreth Tigwell and Dr. Roshan Peiris also participated in the conference's organizing committee.
AWARE-AI launched a Trainee Council that coordinates trainee-organized events and meets monthly with the Executive Committee. The inaugural members include PhD students Karthik Subramanian, Emily Kuang, Justin Namba, and Arianna Giguere
Trainee Emily Kuang received an AWARE-AI Trainee Seed Funding Grant for her research on Exploring the Effectiveness of Proactive Conversational Assistants for Human-AI Collaborative Usability Analysis. Congratulations!

Trainee Spotlights

Justin Namba

Justin Namba is a PhD student in Computing and Information Sciences and trainee in the research track focused on human-sensing AI hardware. He is a 2019 RIT alumnus (BS in Computing and Information Technologies with a concentration in databases). Justin’s doctoral research focuses on non-relational data integration and the next challenges to be addressed in the area of JSON schema discovery. In the AWARE-AI program, he can apply his database skills and contribute to developing AI systems trained on data that are more representative of the diversity in society and reduce system bias. His AWARE-AI research project in the human-sensing AI hardware research track, guided by Dr. Ferat Sahin and affiliated research track faculty, centers on human-robot collaboration. The project aims to apply continual learning algorithms to improve real-time security and comfort of humans who are working in proximity to robots. Justin is excited about collaborating with students from other disciplines and applying his database and analytic skills in the collection and analysis of multimodal human sensing data. In the future, Justin hopes to create programs that promote the learning of artificial intelligence and data science in schools, particularly in Cameroon.

Margaret Gray

Margaret Gray is an MS student in Data Science and trainee in the research track focused on cognitive models for AI. Maggie earned her Bachelor's degree at RIT in the School of Individualized Study focusing on biology, computer science, and language science. As part of exploring different fields during her undergraduate studies, she had the opportunity to attend classes that introduced her to the concepts of artificial intelligence. Through these experiences, AI, which had previously seemed so far out of her realm of possibility, became much more real and tangible, and she was intrigued and wanted to learn more. Maggie returned to RIT again for her Master’s, and was encouraged to apply to the AWARE-AI program. She was selected for the program and is conducting research with two professors, Drs. Esa Rantanen and Jamison Heard. Maggie reports having had the opportunity to learn new skills and delve into new fields that she had not previously explored much (robotics and engineering psychology). She notes that the structure of the AWARE-AI program allows her freedom and support to conduct research and explore her interests in AI, while honing her skills as a responsible researcher. Maggie is looking forward to what her next few years with the program will bring!

Faculty Spotlights

Jamison Heard, Department of Electrical and Microelectronics Engineering

Dr. Jamison Heard is a faculty member from the Department of Electrical and Mictroelectronics Engineering. He started at RIT in the Fall of 2019 as an assistant professor of electrical engineering and co-leads the cognitive models for AI research track in the AWARE-AI program. Outside of this program, he advises the student chapter of IEEE, teaches AI-focused courses, and supports professional research conferences through program and organizing committees.

Dr. Heard founded the Adaptive Human-Robot Teaming Lab (AHRT Lab), which investigates adaptable and scalable solutions to enable natural human-agent and human-robot teaming. This is accomplished by bridging human factors knowledge with advanced artificial intelligence algorithms to drive an agent’s decision making process. Current research topics include human-aware reinforcement learning, enabling agents to understand unknown spaces and new skills, understanding human-robot team dynamics with deaf and hard of hearing individuals, and developing new data fusion modality methods for deep-learning architectures.

Kristen Shinohara, School of Information

Dr. Kristen Shinohara, assistant professor in the School of Information at the Rochester Institute of Technology, is a faculty member, Co-PI, and Research Track Lead for HCI in AI in the AWARE-AI program. Her NSF-funded research projects focus on how to empower disabled graduate students and designers, and how to improve accessibility practice in the tech industry and in computing education. Her work has received Best Paper and Honorable Mention awards from the CHI Conference in Human Factors in Computing and has appeared as the cover story in the Communications of the ACM.

Dr. Shinohara is also the co-director of the Center for Accessibility and Inclusion Research (CAIR) Lab at RIT. Her research is at the intersection of human-computer interaction, accessibility, and design, with a focus on accessible design, research, and computing education. She developed the Design for Social Accessibility (DSA) perspective and method cards, which support how designers engage with disabled user needs and preferences, particularly for social situations. She is the recipient of a 2022 Google Scholar Award to improve user-centered design methods for deaf and hard of hearing designers. Kristen received her PhD in Information Science from the University of Washington in 2017.

News

AWARE-AI August 2022 Onboarding Bootcamp

The AWARE-AI onboarding bootcamp’s virtual plenary speaker Sidney K. D’Mello, PI for the NSF National AI Institute for Student-Agent Teaming. Inset shows RIT assistant professor Alex Ororbia who delivered an in-person technical AI lecture.

Photo: The AWARE-AI onboarding bootcamp’s virtual plenary speaker Sidney K. D’Mello, PI for the NSF National AI Institute for Student-Agent Teaming, presented to and had discussions with trainees, faculty, and other attendees. Photo insert (top right): RIT assistant professor Alex Ororbia delivered an in-person technical AI lecture.

