Digital Commons Network^™

Ma 250 – Evaluating & Creating With Genai, Mohamed Ben Zid

Open Educational Resources

In this assignment, students use Excel and ChatGPT to design, analyze, and interpret a regression model. They create visualizations, calculate the regression equation manually, and make predictions before consulting AI-generated feedback on their model’s strengths and limitations. Students then compare their own interpretation with ChatGPT’s insights, summarize their findings, and critically assess the model’s accuracy and real-world usefulness. The exercise develops quantitative reasoning, practical AI application, and reflective evaluation skills.

Decentralized Linear Solvers: Communication Cost And Privacy, Nelson G. Brasil, Vinay A. Vaishampayan

Publications and Research

We consider the problem of multiple parties iteratively solving a system of linear equations in a decentralized manner. Specifically, we solve for $\negr{x} \in \R^n$, the $n \times n$ system of linear equations $M\negr{x} = \negr{b}$ when each party only knows their row of the matrix $M$ and a single component of $\negr{b} \in \R^n$. Our objective is to determine the tradeoff between the accuracy of the solution and the total communication cost measured in bits. A fully connected, reliable mesh network is assumed to connect the different parties. We develop a general formulation that applies to a large class …

An Empirical Framework For Evaluating Semantic Preservation Using Hugging Face, Nan Jia, Anita Raja, Raffi Khatchadourian

Publications and Research

As machine learning (ML) becomes an integral part of high-autonomy systems, it is critical to ensure the trustworthiness of learning-enabled software systems (LESS). Yet, the nondeterministic and run-time-defined semantics of ML complicate traditional software refactoring. We define semantic preservation in LESS as the property that optimizations of intelligent components do not alter the system's overall functional behavior. This paper introduces an empirical framework to evaluate semantic preservation in LESS by mining model evolution data from HuggingFace. We extract commit histories, $\textit{Model Cards}$, and performance metrics from a large number of models. To establish baselines, we conducted case studies in three …

All Games Have Equilibria, M. Ali Khan, Arthur Paul Pedersen, Maxwell B. Stinchcombe

Publications and Research

Research on Nash equilibrium existence for infinite games has grown into a patchwork of technical preconditions and counterexamples. This paper presents a unified program in equilibrium theory by revising the predominant model of mixed strategies based on countable additivity. A game is specified by a nonempty set of players and, for each player, a nonempty action set and a bounded von Neumann-Morgenstern utility function. Every such game is shown to admit a Nash equilibrium in finitely additive mixed strategies. In addition, the equilibrium correspondence for any such game is shown to be nonempty, compact-valued, and upper hemicontinuous, and the same …

Resilience For Whom? A Study In Pathways And Production Of Unequal Risk In The Rockaways, Aaryan M. Nair

Publications and Research

This paper investigates how climate adaptation policies in the Rockaway Peninsula of New York City produce unequal outcomes despite their ostensibly neutral design, framing resilience as an environmental and climate justice problem. Situated within a landscape marked by stark socioeconomic disparities, aging housing stock, and high exposure to coastal flooding, the study demonstrates that existing adaptation strategies—centered on uniform technical standards, insurance frameworks, and large-scale coastal infrastructure—systematically advantage actors with greater financial and institutional capacity while leaving low-income residents, particularly renters, disproportionately vulnerable.

The analysis identifies three core dynamics underlying this “unequal-by-design” resilience regime: (1) the stratified feasibility of compliance …

Gowanus Faces A Hidden Threat Beneath Its Neighborhood Boom, Emma J. Rosenberg

Capstones

This article investigates urban redevelopment, climate change and environmental contamination in Brooklyn’s Gowanus neighborhood. The Gowanus Canal itself has been a designated EPA Federal Superfund Site since 2010, this designation does not apply to the land surrounding it where legacy industrial contamination still exists. This includes coal tar from former manufactured gas plants which poses a risk to groundwater and indoor air. Under a 2021 rezoning plan, large-scale residential redevelopment is rapidly moving forward, rising groundwater and increased flooding associated with climate change may exacerbate contaminants. Utilizing agency documents, Community Advisory Group meetings, and conversations with residents, advocates, officials and …

How Has Your Climate Changed?, Rhyannon Bartlett-Imadegawa

Capstones

This interactive data visualization shows readers how much the climate has changed in their home state compared to 100 years ago, since the reader was born, the current year and projections into the future. It aims to communicate climate change impacts more personally by linking it to seasons, the reader's birth year and age mile stones and compares a readers' home state to a state that has been more impacted to connect across different states and communities.

