Title
Topic
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‘”Always Nice and Confident, Sometimes Wrong”: Developer’s Experiences Engaging Generative AI Chatbots Versus Human-Powered Q&A Platforms’
“Software engineers have historically relied on human-powered Q&A platforms, like Stack Overflow (SO), as coding aids. With the rise of generative AI, developers have adopted AI chatbots, such as ChatGPT, in their software development process. Recognizing the potential parallels between human-powered Q&A platforms and AI-powered question-based chatbots, we investigate and compare how developers integrate this assistance into their real-world coding experiences by conducting thematic analysis of Reddit posts. Through a comparative study of SO and ChatGPT, we identified each platform’s strengths, use cases, and barriers.” Find the paper and full list of authors at ArXiv.
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‘Semantic Encapsulation Using Linking Types’
“Interoperability pervades nearly all mainstream language implementations, as most systems leverage subcomponents written in different languages. And yet, such linking can expose a language to foreign behaviors that are internally inexpressible, which poses a serious threat to safety invariants and programmer reasoning. … In this paper, we outline an approach that encapsulates foreign code in a sound way — i.e., without disturbing the invariants promised by types of the core language.” Find the paper and full list of authors in the Proceedings of the 8th ACM SIGPLAN International Workshop on Type-Driven Development.
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Is air pollution putting you at risk of dementia? This researcher wants to find out
Clinical professor and associate dean Trenton Honda is part of a multi-university study comparing incidence of metal airborne pollutants in the “olfactory bulb” with other areas of the brain to identify potential risk factors for Alzheimer’s and other dementias.
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Patent awarded for subharmonic sensor technology
“Electrical and computer engineering associate professor Cristian Casella, professor Matteo Rinaldi and postdoctoral research associate Hussein Hussein were awarded a patent for ‘Subharmonic Tags for Remote Continuous and Threshold Sensing.'”
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‘Unicorn, Hare or Tortoise? Using Machine Learning To Predict Working Memory Training Performance’
“People differ considerably in the extent to which they benefit from working memory (WM) training. … In the current study, 568 undergraduates completed one of several N-back intervention variants over the course of two weeks. … We applied machine-learning algorithms to train a binary tree model to predict individuals’ training patterns relying on several individual difference variables that have been identified as relevant in previous literature. … We found that our classification model showed good predictive power in distinguishing between high performers and relatively lower performers.” Find the paper and full list of authors at the Journal of Cognition.
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Designing chips for AI-enabled spectrum perception
“Electrical and computer engineering assistant professor Francesco Restuccia — in collaboration with Arjuna Madanayake from Florida International University, Vishal Saxena from the University of Delaware and Jia Di from the University of Arkansas — was awarded a $2,000,000 NSF grant for ‘FuSe: Deep Learning and Signal Processing Using Silicon Photonics and Digital CMOS Circuits for Ultra-Wideband Spectrum Perception.'”
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Spinout company Fourier LLC to revolutionize thermal management
“After pioneering thermoforming technical ceramic matrix composites last year, mechanical and industrial engineering associate professor Randall Erb and mechanical engineering alum Jason Hoffman-Bice, PhD’22, have created a spinout company called Fourier LLC to commercialize their groundbreaking innovation in thermal management.”
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Reshaping spectrum sharing above 100 GHz
“Electrical and computer engineering professors Josep Jornet (PI), Tommaso Melodia, principal research scientists Michele Polese, Michael Marcus and associate research scientist Vitaly Petrov, in collaboration with Steven Reising from Colorado State University, were awarded a $750,000 NSF grant for ‘DASS: Dynamically Adjustable Spectrum Sharing between Ground Communication Networks and Earth Exploration Satellite Systems Above 100 GHz.'”
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‘Assessing the Potential for the Surface Water and Ocean Topography (SWOT) Mission for Constituent Flux Estimations’
“The recently launched Surface Water and Ocean Topography (SWOT) satellite will simultaneously measure river surface water widths, elevations, and slopes. These novel observations combined with assumptions for unobserved bathymetry and roughness enable the derivation of river discharge. … SWOT has an irregular flyover frequency, ranging from roughly 1 to 10 times per 21 days. Here, we present how best to use SWOT data when it becomes live, including consideration of how best to accommodate or utilize the irregular flyover frequency of SWOT as it intersects with river reaches.” Find the paper and full list of authors at Frontiers in Earth Science.