The AWARE-AI program hosted its first annual multiday onboarding bootcamp for the incoming NRT cohort in mid-August, 2022. The onboarding aimed to kick-start the AWARE-AI academic year and also allow the incoming trainee cohort to get to know each other and the AWARE-AI faculty before the fall semester started.

New AWARE-AI Project Coordinator

Leslie Weber joined the AWARE-AI team as project coordinator on September 1st. She is thrilled to be assisting a program focused on providing a wide variety of unique professional and experiential research opportunities to a diverse cohort of graduate student trainees. We welcome Leslie to the AWARE-AI team!

Spotlight on Research Track: Human-sensing AI Software

Photo: Collage of select activities in the human-sensing AI software research track which seeks to develop more human-like, robust multimodal AI systems. Some of the trainees involved include (top row, left to right): Kevin Barkevich, Rajesh Titung, Naveen Kudli Balaji, Michael Peechatt, and Viet Nguyen. Trainees have gained experience with multimodal data collection experiments, for example, (bottom row, left to right): using a custom-built driving simulator to study drivers' behavior when distracted, or construction tasks to study collaborative interactions and human emotional reactions.

The AWARE-AI program’s human-sensing AI software research track aims to develop AI systems and algorithms that process and respond to heterogeneous, heavily multimodal input as flexibly as humans. Humans can adapt during interaction by integrating various heterogeneous and temporally evolving sensory sources such as dialogue, voice inflection, facial expressions, head and body pose, eye movements, touch, biophysical cues, and other environmental information. In contrast, AI systems tend to be unimodal or incapable of similar dynamic flexibility in real-world interactions.

Fall 2022 Mentor Café

Photo: Dr. Renata Rezende Miranda talked with AWARE-AI trainees Justin Namba, Saurav Singh, and other participants.

Photo: Dr. Garreth Tigwell provided advice to trainees Arianna Giguere and Margaret Gray.

The fall mentor café was held in October in Gleason Hall. This was an informal gathering of NRT trainees and early career researchers, featuring junior faculty and postdoctoral scholars as mentors. During the event, trainees and researchers had a chance to chat about research, career trajectory, and navigating academic life in general. It also provided an opportunity for both trainees and researchers to expand their networks.

Four mentors met with five NRT trainees. In a round-robin fashion, participants took turns meeting with each other and asking for advice from mentors. Mentors who participated in support of the café included: Dr. Renata Rezende Miranda, Gosnell School of Life Sciences; Dr. Poornima Padmanabhan, Chemical Engineering; Dr. Garreth Tigwell, School of Information; and Dr. Alex Ororbia, Computer Science. Thank you to all participants!

AFRL visits to AWARE-AI

AFRL visitors: Drs. Hayduk, Wenndt, and Inkawich, and members of the AWARE-AI faculty team: Drs. Ororbia, Heard, Rantanen, Alm, and Yang.

Photo: AFRL visitors: Drs. Hayduk, Wenndt, and Inkawich, and members of the AWARE-AI faculty team: Drs. Ororbia, Heard, Rantanen, Alm, and Yan.

AWARE-AI hosted two visits from the Air Force Research Labs (AFRL) this fall. On October 21 Drs. Michael Hayduk, Deputy Director at AFRL Information Directorate in Rome, NY; Stanley Wenndt, Information Institute Lead, Intern Lead, AFOSR Liaison in AFRL/RIBB; and Nathan Inkawhich in AFRL/RIBB, spent approximately half a day on campus, giving presentations about the AFRL/RIBB organization and current research and hearing from RIT faculty and students about the research activities within the AWARE-AI program. We also showed our visitors several AWARE-AI-associated labs where our trainees demonstrated their ongoing research.

In addition, on November 18 we hosted Dr. Dan Zelik, the Assistant Chief Scientist of the 711th Human Performance Wing (711 HPW/CL) at Wright-Patterson AFB in Ohio. Dan met with Drs. Alm, Shinohara, and Rantanen, and had a tour of labs on campus, meeting with several AWARE-AI trainees who shared information about their ongoing research projects.

Examples of Fall 2022 Events

Photo: Dr. Scott Franklin, professor of physics and director of CASTLE, offered a workshop on leadership and collaborative research.

NRT trainees have attended plenary talks, research talks, and advanced PhD student talks in the CHAI seminar series, organized by Sue Brightman, with CHAI co-associate directors Alm and Yu. The seminar talks have a designated playlist in the AWARE-AI Video Archive. The fall series also included presentations by two AWARE-AI trainees: Matthew Seita and Jhair Gallardo.
Dr. Ammina Kothari, University of Rhode Island, facilitated an interactive workshop on Communicating with Broader Audiences - Policy and Decision-makers, Media, and Public. Trainees gained insights into how to make engaging public research presentations and communicate effectively and clearly to a wide variety of audiences.
PSYC 719 Human Factors in Artificial Intelligence is a brand-new course designed for the AWARE-AI program. Offered for the first time by Dr. Rantanen, the course was organized around three main components: (1) a recent textbook about human-centered AI, (2) human factors content and principles, provided by the instructor in written materials and short lectures, and most importantly (3) students’ individual learning experiences, integrating their own background, knowledge, and interests in AI with content learned from class sessions and course materials.

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