Using JavaScript and Svelte, the code calculates and displays seasonal averages for the baseline period for the reader's state and years for the …

Flooding, Not Just A Rain Problem, Annisha Singh

Capstones

This capstone focuses on the Rockaway Peninsula and how high-tide flooding also known as "sunny-day flooding" is not only affecting Rockaway but neighboring areas, such as Jamaica Bay.

Modeling Mineral Redistribution In Biological Tissue Using Apple As An In Vitro Analogue, Daler Djuraev, Ali Algemsh, Halima Alazeb, Zeenia Ahmed

Publications and Research

This project aims to model mineral (ion) redistribution that occurs in human soft tissue after injury or mechanical/thermal stress. Because direct, repeatable in vivo measurements are difficult, we use apples as an in vitro analogue: their mineral content is relatively uniform and the tissue can be cut, dried, and repeatedly imaged under controlled conditions. Using X-ray imaging, we tracked how minerals in apple tissue move toward damaged regions immediately after cutting, and how subsequent drying at room temperature drives a redistribution toward the central core. We also observed that biological degradation (decay) alters mineral density over time, indicating that even …

Challenges In Engineering Machine Learning (Software) Systems, Raffi T. Khatchadourian Ph.D.

Open Educational Resources

Lecture slides on the software engineering challenges unique to machine learning systems, for an undergraduate software engineering course. After contrasting traditional programming with machine learning, the deck examines why the usual tools for managing complexity—abstraction, reuse, and composition—are harder to apply to ML, given the lack of clear specifications and modularity. It covers concept drift, feedback loops (illustrated with crime-prediction and recommendation examples), and the accumulation of technical debt in ML systems, including the role and pitfalls of notebooks in moving from experimentation to production. Based on "Machine Learning in Production/AI Engineering" by Christian Kaestner and Eunsuk Kang (Carnegie Mellon …

My First Conversation With Chatgpt (February 22, 2023): Origins Of A Generative Dialogue, David Smith

Publications and Research

This working paper presents the first recorded interaction between the author and the generative AI system ChatGPT, written on February 22, 2023 during the initial weeks of a faculty sabbatical in Boston. The document preserves a complete and unedited transcript of an exploratory conversation conducted without predetermined research aims, marking the author’s first encounter with a large-language-model conversational interface. Although the exchange includes creative experimentation—including musical and poetic prompts—the discussion remains informal and wide-ranging, and no theoretical framework is articulated at this stage. Rather, this transcript is published as primary-source material documenting the moment of discovery and experimentation that precedes …

Math Meets Climate: The Energy Balance Model, Maria I. Sanchez Muniz

Open Educational Resources

This assignment introduces students to the mathematics of Earth’s climate through the classical energy balance model. Students analyze how incoming solar radiation, outgoing thermal radiation, and temperature-dependent albedo interact to determine Earth’s equilibrium temperature. Using analytical calculations and computational tools, students identify equilibrium states, assess their stability, and interpret the results through the lens of dynamical systems and bifurcation theory. The activity builds conceptual understanding of climate feedbacks, greenhouse effects, and tipping behavior using a transparent, one-variable model. Designed for applied mathematics and interdisciplinary STEM courses, this assignment emphasizes computation, physical interpretation, and real-world relevance. It is released as a …

Understanding Enso Through Mathematical Models, Maria I. Sanchez Muniz

Open Educational Resources

This assignment introduces students to conceptual models of the El Niño–Southern Oscillation (ENSO) and guides them through a structured investigation of their physical and mathematical foundations. Students analyze the recharge–oscillator and delayed–oscillator frameworks, explore how differential equations capture ocean–atmosphere interactions, and evaluate parameter-driven changes in oscillatory behavior. A key component of the work is the guided use of generative AI as a research tool: students employ AI models to locate peer-reviewed literature, interrogate model extensions, and refine their understanding of complex mechanisms, while synthesizing all final explanations in their own words. By blending classical climate modeling with modern AI-supported inquiry, …

