Physical Sciences and Mathematics Commons^™

Dynamind: A Dynamic Learned Index For Update-Intensive Workloads, Jingxian Cheng, Yingfang Wang, Tianqing Zhu, Xu Yang, Ningning Cui, Jianxin Li

Research outputs 2022 to 2026

Learned indexes leverage machine learning models to approximate data distributions and predict key positions, offering better performance than traditional index structures such as B+Trees. As data in real-world applications evolve rapidly, the timely and efficient updating of learned indexes has become an increasingly important research problem, attracting growing attention in recent studies. However, under update-intensive workloads with frequent insertions and deletions, existing learned indexes cannot update the model in a timely manner. Moreover, they ignore the impact of deletions on model accuracy. These limitations lead to degraded prediction accuracy and increased query latency, undermining the core advantage of learned indexes. …

A Semantic Data Management Framework For Uncertainty Quantification In Synchrotron Diffraction Pattern Analysis, Ayorinde E. Olatunde, Ozan Dernek, Erika I. Barcelos, Roger H. French, Anirban Mondal

Student Scholarship

Advancements in technology have enabled scientists and engineers in the synchrotron science domain to generate high-dimensional data. To conduct a machine learning study on these data, an analyst undergoes multiple analytical stages, including dimensionality reduction, predictive modelling, and uncertainty quantification (UQ).

To ensure reproducibility in science, it is necessary to document the semantic relationships among the stages of the analysis to enable provenance, interoperability, and knowledge reuse. In this work, we present a Semantic Data Management (SDM) framework rooted in FAIR principles that provides ontologies for UQ workflows. We illustrate the application of UQ ontology in synchrotron diffraction pattern analyses …

Final Bpsou Unreclaimed Sites: Ur-46 Remedial Action Work Plan (Rawp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Clinical Utility Of An Fda-Authorized Artificial Intelligence Imaging Platform In Interstitial Lung Disease Diagnosis, Arjun Prakash Tambe, Ryan Boente, Gautam George, Fayez Kheir, Omid Tahamtani Omran, Kavitha Selvan

Division of Pulmonary, Allergy, and Critical Care Medicine Faculty Papers

Background/Objectives: The diagnosis of interstitial lung disease (ILD) is challenging and frequently delayed. Clinically accessible and minimally invasive diagnostic tools are needed to expedite the diagnosis of ILD while minimizing risk to patients. Fibresolve is an imaging artificial intelligence (AI) tool recently approved by the Food and Drug Administration (FDA) for use in ILD diagnosis and made available to clinicians. The objective of this study was to describe its utility in clinical practice. Methods: We conducted a prospective, observational study of patients across the United States (US) in whom Fibresolve was utilized during routine clinical practice between July 2024 and …

Climate-Driven Degradation And Lifecycle Reliability Of Building-Integrated Photovoltaic Systems: Integration Challenges And Deployment Pathways, Mohammad Nur-E-Alam, Mohammad Khairul Basher, Mohammad Tariqul Islam, Mongi Amami, Rajesh Haldhar, M. Khalid Hossain

Research outputs 2022 to 2026

Building-integrated photovoltaics (BIPV) are becoming a more popular source of renewable energy. It is an on-site renewable energy source within buildings but has limited growth due mainly to lifespan issues throughout the entire life cycle from manufacturing to design, installation, electrical integration, operation, and end of life. This paper reviews the climate-driven deterioration mechanisms of BIPV, including thermal cycling, moisture ingress, atmospheric pollutants, wind loads, etc. They relate these climate-driven deterioration mechanisms to BIPV performance deterioration, energy yield reductions, safety concerns related to energy loss, and long-term reliability of BIPV systems across all parts of the BIPV life cycle. Through …

Bayesian Variable Selection In High-Dimensional Ordinal Quantile Regression Models, Mai Dao, Md. Sakhawat Hossain, Zhuanzhuan Ma

School of Mathematical & Statistical Sciences Faculty Publications

Quantile regression (QR) provides a flexible statistical framework for modeling the entire conditional distribution of the response variable, making it useful for analysis in various fields. Despite its advantages, existing methods for QR often encounter numerical challenges in high-dimensional settings, especially for those with ordinal responses. In this paper, we use a latent-response framework to construct a Bayesian hierarchical model to conduct parameter estimation and variable selection for ordinal QR. Using the asymmetric Laplace working likelihood and the horseshoe prior for the regression coefficients, we obtain the posterior samples to be screened by the sequential two-means clustering process to identify …

Positive Curvature And Discrete Abelian Symmetry, Lee Kennard, Elahe Khalili Samani, Catherine Searle

Mathematics

By replacing the torus with an elementary abelian two-group, we generalize Grove and Searle’s maximal symmetry result and Wilking’s half-maximal symmetry result for positively curved manifolds with an isometric torus action. © The Author(s) 2026.

