Regular Events
Society for Women in Computing
SWIC offers regular meetings for women in technology to develop professional skills and build their expertise.
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A bi-weekly opportunity for majors, and those interested in technology topics, to network and collaborate.
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Seminars and Colloquia
- Women in AI Workshop - When: Wednesday, April 16, 4:30-6:00 pm Where: Ballentine 115 Our Computer Science IGT Scholars are presenting a Women in AI Workshop that is open to all who are interested. The workshop will include a panel of women who have worked in the field of Artificial Intelligence in a variety of capacities: Panel: Dawn Fitzgerald – […]
- Stephen Bach, Rigorously Benchmarking LLMs for Translating Text to Structured Planning Languages - When: Friday, 4/18/25 11:00 am; Where: Bliss 260 Abstract: Can large language models (LLMs) help with planning? And how should we even measure that ability? In this talk, I will present our work on Planetarium, a benchmark that evaluates LLMs’ ability to generate PDDL (Planning Domain Definition Language) code from natural language descriptions of planning […]
- Hang Hua, Advancing Generative AI for Multimodal Intelligence - When: Friday, 3/7 11 am – 12 pm; Where: Tyler Hall 055. Abstract: Generative AI is transforming how machines interact with and augment human capabilities. However, achieving artificial general intelligence (AGI) requires addressing significant challenges in retrained language models (PLM) and multimodal large language models (MLLMs), including the brittleness of language model fine-tuning, imbalanced vision-language […]
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News stories
- Women in AI Workshop - When: Wednesday, April 16, 4:30-6:00 pm Where: Ballentine 115 Our Computer Science IGT Scholars are presenting a Women in AI Workshop that is open to all who are interested. The workshop will include a panel of women who have worked in the field of Artificial Intelligence in a variety of capacities: Panel: Dawn Fitzgerald – […]
- Indrani Mandahl honored as Rhode Island Monthly Tech10 recipient - Congratulations to Associate Teaching Professor Indrani Mandahl as one of two members of the URI community recognized among Rhode Island Monthly’s 2024 Tech10 and Next Tech Generation Award recipients for their exceptional contributions to technology and education.
Two Computer Science students honored at URI Black Scholar awards - Computer science students Amoy Scott and Warith Balogun were honored Monday at the URI Black Scholar awards. Scott received the Sojourner Truth Award for Scholarly Persistence and Dedication, presented to a senior in recognition of success despite dire financial, physical and/or personal problems that would ordinarily impede progress, and Balogun received the Earl N. Smith, […]- Kelum Gajamannage, Low-rank data imputation using Hadamard deep autoencoders, with applications to fragmented trajectory reconstruction of collective motion - When: Friday, October 13 at 4:00 pm. Where: Fascitelli 040 Abstract: Data imputation is an essential preprocessing step in statistical learning that is to be performed before any technical analysis is conducted on partially observed data. Data originating from natural phenomena is low-rank due to diverse natural dependencies that a low-rank technique should primarily emphasize […]
- Antonios Argyriou, Passive Wireless Sensing: Implications on Privacy and Counter-Measures - When: Monday, October 30 at 1:00 pm. Where: Quinn 211. Who: Dr. Antonios Argyriou, Associate Professor, Department of Electrical and Computer Engineering, University of Thessaly, Greece. Abstract: Emitters of wireless signals are all around us 24/7. These wireless signals contain digital information that may be the target of different types of cyber security attacks. However, […]
- Ming-Hui Chen, A New Statistical Monitoring Approach Based on Linear Mixed-Effects Models: Application to Energy Usage Management on a Large University Campus - When: Friday, October 27th, from 4:00 PM to 5:00 PM Where: ENGR 040 Who: Professor Ming-Hui Chen, Department of Statistics, University of Connecticut Abstract: In this paper, we introduce a novel application of the linear mixed-effects model (LMM) repurposed for statistical monitoring. We develop an efficient EM algorithm to handle rapid estimation, especially in scenarios […]