Oana Ignat, Towards Language-Vision Models for Positive Societal Impact

When: Monday 2/19 from 1:00 to 2:00 PM Where: Tyler 055 Abstract: Solving complex real-world problems often requires AI models that can process information from multiple modalities, such as language and vision, which can align with the needs of people from diverse backgrounds. An effective AI model will not only learn how to interact with […]

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Kaleel Mahmood, On the Robustness of Vision Transformers to Adversarial Examples

When: Friday 2/16 from 10:00 to 11:00 AM Where: Ranger 202 Abstract: Machine learning has become ubiquitous, being deployed in a range for domains like self driving cars, medical imaging and face recognition. With this increased use of machine learning an important question arises, how secure are these systems? In this presentation we dive into […]

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Taslima Akter, Designing Privacy Enhancing Technology for Blind and Low-Vision (BLV) People

WHen: Tuesday 2/13 from 1:00 to 2:00 PM. Where: Quinn 214 Abstract: Advancements in computer vision and machine learning have empowered Blind and Low-Vision (BLV) individuals through camera-based assistive applications. These systems, capable of recognizing objects, identifying colors, and reading text, provide independence to BLV users. However, the reliance on camera-based assistive systems introduces privacy […]

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Gianluca Brero (Brown University), Stackelberg POMDP: A Reinforcement Learning Approach for Economic Design

When: Friday, Feb 2nd, from 2:00 PM to 3:00 PM Where: ENGR 045 Abstract: We introduce a reinforcement learning framework for economic platform design where the interaction between the platform designer and the participants is modeled as a Stackelberg game. In this game, the designer (leader) sets up the rules for the platform, while the […]

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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 […]

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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, […]

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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 […]

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ML Tlachac, Digital Mental Health Screening with Text Logs

When: Friday, September 29th, from 4:00 PM to 5:00 PM Where: ENGR 040 Who: ML Tlachac, Assistant Professor of Data Science at Bryant University Abstract: In this talk, ML Tlachac will provide an overview of digital mental health screening research with a focus on digital phenotyping data. The presentation will include insights into research involving […]

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Basheer Qolomany, “The Role of Artificial Intelligence and Machine Learning in Complex Systems”

When: Friday, April 28, 2:00 PM Where: CBLS 100 Who: Basheer Qolomany, University of Nebraska at Kearney The Role of Artificial Intelligence and Machine Learning in Complex Systems Abstract: Current methods for diagnosing PAD require specialized vascular laboratory tests and do not allow natural environment detection, monitoring, or management of chronic PAD disease. The research […]

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