Crystal Structure Of New Polar Rare Earth Borates Na2.62Ln2.12(Bo3)3 (Ln = Pr, Nd, Sm) Containing Isolated Bo3 Groups, Alevtina A. Maksimova, Mark D. Smith, Hans Conrad Zur Loye

Faculty Publications

Three new rare earth borates, Na2.62Ln2.12(BO3)3 (Ln = Pr, Nd, Sm), were synthesized via a high-temperature solution reaction using a BaCO3–H3BO3–NaF flux and structurally characterized by single-crystal X-ray diffraction analysis. The compounds crystallize in the orthorhombic space group Amm2 with lattice parameters a = 5.0985(10) Å, b = 11.180(2) Å, c = 7.1483(14) Å, and a unit cell volume of 407.48(14) ų (Z = 2) for Na2.62Pr2.12(BO3)3, a = 5.0983(10) Å, b = 11.181(2) Å, c = 7.1491(14) Å, and a unit cell volume of 407.51(14) ų (Z = 2) for Na2.62Nd2.12(BO3)3, and a = 5.08630(10) Å, b …

A Stabilized Weighted Interior Penalty Method For Thermal Convection Model In Heterogeneous Porous Media, Yuanyuan Hou, Qianqian Ding, Xiaoming He, Yanping Lin

Mathematics and Statistics Faculty Research & Creative Works

In this article, we propose and analyze a stabilized weighted interior penalty method for solving the thermal convection problems in heterogeneous porous media. We first transform the thermal convection model into the pressure primal form with homogeneous Neumann boundary condition and develop a symmetric weighted interior penalty method to handle the discontinuous Darcy number and automatically adjust the penalty coefficient corresponding to the varying permeability. Then we recover the velocity by a stabilized method and incorporate it into the energy equation to obtain the temperature. The stability and convergence rates of the numerical solutions are rigorously proved and verified by …

Single Crystal Growth Of The Orthoborate Nabalu(Bo3)2 And Optical Investigation Of Eu3+ And Tb3+ Doped Nabalu(Bo3)2, Alevtina A. Maksimova, Mark D. Smith, Lakshani W. Masachchi, Hans Conrad Zur Loye

Faculty Publications

Sodium barium lutetium borate NaBaLu(BO₃)₂ crystals were synthesized using a high-temperature solution method. The crystal structure of this layered orthoborate is described and corresponds to that of an extensive orthoborates family, NaBaR(BO₃)₂ (R = Sc, Y, Yb, Tb – Lu). NaBaLu(BO₃)₂ was doped by Eu³⁺ and Tb³⁺ to explore its performance as a host material and to investigate the luminescent properties of the Eu³⁺ and Tb³⁺ doped materials. The emission spectra of the NaBaLu(BO₃)₂:Ln (Ln = Eu, Tb) crystals are presented. The most …

Graph Perturbation Analysis For Subgraph Counting, Hanhua Xiao, Yuchen Li, Kyriakos Mouratidis

PhD Student’s Publications Collection

Subgraph counting, which involves determining the frequency of a query graph within a data graph, has numerous applications such as query optimization, fraud detection, and evaluating the expressiveness of graph neural networks. Despite its importance, there has been no systematic study on the impact of adversarial graph perturbations on subgraph counts. In this work, we examine the kSub problem, which aims to identify k edge additions that maximize the count of a query graph. We prove that kSub is intractable due to its NP-hardness, even for constant approximation. To address this, we relax the problem into a top-k selection, termed …

The Role Of Local Winds And A Semi-Persistent Coastal Front On The Diurnal Heat Budget In An Upwelling Bay, April P. Thibodeau, Ryan K. Walter, Piero L.F. Mazzini, Thomas P. Connolly, Christopher A. Edwards, Ian C. Robbins

Physics

Coastal embayments in nearshore upwelling systems (“upwelling bays”) play a disproportionately large role in regional oceanography. In these systems, local diurnal wind forcing and thermal gradients associated with an upwelling shadow front that forms between warmer sheltered waters inside the bay and colder recently upwelled waters outside the bay strongly influence local temperature dynamics. Despite their importance to local ecosystems, there are no long-term studies that assess the heat budget inside upwelling bays. In this study, we analyzed approximately two years of water temperature throughout the water column using an autonomous profiler in a small upwelling bay in central California …

