Physical Sciences and Mathematics Commons^™

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, …

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 …

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.

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 …

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 …

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 …

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 …

Csc36000 - Modern Distributed Computing Assignment, Saptarashmi Bandyopadhyay

Open Educational Resources

This assignment covers standard performance metrics for Distributed Systems and the basics of Multiprocessing for CSC36000 - Modern Distributed Computing at the City College of New York CUNY. It is an interactive coding assignment intended to be executed in a Python notebook.

Art Forms: Born Out Of Necessity, Urmi Duttagupta

Publications and Research

This collection of artworks expresses the artist’s profound passion for mathematics and life’s complex balance. As a female mathematician, she uses artistic expression and intricate patterns to evoke mathematical beauty and feminine strength, celebrating the presence and resilience of women in mathematics.

Major, Trace And Rare Earth Element Concentrations In Nist Standard Reference Material® 1646a Analyzed By Als Global Using Method Me-Ms61r, Jane L. Alexander

Publications and Research

This technical note compares analytical results obtained from ALS Global Method ME-MS61r with the certified and previously published results for NIST Standard Reference Material® 1646a, Estuarine Sediment. The results are grouped into major, trace and rare earth elements, and focus on elements used by sedimentary geochemists, for example in studies of sediment provenance. The results from ALS Global Method ME-MS61r are internally consistent and generally robust when compared with published analyses. However, acid digestion may not completely dissolve resistant minerals, leading to under-reporting of some elements such as Ti, Cr, Zr, heavy REE and Y.

The Floodnet Community Engagement Guide, Véronëque Ignace, Sofia Mariyamis, Kendra Krueger, Polly Pierone, Hayley Elszasz, Hannah Eisler Burnett

The Science and Resilience Institute at Jamaica Bay, SRIJB

"At the Intersection of Science, Policy, and Community: The FloodNet NYC Community Engagement Strategy” is a public-facing community engagement guide that documents the strategies, tools, and lessons developed through FloodNet NYC, a cross-sector partnership among researchers at NYU and CUNY and New York City agencies. Designed as a practical resource, this guide shares our approach to community engagement and dissemination so that researchers, practitioners, community organizations, and public agencies can adapt these methods to their own urban climate science projects and other community-centered efforts that address climate challenges.

Grounded in community-based participatory research (CBPR) principles, the guide presents community engagement …

Multi-Modal Depth Estimation Using Camera And Mmwave Sensors, Alston D. Devero-Belfon

Student Theses

For accurately estimating the depth of environments with varying lighting conditions, reliable methods are limited. By utilizing wireless sensor technology in conjunction with cameras, a wide range of environments can be visualized, and objects within these environments can be tracked and monitored. Such methods offer cost-effective alternatives and provide a more secure, data-at-rest option for individuals with low vision, while also enhancing machine perception. In this work, we develop such a prototype that utilizes wireless sensors and cameras, which act in sync, enabling us to estimate the depth of objects within varying lighting environments to a level that is recognizable …

Non-Perturbative Aspects Of Gauge Theories Through A Complex Parametrization, Antonina Maj

Dissertations, Theses, and Capstone Projects

This dissertation explores a complex matrix parametrization of four-dimensional non-Abelian gauge theories as a means of gaining analytical insights into (3+1)-dimensional QCD. The low-energy scale of non-Abelian gauge theories remains an elusive area of research even after decades of work. A key challenge lies in identifying physical, gauge-invariant degrees of freedom that are relevant to non-perturbative phenomena. In this dissertation we develop a complex parametrization of gauge fields on which gauge transformations act homogeneously, thereby enabling a manifestly gauge-invariant analytical formulation of the theory.

