Fall 2025 PEAK Experiences Awardees for Undergrad Research

Several COE, COS, and Khoury students mentored by COE faculty are recipients of the Fall 2025 PEAK Experiences Awards from Northeastern’s Office of Undergraduate Research and Fellowships. This group of students from across the university will explore a wide variety of topics and questions from the intersection of maternal health public policy and structural inequality, to developing a low-cost device that can be used as a front-line detector for plant health deterioration, to exploring how universities act as economic anchors, supporting regional businesses and resilience, and more.

Base Camp Fellows
Exploring Methods to Eliminate the “Mirror Problem” in Computer Vision Techniques Awardee: Anoushka Abroal, Khoury’28 Mentor: Somaieh Amraee, Bouvé, Electrical and Computer Engineering Computer vision object detection is quite effective, until a reflective surface is involved. I intend to find a viable solution to the known computer vision problem where computer vision programs consider reflections as real object images during object detection and analysis.
Electrochemical ‘W-Cell’ Data Collection and Analysis Awardee: Ruth Benyo, COE’25 Mentor: Joshua Gallaway, COE, Chemical Engineering The electrochemical cell known as the W-Cell is a cell designed and created by members of the Gallaway group. This project serves as an effort to collect more data about how cell compression and electrolyte volume will affect the cycling behavior of the cell.
Ion-Dependent Tuning of Density-Driven Fingering in Hele–Shaw Cells Awardee: Daniel Cabestrero, COE’26 Mentor: Xiaoyu Tang, COE, Mechanical & Industrial Engineering This project explores how different dissolved ions, such as sodium, calcium, and barium, influence fluid mixing patterns in narrow channels. By observing how ion properties affect the formation and shape of these patterns, the study aims to uncover new ways to control flow instabilities in practical applications.
Enhancing Processing for Battery Cycling and Pressure Data Awardee: Tina Jiang, COE’27 Mentor: Juner Zhu, COE, Mechanical & Industrial Engineering The project aims to develop robust code that can seamlessly merge different datasets. Additionally, create plots by calculating the derivative of capacity, pressure, and voltage over time, to correlate with the state of health of battery cells. This will enable more accurate monitoring, diagnosis, and prediction of battery performance.
Utilizing Diamond-Agar Mixtures to Achieve Chemical-Free Cooling Immobilization of C. Elegans Awardee: Kavish Khamesra, COE’28 Mentor: Samuel Chung, COE, Bioengineering By enabling repeated imaging of C. elegans over multiple days, this method allows detailed longitudinal observation of developmental and behavioral changes. This work presents a novel immobilization approach utilizing a diamond-agar mixture, designed to replace harmful techniques that compromise C. elegans health and restrict long-term imaging.
High-Throughput Cultivation and Identification of Bacteria from 1,4-Dioxane Consortia Awardee: Grace McKrell, COS’27 Mentor: Rain Miao, COE, Civil & Environmental Engineer This project focuses upon isolating the most representative individual bacteria strains from an environmental enriched 1,4-dioxane metabolizing consortium by high-throughput method, and determining these pure isolates’ taxonomic classifications.
Designing Temperature-Responsive Adhesives to Enhance Robotics Efficiency Awardee: Abhi Nair, COE’28 Mentor: Ruobing Bai, COE, Mechanical & Industrial Engineering I am going to work on making a more adhesive material in order to then add onto robotics in order to increase functionality.
Computational Predictions and Experimental Validation of 2D Polymer Growth and Phase Behavior Awardee: Justin Oliak, COE’27 Mentor: Steve Lustig, COE, Chemical Engineering This project uses computational simulations and quantum chemistry to predict the growth kinetics, molecular weight distributions, shapes, and phase behavior of graphamid, a thermostable 2D polymer, while validating models through wet lab synthesis and characterization to optimize defect-free materials for applications like lightweight armor.
Using Wearable Sensor Data and Machine Learning to Identify Injury Risk in Athletes Awardee: Arnibish Ray, COE’28 Mentor: Aston McCullough, Bouvé, Physical Therapy, Movement, and Rehabilitation Sciences This project uses wearable motion sensors and machine learning to uncover patterns in how athletes move. By identifying movement profiles linked to injury risk, the research aims to improve injury prevention strategies and support the development of personalized training and rehabilitation programs.
Simulation/Prediction of Thermal Distortion in Metal Additive Manufacturing Awardee: Viren Sehgal, COE’28 Mentor: Yaning Li, COE, Mechanical & Industrial Engineering Additive manufacturing builds components layer by layer, using high energy sources like lasers. Since this process involves rapid heating and cooling, internal stresses such as warping, residual stress, and cracking are common. Predicting these distortions can help greatly to design parts that are more accurate and reliable.