Summary Report: Second Conference On Attribution Science And Climate Law, Jessica A. Wentz

Sabin Center for Climate Change Law

The Sabin Center for Climate Change Law and the Columbia Climate School hosted the Second Conference on Attribution Science and Climate Law at Columbia University on June 10–11, 2026. This event brought together an interdisciplinary group of researchers and practitioners to discuss recent developments in attribution science and the field’s relevance to climate law and policy. Participants included physical scientists, public health researchers, economists, social scientists, legal scholars, advocates, and policy experts. This report provides a written summary of the conference proceedings.

Leading The Change: Staff-Driven Ai Transformation In Smu Libraries’ Collection Team, Siew Khim Lim, Fion Goh

Research Collection Library

No abstract provided.

Non-Uniform Mixing Of Quantum Walks On The Symmetric Group, Avah Banerjee

Computer Science Faculty Research & Creative Works

It is well-known that classical random walks on regular graphs converge to the uniform distribution. Quantum walks, in their various forms, are quantization's of their corresponding classical random walk processes. Gerhardt and Watrous (2003) demonstrated that continuous-time quantum walks do not converge to the uniform distribution on certain Cayley graphs of the Symmetric group, which by definition are all regular. In this paper, we demonstrate that discrete-time quantum walks, in the sense of quantized Markov chains as introduced by Szegedy (2004), also do not converge to the uniform distribution. We analyze the spectra of the Szegedy walk operators using the …

Why Technical Readiness Is Not Enough: Institutional Barriers To Full Harvest Strategy Adoption In The International Pacific Halibut Commission, Evelyn Roozee, Owen Temby, Gordon M. Hickey

School of Earth, Environmental, & Marine Sciences Faculty Publications

Harvest strategies are increasingly promoted as a mechanism to reduce political discretion and align fisheries management with pre-agreed scientific objectives. While substantial progress has been made in tuna regional fisheries management organizations (RFMOs), non-tuna RFMOs have lagged behind. Existing research has focused primarily on technical modeling challenges, with comparatively limited attention to the governance dynamics shaping adoption. Using the International Pacific Halibut Commission (IPHC) as an instrumental case study, we examine the progress and delays in the development of a harvest strategy policy (HSP) through semi-structured interviews and participant observation. We find that the IPHC successfully addressed commonly cited barriers, …

Wevit: Weight-Entangled Vision Transformers With Class-Specific Attention For Weakly Supervised Semantic Segmentation, Narges Saeedizadeh, Seyed Mohammad Jafar Jalali, Burhan Khan, Shady Mohamed

Research outputs 2022 to 2026

Weakly Supervised Semantic Segmentation (WSSS) is a challenging task in computer vision, as it relies on limited supervision to generate precise object localization maps, often using Class Activation Maps (CAMs). Traditional methods struggle with balancing localization accuracy and scalability due to their reliance on fixed network architectures and handcrafted strategies. Neural Architecture Search (NAS), despite its proven success in optimizing network designs across tasks, has not yet been explored in WSSS due to the need for efficient weight sharing. To address these limitations, we propose WEViT, a novel framework that integrates NAS with transformers to optimize network architectures and generate …

Sem-Pdpl: Semantic Exposure Graphs For Privacy-Law-Informed Risk Assessment Of Public Social-Media Data, Heba Ismail

All Works

Public social-media content often contains self-disclosed personal attributes that appear low-risk in isolation but become privacy-relevant when linked across posts, platform accounts, or user-level traces. Existing research has advanced privacy-sensitive content detection, de-anonymization analysis, social-media research ethics, and privacy-compliance workflows; however, limited work operationalizes how personal-data disclosures combine structurally and how these structures can be translated into auditable governance actions. This paper proposes SEM-PDPL, a computational, privacy-law-informed risk-assessment framework for modeling public social-media exposure as semantic exposure graphs and mapping graph patterns to controls aligned with the United Arab Emirates Personal Data Protection Law (PDPL) and compatible with GDPR principles. …

Modeling The Psychological And Technical Factors Influencing The Use Of Artificial Intelligence Tools Among Non-Native Arabic Learners: A Comparative Study In Egypt, Saudi Arabia, And Jordan., Mohammad Odeh, Alaa Al Din Musa, Ahmed Ragab Ali Ghalish, Montaser Adel Sayed Ahmed