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‘Hierarchical Structure Formation by Crystal Growth-Front Instabilities During Ice Templating’
“Directional solidification of aqueous solutions and slurries in a temperature gradient is widely used to produce cellular materials through a phase separation of solutes or suspended particles between growing ice lamellae. While this process has analogies to the directional solidification of metallurgical alloys, it forms very different hierarchical structures. … We show that the flat side of lamellae forms because of slow faceted ice-crystal growth along the c-axis, while weakly anisotropic fast growth in other directions, including the basal plane, is responsible for the unilateral features.” Find the paper and full list of authors at PNAS.
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‘Electric Shock Causes a Fleeing-Like Persistent Behavioral Response in the Nematode Caenorhabditis Elegans’
“Behavioral persistency reflects internal brain states, which are the foundations of multiple brain functions. However, experimental paradigms enabling genetic analyses of behavioral persistency and its associated brain functions have been limited. Here, we report novel persistent behavioral responses caused by electric stimuli in the nematode Caenorhabditis elegans. When the animals on bacterial food are stimulated by alternating current, their movement speed suddenly increases 2- to 3-fold, persisting for more than 1 minute even after a 5-second stimulation.” Find the paper and full list of authors at Genetics.
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‘Considerations for Electrochemical Phosphorus Precipitation: A Figures of Merit Approach’
“Electrochemical phosphorus precipitation (EPP) from wastewater is a promising emerging technology for recovering valuable nutrients. While there are significant advantages of EPP compared to traditional phosphorus recovery, large gaps in reported performance exist between EPP methods and between EPP and industrial methods. Herein we discuss Figures of Merit (FOM) to normalize and report EPP performance at low-to-intermediate technology readiness levels (TRLs).” Find the paper and full list of authors in The Electrochemical Society Interface.
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‘Hospice Satisfaction Among Patients, Family and Caregivers: A Systematic Review of the Literature’
“Hospice care is an underused form of intervention at the end of life. … Methods: A PRISMA-guided review of the research on hospice care satisfaction and its correlates among patients, families and other caregivers. Included in the review is research published over the time period 2000-2023 identifying a hospice care satisfaction finding. … Key findings were: (a) higher levels of hospice care satisfaction among patients, families and other caregivers; and (b) correlates of hospice care satisfaction falling into the categories of communication, comfort and support.” Find the paper and full list of authors in the American Journal of Hospice and…
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‘ShadowNet: A Secure and Efficient On-Device Model Inference System for Convolutional Neural Networks’
“With the increased usage of AI accelerators on mobile and edge devices, on-device machine learning (ML) is gaining popularity. Thousands of proprietary ML models are being deployed today on billions of untrusted devices. This raises serious security concerns about model privacy. … In this paper, we present a novel on-device model inference system, ShadowNet. ShadowNet protects the model privacy with Trusted Execution Environment (TEE) while securely outsourcing the heavy linear layers of the model to the untrusted hardware accelerators.” Find the paper and full list of authors at the IEEE Symposium on Security and Privacy.
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‘Secure Multiparty Computation With Identifiable Abort From Vindicating Release’
“In the dishonest-majority setting, generic secure multiparty computation (MPC) protocols are fundamentally vulnerable to attacks in which malicious participants learn their outputs and then force the protocol to abort before outputs are delivered to the honest participants. … We present a novel approach for realizing functionalities with a weak form of input-revealing [identifiable abort], which is based on delicate and selective revealing of committed input values. We refer to this new approach as vindicating release.” Find the paper and full list of authors at Cryptology ePrint Archive.
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‘A Hybrid Partitioning Strategy for Backward Reachability of Neural Feedback Loops’
“As neural networks become more integrated into the systems that we depend on for transportation, medicine and security, it becomes increasingly important that we develop methods to analyze their behavior to ensure that they are safe to use within these contexts. The methods used in this paper seek to certify safety for closed-loop systems with neural network controllers, i.e., neural feedback loops, using backward reachability analysis.” Find the paper and full list of authors in the American Control Conference proceedings.
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‘RAMP: A Risk-Aware Mapping and Planning Pipeline for Fast Off-Road Ground Robot Navigation’
“A key challenge in fast ground robot navigation in 3D terrain is balancing robot speed and safety. Recent work has shown that 2.5D maps (2D representations with additional 3D information) are ideal for real-time safe and fast planning. However, the prevalent approach of generating 2D occupancy grids through raytracing makes the generated map unsafe to plan in. … The RAMP pipeline proposed here solves these issues using new mapping and planning methods.” Find the paper and full list of authors at the IEEE International Conference on Robotics and Automation.