Vertical Four-Channel Flow Cell for Single-Molecule Sensing Awardee: Howard Zheng, COS’27 Mentor: Meni Wanunu, COS, Physics This project develops a chip-based vertical flow cell with four parallel nanopore channels, combining precision single-molecule sensing with high speed and flexibility. The design allows efficient adjustment of experimental variables, enabling rapid protein detection and providing a versatile platform for biomedical research and future diagnostic applications.
Summit Fellows
Cobra: Crater Observing Bio-Inspired Rolling Articulator Awardee: Sera Arimori, COE’28 Mentor: Alireza Ramezani, COE, Electrical and Computer Engineering The COBRA Project (Crater Observing Bio-Inspired Rolling Articulator) is a snake-like robotic system designed to explore the Moon’s Shackleton Crater, where extreme temperatures and challenging terrain make exploration difficult. My work focuses on improving its mechanical and electronic systems, which includes battery placement, latching mechanisms, protective outer skin, and sensors in order to prepare for a titanium-printed prototype capable of withstanding lunar conditions. Using design, prototyping, and targeted testing, I aim to enhance durability, efficiency, and ease of maintenance. Results will be shared through presentations at RISE and relevant robotics conferences, contributing to advancements in space exploration.
Trabecular Meshwork on a Chip Awardee: Keerthi Atluri, COE’26 Mentor: Amir Vahabikashi, COE, Bioengineering This project focuses on developing a 3D “trabecular meshwork on a chip” to improve understanding of glaucoma and enable testing of new treatments without animal tissue. Glaucoma, a leading cause of blindness, often results from fluid buildup in the eye that increases pressure and damages the optic nerve. Using high-resolution 3D printing and a gel-like material called GelMA, the device will replicate the eye’s drainage tissue and support living cells. This model will provide a controlled, physiologically relevant platform for evaluating multiple therapies, making glaucoma research faster, more ethical, and more reproducible.
Quantum Materials Engineering through Tailored Metasurfaces Awardee: Brennan Bezdek, COE’26 Mentor: Alberto De la Torre, COS, Physics This project proposes the fabrication of dielectric metasurfaces to control quantum materials by harnessing their inherent sensitivity to external excitations via photons in photonic micro-cavities. This tool is a scalable approach to quantum materials control by replacing the need for large tuning fields and extreme environments with confined photons in a highly engineered electromagnetic environment. Findings from this project may enable the development of new quantum sensing probes and photon sources. Results will be shared at RISE and published in a peer-reviewed journal.
Agentic AI for Practical Impact: Supporting Sustainability, Healthcare, and Community Organizations Awardee: Aaron Bhattachan, COE’26 Mentor: Miguel Fuentes-Cabrera, Khoury, Data Science Imagine a world where AI agents transform how nonprofits, education centers, and clinical providers handle daily operations by automating routine tasks, managing workflows, and coordinating communications. While specific use cases may vary, this project will develop agentic AI to streamline scheduling, data entry, client follow-ups, and other processes. Over 50% of nonprofits today use or explore AI to increase efficiency and improve service delivery, while 80% of hospitals employ AI to boost operational performance. By piloting AI agents with local organizations, the project aims to boost efficiency, reduce errors, and enhance decision-making—helping organizations focus on critical work responsibly and effectively.
Identifying SIMD Code Fragments of a Higher-Order Parallel Programming Language Awardee: Anfisa Bogdanenko, COE’25 Mentor: Olin Shivers, Khoury, Computer Science Modern computers contain powerful parallel processors like GPUs, but programming them requires expert knowledge. Remora is a higher-order parallel programming language that seeks to solve this issue by delegating hardware-specific decisions to the compiler. This project extends Remora with a static code analysis that identifies which code fragments are well-suited for parallel hardware. The analysis will utilize abstract interpretation to determine whether a given code fragment is SIMD (Single-Instruction Multiple-Data), meaning a single set of instructions that can simultaneously operate on multiple data. The resulting specification will be implemented in the Remora compiler, shared at RISE and published domain-specific conferences.