Evaluating How New York City’S Recycling And Organic Waste Systems Reduce Resource Waste And Methane Emissions, Zihan Cao

Publications and Research

This study analyzes New York City’s waste management systems, with a focus on food waste diversion, composting, and renewable energy initiatives, to assess their role in methane emission reduction and resource efficiency. The analysis highlights the relative effectiveness of different waste management pathways and suggests that community-scale composting and decentralized anaerobic digestion are associated with substantial methane reductions relative to cost.

The Study Of Hybrid Nanostructures For Optoelectronics, Alex Davis, Khaoula Dehhou

Publications and Research

Hybrid nanostructures that combine zero-dimensional (0D) quantum dots (QDs) with two-dimensional (2D) transition-metal dichalcogenides (TMDs) are promising building blocks for next-generation optoelectronic devices, such as highly sensitive photodetectors, light-emitting diodes, and tunable light sources. These hybrid systems take advantage of the strong, size-dependent emission of colloidal QDs and the high carrier mobility and tunable band structure of 2D materials. In this research, we investigate hybrid structures composed of colloidal CdSe/ZnS, CuInS/ZnS, and PbS QDs integrated with indium selenide (InSe), a TMD known for its exceptional electron mobility and robust photoluminescence in few-layer form. The goal is to understand how interfacial …

Ctrl + Alt + Inner Speech: A Verbal–Cognitive Scaffold (Vcs) Model Of Pathways To Computational Thinking, Daisuke Akiba

Publications and Research

This theoretical paper introduces the Verbal–Cognitive Scaffold (VCS) Model, a cognitively inclusive framework which proposes the cognitive architectures underlying computational thinking (CT). Moving beyond monolithic theories of cognition (e.g., executive-function and metacognitive control models), the VCS Model posits inner speech (InSp) as the predominant cognitive pathway supporting CT operations in neurotypical populations. Synthesizing interdisciplinary scholarship across cognitive science, computational theory, neurodiversity research, and others, this framework articulates distinct mechanisms through which InSp supports CT. The model specifies four primary pathways linking InSp to CT components: verbal working memory supporting decomposition, symbolic representation facilitating pattern recognition and abstraction, sequential processing enabling …

Extensions Of Weighted Integral Inequalities For Ga-Convex Functions In Connection With Fejér’S Result, Muhammad Amer Latif

Publications and Research

No abstract provided.

Early Conceptual Sketches Of Blended Reality And The Precursor To The Bbs Quad (2022), David Smith

Publications and Research

This document contains two original hand-drawn conceptual sketches created in early 2022, representing the earliest visual formulations of what would later evolve into the Balanced Blended Space (BBS) framework. The drawings predate my first conversations with ChatGPT and were produced as part of my independent sabbatical research into blended environments, mediated performance, and human–machine interaction.

The first drawing examines human–computational mediation, perception, and internal mapping. The second sketch—later referred to informally as the “BBS Quad”—extends this idea by reconciling cognition–computation symmetry with physical–virtual spatial relationships. Published together, these images document the conceptual foundations of the BBS framework prior to its …

Introduction To Machine Learning And Machine Learning Systems, Raffi T. Khatchadourian Ph.D.

Open Educational Resources

Lecture slides introducing machine learning and machine learning systems for an undergraduate software engineering course. Topics include what machine learning is and how it differs from traditional programming, foundation models, the major types of learning (supervised, unsupervised, reinforcement, and others), and applications across domains. Using a food-delivery time-prediction case study, the deck walks through a typical ML pipeline—data collection and cleaning, feature engineering, model training, and evaluation—and covers evaluation methods (precision and recall, confusion matrices, error measures) along with underfitting versus overfitting and the realities of learning and evaluation in production. Based on "Machine Learning in Production/AI Engineering" by Christian …