Chapter one constructs the complex gauge-invariant parametrization for gauge theories living on both complex projective space …

The Density Distribution Of The Material Around Betelgeuse, Iman Behbehani

Dissertations, Theses, and Capstone Projects

Betelgeuse is a red supergiant star visible in the constellation Orion. Its windy and highly convective surface results in a complicated mass loss pattern difficult to understand and replicate in simulations. The ejected mass can form a shell around the star we consider the circumstellar material (CSM). In this study, we use ALMA interferometric observations to find the structure of Betelgeuse's CSM, and connect to the mass loss mechanisms that could form it. We measure a bipolar circumstellar structure with a position angle of 42.3$\pm 7.0^\circ$. We observe asymmetries in the form of hot spots in the north east of …

Developments In The Lithographic Engineering Of Bi2sr2cacu2o8+Delta Mesa Terahertz-Emitting Devices, Sarah Elghazoly

Dissertations, Theses, and Capstone Projects

Devices microfabricated from the high-temperature superconducting cuprate Bi₂Sr₂CaCu₂O_8+𝛿 (Bi-2212) are a promising source of coherent terahertz radiation within the ’terahertz gap’ (0.3- 1.5 THz). A current-biased mesa patterned into the surface of a single crystal will produce electromagnetic radiation in the terahertz regime due to the naturally occurring Josephson junctions formed by the stacks of superconducting cuprate oxide planes in the material separated by insulating BiO and SrO barrier layers. Previous research has shown that by fabricating these mesas such that the geometry supports resonant cavity Fabry-Perot modes, the junctions within the mesa …

Towards Automated Evolution Of Imperative Deep Learning Programs, Tatiana Castro-Vélez

Dissertations, Theses, and Capstone Projects

Software engineering (SE) is increasingly intersecting with data-centric domains such as machine learning (ML) and deep learning (DL). Similar to bugs in traditional software systems, defects can emerge in ML and DL systems. ML, including DL, systems are now widespread and rely on dynamic models defined by input data. Developers face the challenge of building dependable systems while addressing the demand for scalable software.

Efficiency is essential to support responsiveness with respect to ever-growing datasets. Traditional DL frameworks achieve scalability through deferred execution, enabling symbolic, graph-based deep neural network (DNN) computation. While efficient, this approach is error-prone, cumbersome, and difficult …

Starspot Inference Using Light Curve Inversion Techniques, Mohammad Refat

Dissertations, Theses, and Capstone Projects

Star spots are patches that are dark or bright on the surface of a star. They are tightly correlated to the magnetic activity of stars. One of the reasons we want to study star spots is to better understand where the active latitude of stars are located, which helps us understand planet habitability around low mass stars. The Starry package is a set of tools that can map the surface of stars and exoplanets using time series data, with spherical harmonics. Butterpy is a package that allows for the simulation of starspot evolution and their lightcurves. Fleck is a package …

How To Form A Gravitational-Wave Source: Quantifying Intermediate Evolutionary Stages In Isolated Binary Stellar Evolution, Ana Lam

Dissertations, Theses, and Capstone Projects

Gravitational-wave (GW) detections from double compact object (DCO) mergers provide crucial observational constraints for understanding massive stars across cosmic time. Coupled with these observations, binary population synthesis simulations become powerful tools for probing the formation, evolution, and ultimate fates of their progenitors---massive binary stars. However, complex evolutionary pathways, shaped by key intermediate stages such as mass transfer phases and supernovae, present a significant challenge to assess their impact. To address this, we develop a framework to quantify the influence of intermediate evolutionary stages on GW sources. By combining Sankey diagrams with survival factors, we systematically investigate how intermediate stages influence …

Effect Of Equation Of State On The Formation Of Binary Black Holes In Active Galactic Nucleus Disks, Theodore Edwards

Dissertations, Theses, and Capstone Projects

Active galactic nucleus disks have been proposed as a possibly dominant location of the mergers of binary black holes detected by gravitational wave observatories. The nonlinear interactions between stellar mass black holes and disk gas determine when binaries will form from single objects on nearby orbits. Prior work has used smoothed particle hydrodynamics models in an isothermal disk to study this problem. However, the local equation of state near the midplane of an optically thick accretion disk is adiabatic rather than isothermal, even if the radiative equilibrium temperature is azimuthally isothermal. Therefore, we investigate the use of an adiabatic equation …