All Works

This study aimed to develop a predictive longitudinal model of the psychological and technical factors influencing the use of artificial intelligence tools among non-native Arabic learners (international students) in three Arab countries: Egypt, the Kingdom of Saudi Arabia, and Jordan. The study adopted an extended Technology Acceptance Model (TAM) incorporating two psychological variables: trust in artificial intelligence and artificial intelligence anxiety. A quantitative longitudinal design with two time waves (T1 and T2) over a full academic semester was employed using Hierarchical Multiple Regression Analysis and PROCESS Macro for mediation. The sample consisted of 812 international students from public universities in …

Aqqd: Annotated Quranic Qira’At Dataset, Linda Smail, Mohammed Lataifeh, Md Sohazur Islam Sozib, Arthur Diniz De Souza

All Works

AQQD (Annotated Quranic Qira'at Dataset) is an open audio dataset of Quranic recitations annotated across canonical Qira'at styles. The dataset is designed to support research in machine learning, speech and audio processing, computational linguistics, and Quranic studies. The current release contains 24,183 WAV audio files from 309 reciters and covers 70 selected Quranic Surahs segmented into representative verses and phonetic variation points. Of these, 23,111 recordings were collected from publicly available sources, including official reciter websites, the Midad repository, MP3Quran, and verified YouTube channels, while an additional controlled subset of 1,072 recordings was obtained from a single reciter recorded as …

Efficient And Universal Watermarking For Llm-Generated Code Detection, Boquan Li, Zirui Fu, Mengdi Zhang, Peixin Zhang, Jun Sun, Xingmei Wang

Research Collection School Of Computing and Information Systems

Large language models (LLMs) have significantly enhanced the usability of AI-generated code, providing effective assistance to programmers. This advancement also raises ethical and legal concerns, such as academic dishonesty and the generation of malicious code. For accountability, it is imperative to detect whether a piece of code is AI-generated. Watermarking is broadly considered a promising solution and has been successfully applied to identify LLM-generated text. However, existing efforts on code are far from ideal, suffering from limited universality and excessive time and memory consumption. In this work, we propose a plugand- play watermarking approach for AI-generated code detection, named ACW …

Spring Ai 2026 Workshop And Speaker Series Report, Gregory Blike, Hannah (Nyingi) Brown, Dora (Dawn) Nguyen, Rami Huu Nguyen, Ajanee Igharo, Frayni Calderon, Moumita Saha, Chengjie Zheng

Paul English Applied Artificial Intelligence (AI) Institute Publications

The AI Workshop and Speaker Series was organized by the Student Advisory Council of the Paul English Applied Artificial Intelligence Institute at the University of Massachusetts Boston with the guidance of Distinguished Professor of Computer Science Wei Ding to create a practical and student-centered AI learning space. The Spring 2026 series included workshops on LinkedIn Optimization, Data Mining, GitHub, Prompt Engineering, Machine Learning of Structured Data, and Applied LLMs with Responsible AI Use in Research, while the broader speaker series introduced students to AI career development, generative AI and LLMs for cybersecurity, transportation security, political sciences, and AI in biomedicine. …

The Role Of Non-Symmetric Weights In Hermite–Hadamard Inequalities For Coordinated Ga-Convex And Ga-Quasi-Convex Functions, Muhammad Amer Latif, Ayesha Shabbir

Publications and Research

This paper establishes new Fejér and Hermite–Hadamard-type inequalities for functions of two variables whose mixed second-order partial derivatives satisfy coordinated GA-convexity or coordinated GA-quasi-convexity on a rectangle in the positive quadrant. Our main results are formulated for non-negative continuous weight functions that are not necessarily symmetric with respect to the geometric means of the interval endpoints, thereby extending the classical framework to genuinely asymmetric weights. However, to obtain explicit and sharp integral bounds in certain cases, we also employ a technical lemma that assumes a special symmetric setting where the weight function is symmetric on each coordinate with respect to …

Alaska Earthquake Center Quarterly Review October-December 2025, Heather Mcfarland, Beth Grassi, Austin Holland, Nate Murphy, Elisabeth Nadin, Carolyn Parcheta, Michael West

Alaska Earthquake Center Reports

This series of technical quarterly reports from the Alaska Earthquake Center (AEC) includes detailed summaries and updates on Alaska seismicity, the AEC seismic network and stations, fieldwork, our online presence, public outreach, and lists publications and presentations by AEC staff. Multiple AEC staff members contributed to this report.