Saussure’S Universal Distinctive Feature Dimensions, Thomas M. Eccardt

Publications and Research

This paper revisits Saussure’s scalar analysis of phonemes, offering a modern reinterpretation that replaces binary features with phonological dimensions grounded in measurement theory. By redefining Saussure’s [openness] and [backness] as ordered scales and Chomsky and Halle’s “combination and concatenation” as partially ordered scales, the paper introduces a notion of “[phono]logical simultaneity.” This framework renders the variously-defined phoneme and segment redundant, and shifts the focus of distinctiveness to the linguistic sign, the morpheme. It demonstrates how phonological dimensions link continuous articulations and acoustic signals (e.g., F1 and F2) with discrete linguistic signs through calibrated distinctive features. The analysis identifies Saussure’s two …

Speculative Automated Refactoring Of Imperative Deep Learning Programs To Graph Execution, Raffi Khatchadourian Ph.D., Tatiana Castro Vélez, Mehdi Bagherzadeh, Nan Jia, Anita Raja

Publications and Research

Efficiency is essential to support ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code---supporting symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, imperative DL frameworks encouraging eager execution have emerged but at the expense of run-time performance. Though hybrid approaches aim for the "best of both worlds," using them effectively requires subtle considerations. Our key insight is that, while DL programs typically execute sequentially, hybridizing imperative DL code resembles parallelizing sequential code in traditional systems. Inspired by this, we …

Speculative Automated Refactoring Of Imperative Deep Learning Programs To Graph Execution, Raffi Khatchadourian Ph.D., Tatiana Castro Vélez, Mehdi Bagherzadeh, Nan Jia, Anita Raja

Publications and Research

Efficiency is essential to support ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code---supporting symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, imperative DL frameworks encouraging eager execution have emerged but at the expense of run-time performance. Though hybrid approaches aim for the "best of both worlds," using them effectively requires subtle considerations. Our key insight is that, while DL programs typically execute sequentially, hybridizing imperative DL code resembles parallelizing sequential code in traditional systems. Inspired by this, we …

Speculative Automated Refactoring Of Imperative Deep Learning Programs To Graph Execution, Raffi T. Khatchadourian Ph.D., Tatiana Castro Vélez, Mehdi Bagherzadeh, Nan Jia, Anita Raja

Publications and Research

Efficiency is essential to support ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code---supporting symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, imperative DL frameworks encouraging eager execution have emerged but at the expense of run-time performance. Though hybrid approaches aim for the "best of both worlds," using them effectively requires subtle considerations. Our key insight is that, while DL programs typically execute sequentially, hybridizing imperative DL code resembles parallelizing sequential code in traditional systems. Inspired by this, we …

Electric-Field Tunable Magnetoexcitons In Xenes/Hbn/Tmdc, Xenes/Hbn/Bp, And Xenes/Hbn/Tmtc Heterostructures, Roman Ya. Kezerashvili, Anastasia Spiridonova, Klaus Ziegler

Publications and Research

In this work, we propose novel van der Waals heterostructures composed of Xenes, transition metal dichalcogenides (TMDCs), phosphor ene, and transition metal trichalcogenides (TMTCs), which are separated by insulating hexagonal boron nitride (hBN) layers. We theoreti cally investigate the behavior of Rydberg indirect excitons in Xenes/hBN/TMDC, Xenes/hBN/phosphorene and Xenes/hBN/TMTC heterostructures subjected to parallel external electric and magnetic fields that are oriented perpendicular to the layers. By incorporating both isotropic and anisotropic materials, we demonstrate that excitonic properties can be effectively tuned through the external field strengths and the heterostructure design. Our results show that the exciton reduced mass and the …

Does Idiosyncratic Volatility Follow A Random-Walk? Evidence From U.S. Stocks, Zihan Cao, Ossama Elhadary

Publications and Research

In asset pricing literature, idiosyncratic volatility (IVOL) measures the firm-specific risk that is not explained by broader market movements. In this study, I investigate whether the idiosyncratic volatility (IVOL) of individual stocks follows a random-walk. Using monthly residuals from the Fama-French three-factor model (Fama & French, 1993), I estimate IVOL for more than 11,000 U.S. stocks, and apply the Augmented Dickey-Fuller test (Said & Dickey, 1984) to determine whether IVOL behaves like a random-walk. While most stocks display random-walk behavior, the proportion varies across industries, with some sectors showing deviations from random-walk behavior. Stocks with different levels of average return …