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‘Level Assembly as a Markov Decision Process’
“Many games feature a progression of levels that doesn’t adapt to the player. This can be problematic because some players may get stuck … while others may find it boring if the progression is too slow to get to more challenging levels. This can be addressed by building levels based on the player’s performance and preferences. In this work, we formulate the problem of generating levels for a player as a Markov Decision Process (MDP) and use adaptive dynamic programming (ADP) to solve the MDP before assembling a level.” Find the paper and full list of authors at ArXiv.
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‘Re-trainable Procedural Level Generation via Machine Learning (RT-PLGML) as Game Mechanic’
“We present re-trainable procedural level generation via machine learning (RT-PLGML), a game mechanic of providing in-game training examples for a PLGML system. We discuss opportunities and challenges, along with concept RT-PLGML games.” Find the paper and full list of authors at Proceedings of the 18th International Conference on the Foundations of Digital Games
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‘Solder: Retrofitting Legacy Code with Cross-Language Patches’
“Internet-of-things devices are widely deployed, and suffer from easy-to-exploit security issues. … Because patch deployments tend to be focused on server-side vulnerabilities, client software in large codebases such as Apache may remain largely unpatched, and hence, vulnerable. … In this paper, we address this issue of leaving latent vulnerabilities in legacy codebases. We propose Solder, a framework to patch or retrofit legacy C/C++ code by replacing any target function with a newly-implemented one in a safe language such as Rust.” Find the paper and full list of authors in the International Conference on Software Analysis, Evolution and Reengineering proceedings.
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‘On Regularity Lemma and Barriers in Streaming and Dynamic Matching’
“We present a new approach for finding matchings in dense graphs by building on Szemerédi’s celebrated Regularity Lemma. This allows us to obtain non-trivial albeit slight improvements over longstanding bounds for matchings in streaming and dynamic graphs.” Find the paper and full list of authors in the Proceedings of the 55th Annual ACM Symposium on Theory of Computing.
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‘Complex Network Effects on the Robustness of Graph Convolutional Networks’
“Vertex classification — the problem of identifying the class labels of nodes in a graph — has applicability in a wide variety of domains. Examples include classifying subject areas of papers in citation networks or roles of machines in a computer network. Vertex classification using graph convolutional networks is susceptible to targeted poisoning attacks, in which both graph structure and node attributes can be changed in an attempt to misclassify a target node. … This paper considers an alternative: we leverage network characteristics in the training data selection process to improve robustness of vertex classifiers.” Find the paper and list…
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‘PaniniQA: Enhancing Patient Education Through Interactive Question Answering’
“Patient portal allows discharged patients to access their personalized discharge instructions in electronic health records (EHRs). However, many patients have difficulty understanding or memorizing their discharge instructions. In this paper, we present PaniniQA, a patient-centric interactive question answering system designed to help patients understand their discharge instructions. PaniniQA first identifies important clinical content from patients’ discharge instructions and then formulates patient-specific educational questions.” Find the paper and full list of authors at ArXiv.
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‘SEIL: Simulation-Augmented Equivariant Imitation Learning’
“In robotic manipulation … traditional image-level data augmentation has shown the potential to improve sample efficiency in various machine learning tasks. However, image-level data augmentation is insufficient for an imitation learning agent to learn good manipulation policies in a reasonable amount of demonstrations. We propose Simulation-augmented Equivariant Imitation Learning (SEIL), a method that combines a novel data augmentation strategy of supplementing expert trajectories with simulated transitions and an equivariant model that exploits the O(2) symmetry in robotic manipulation.” Find the paper and full list of authors at the IEEE International Conference on Robotics and Automation proceedings.
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‘Leveraging Symmetries in Pick and Place’
“A recently proposed [robotic] pick and place framework known as Transporter Net captures some of these symmetries, but not all. This paper analytically studies the symmetries present in planar robotic pick and place and proposes a method of incorporating equivariant neural models into Transporter Net in a way that captures all symmetries. The new model, which we call Equivariant Transporter Net, is equivariant to both pick and place symmetries and can immediately generalize pick and place knowledge to different pick and place poses.” Find the paper and full list of authors at ArXiv.