Ultraviolet Imaging Of Sr 12 C With Hst/Wfc3: Accretion And Variability Of A Giant Planet At The End Stages Of Growth, Claire O. Finley, Brendan P. Bowler, Ya-Lin Wu, Adam L. Kraus, Yifan Zhou, Yuhiko Aoyama, William Best, Ian Czekala, Catherine C. Espaillat, Katherine B. Follette, Gregory J. Herczeg, Raquel A. Martinez, Connor E. Robinson, Quang H. Tran, K. Ward-Duong

Astronomy: Faculty Publications

Many details of the gas accretion phase during giant planet formation remain untested. We present new 0.2–0.7 μm UV-through-red optical imaging of the young, wide-orbit planetary-mass companion SR 12 c from the Wide Field Camera 3 (WFC3) instrument on board the Hubble Space Telescope. SR 12 c exhibits strong accretion-related continuum excess blueward of∼5000 Å and clear signs of the Balmer jump at 3646 Å. We derive a total accretion luminosity of1.65 ±0.19× 10⁻⁵L_⊙and a mass accretion rate of 8 ±2 × 10⁻¹² M_⊙yr⁻¹. Based on its mass and age,SR12 c …

Lessons Learned From The Adrenalin Load Disaggregation Challenge, András Balázs Tolnai, Zheng Ma, Igor Sartori, Clayton Miller, Stephen White, Matt Amos, Gustaf Bengtsson, Akram Hameed, Nørregaard Bo Jørgensen

Research Collection College of Integrative Studies

Crowdsourced data science competitions have emerged as a powerful mechanism for advancing research in energy informatics, offering scalable pathways for developing machine learning solutions that enhance energy efficiency and smart building operations. The ADRENALIN Load Disaggregation Challenge addressed a central problem in energy analytics—non-intrusive load monitoring (NILM) of heating and cooling loads in commercial buildings—while emphasizing the importance of model generalization across different buildings. This paper presents a comprehensive reflection on the lessons learned from organizing and executing the ADRENALIN competition, including technical insights, organizational challenges, and recommendations for future energy data challenges. In addition to the ADRENALIN case, a …

Ai-Ready Libraries Require Ai-Ready Librarians: Building Organisational Capability For Digital Transformation, Salihin Mohammed Ali

Research Collection Library

Academic libraries worldwide are rapidly experimenting with artificial intelligence (AI) to enhance research, learning, discovery, operations, and user engagement. However, many institutions continue to approach AI adoption primarily through isolated pilots, individual experimentation, or technology-centric initiatives. While these efforts generate innovation, they often struggle to scale sustainably without corresponding organisational capability development. This presentation argues that AI-ready libraries require AI-ready librarians and proposes an organisational capability approach for sustainable AI transformation in academic libraries. Drawing from the development of a library-wide AI strategy plans at Singapore Management University, the presentation explores how AI capability-building can be operationalised across diverse functional …

Prediction Of Pasture Condition In The Kimberley Rangelands Of Western Australia Using Simple Classification Tree Models, Ben Nestor, Kath Ryan, Charles Martin, Philip Thomas, Chris Hetherington, Matthew Fletcher, Robert Sudmeyer, Karyn Reeves

Natural Resources Research Articles

Pasture condition assessments assist pastoralists, regulators, and policy makers in making informed decisions around livestock production and the preservation of natural resources in the Kimberley rangelands of Western Australia (WA). Reliable qualitative assessments of pasture condition require assessors with extensive expertise, which means frequent and reproducible assessments can be difficult to achieve. To develop a quantitative approach that can complement existing qualitative assessment approaches in the Kimberley, we investigated the use of simple classification tree models to predict pasture condition using assessment data from the Western Australian Rangeland Monitoring System (WARMS). Quantitative traits were derived from WARMS observation data for …

Evolution Of Propagator Wakes On The Kolbeinsey Ridge From An Integrated Geophysical Perspective, Ethan Stowell

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

Oceanic lithosphere is formed following the extension and rifting of a continent, with new material generated at mid-ocean ridges. While ridges generally spread in the direction of extension, individual spreading centers are offset by perpendicular transform faults that break the ridges into individual segments. Ridge propagation, in which one ridge segment grows at the expense of another’s shortening, has been identified in global investigations as a poorly understood component of axial reorganization. This process leaves propagator wake structures composed of faults and pseudofaults visible as lows in Earth’s gravitational field, and transferred lithosphere with a distorted magnetic signature. This study …

Clark Tailings Consolidated Waste Management Area Site Investigation Quality Assurance Project Plan (Qapp), Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.