Engagement By Design: Belongingness, Cultural Value Orientations, And Pathways Into Emerging Technologies, Daisuke Akiba, Michael Perrone, Caterina Almendral, Rebecca Garte

Publications and Research

This theoretical article examines how belongingness, defined as the sense that one’s participation is legitimate and valued, interacts with cultural value orientations to help explain persistent disparities in U.S. technology engagement, including emerging technologies, across racial and ethnic groups. While structural barriers (e.g., racism, poverty, linguistic bias, etc.) remain essential to understanding such inequity, we argue that engagement patterns in technology also reflect how different cultural communities may define and experience belongingness in relation to digital domains. Drawing on Triandis and Gelfand’s framework, and focusing specifically on educational contexts, we propose the Belongingness through Cultural Value Alignment (BCVA) model, whereby …

R12 Equivalent Resistance Reduction Steps, Vasiliy S. Znamenskiy, Rafael Niyazov

Open Educational Resources

We present a concise, step-by-step reduction of a symmetric resistor network to its equivalent resistance 𝑅₁₂, emphasizing visual reasoning over algebraic brute force. By redrawing the circuit to expose symmetry, we identify equipotential node pairs joined by ideal conductors; the “bottom” bridging resistor is shown to carry zero current and is removed from consideration. The remaining topology reduces by two repeated series combinations, where each left/right pair of equal resistors collapses to 2R. The final network is a three-branch parallel combination (2𝑅∥𝑅∥2𝑅), yielding the closed-form result 𝑅₁₂=𝑅/2. The procedure illustrates three transferable techniques for introductory circuit …

Challenges In Developing Physical Intuition In College General Physics Courses, Vasiliy S. Znamenskiy, Rafael Niyazov

Open Educational Resources

Many students can memorize formulas but struggle to feel what a newton, joule, or volt means; they treat formulas as plug-and-chug templates rather than descriptions of relationships among physical quantities. This presentation introduces three types of learning activities: (1) text-free (“no-text”) problems, in which carefully designed visuals replace prose to convey relationships and constraints; (2) anti-problems, which begin with a mathematical expression and ask students to imagine a physical situation it could describe; and (3) lab games that turn routine measurement into purposeful play, emphasizing estimation, scaling, and unit sense. We provide ready-made, Brightspace-compatible assessments alongside low-tech implementation options. The …

Citytech Algebra Based Physics Exam1 (Brightspace Quiz), Vasiliy S. Znamenskiy, Rafael Niyazov

Open Educational Resources

This Brightspace-based Exam 1 assesses foundational concepts in algebra-based physics through short, auto-graded items designed to provide clear feedback. The exam targets core learning outcomes from the opening units of the course: measurement and unit analysis, significant figures, one-dimensional kinematics with constant acceleration (relationships among 𝑥, 𝑣, 𝑎, 𝑡), and basic problem-solving with proportional reasoning. Question formats include numerical entry multiple choice focused on common misconceptions, and brief conceptual prompts that test qualitative understanding before calculation. The item set emphasizes translating among verbal descriptions, diagrams, formulas, and graphs; checking the reasonableness of results; and communicating precision. Randomized parameters and pooled …

Designing Equity-Focused Pedagogy In Mathematics Teacher Preparation With Digital Data Tools, Nadia Stoyanova Kennedy, Boyan Kostadinov, Sandie Han

Publications and Research

This study examines the implementation of a course module that integrated computing and data analysis. The module aimed to engage prospective mathematics teachers in the practice of working with datasets and analyzing data to investigate questions related to local Brooklyn schools, as well as to gain deeper insight into the students and communities where they conduct their field experiences. Throughout the module, teacher candidates explored issues such as student learning opportunities, achievement gaps, school segregation, educational (in)equity, and other social justice concerns through readings, data analysis, and direct engagement. They shared and reflected on their findings with peers, deepening their …