Improvements of 3D Printed PMMA for Dental Applications Awardee: Umme Hani Bootwala, COE’27 Mentor: Ruobing Bai, COE, Mechanical & Industrial Engineering Over 12 million Americans lack dentures due to cost and access barriers, while many who have them suffer from discomfort and fragility. This project strengthens 3D-printed dental prostheses by reinforcing resins with embedded particles to improve durability. Using digital light processing (DLP) printing, self- reinforced PMMA witll be compared with other resins and techniques to enhance crack resistance, which is critical for withstanding chewing forces. If successful, this method could allow the widepsread adoption of 3D printing dental prostheses and reduce healthcare disparities. Results will be shared through open-access publications and industry partnerships.
Next Generation Periodic Extensional Flow Reactor Design, Fabrication, and Testing Awardee: Catherine Connolly, COE’28 Mentor: Adam Ekenseair, COE, Chemical Engineering Covalent organic frameworks can be formed into ultra-strong thin films with applications in numerous fields, including defense, energy, and biological systems. Most current film-making methods do not synthesize and process the film simultaneously, creating weak points that reduce performance. This project aims to build upon prior research to design a new reactor that achieves this simultaneous activity. The designed reactor will be tested first with a lower performance polymer, then with Graphimine — a breakthrough high-performance polymer first synthesized at Northeastern. Success would lead to stronger materials for critical applications and a patentable manufacturing process.
Guiding Vascular Organization in Cardiac Tissues via Geometric Cues Awardee: Maya Einhorn, COE’26 Mentor: Guohao Dai, COE, Bioengineering Stem cells take information and direction on how to differentiate from the environment around them, including their biochemical and mechanosensory niche. By supplementing media with specific proteins, stem cell colonies can form specific tissues, including cardiac tissue. The Dai Lab combines cardiac and vascular differentiation techniques, forming vascularized cardiac tissue, a physiologically relevant model. This project takes the next step in engineering the 3D patterning, which guides tissue architecture. By shaping tissues with varyious geometric molds, we will test whether structural cues drive certain vascular organization. These insights could accelerate the creation of physiologically relevant cardiac organoids for translational applications.
Polymerization of Novel 2D Polymers Awardee: Hannah Giusti, COE’26 Mentor: Steve Lustig, COE, Chemical Engineering Creating a product that is twice as stronger and lighter weight than Kevlar has applications including aerospace, defense, and sustainable initiatives. Emerging research in the field of two-dimensional polymers has confirmed such a mechanically durable, chemically resistant, and lightweight materials is possible. This research develops a novel extensional flow reactor, designed to allow for greater molecular alignment and results in significantly increased material strength and durability. The ability to control molecular orientation and reaction kinetics has widespread industrial applications manufacturing new products. Results from this research will be documented in a research article summary of findings.
Using CRISPR to Understand Collagen Matrix Formation Awardee: Luke Goncalves, COE’25 Mentor: Erin Cram, COS, Biology This project focuses on how cell migration guides organ formation. Cell migration is important in development, wound healing, and cancer. The DTC guides formation of the reproductive system in the worm. My project is about understanding how a network of collagen extracellular matrix proteins tells the DTC when and where to stop migrating.Our hypothesis is that collagen creates a less degradable matrix surrounding the DTC and halts DTC migration in adult worms. By adding this to a publication in progress, this can give new insights into unregulated cell migration which can be applied to other research areas such as metastasis.
Construction and Validation of an Inducible Cre-loxP Recombinase System For Plant Genomic Editing Awardee: Zaineb Irfan, COS’26 Mentor: Carolyn Lee-Parsons, COE, Chemical Engineering CRISPR/Cas-mediated genome editing in plants can be detrimental to cell health and growth due to a build up of Cas proteins. As such, this research aims to prevent the continued expression of Cas genes by cloning an inducible Cre- loxP recombinase system to remove the Cas gene after it has completed its desired edits. This system will be validated in the model plant Nicotiana benthamiana, with the goal of applying it later to transgenic plants generated by the Lee-Parsons lab. The findings from this project will be presented at RISE.
Contribution of Left Posterior Parietal Cortex on Ipsilateral Movement Adaptation Awardee: Jacob Kogan, COS’27 Mentor: Mathew Yarossi, Bouvé, Physical Therapy, Movement, and Rehabilitation Sciences Movement planning occurring in the left posterior parietal cortex (LPPC) is crucial in right-arm adaptation; however, its contribution in left-arm adaptation is unclear. Understanding how LPPC is involved in left-arm adaptation could facilitate motor recovery in people with motor impairments caused by neurological conditions. This project will causally examine the role of movement planning governed by LPPC in left-arm adaptation by using transcranial magnetic stimulation while participants are adapting to a novel environment. Analyzing reaching error, which reflects adaptation, will implicate the LPPC’s role in left-arm adaptation. I plan to present results at RISE and Society for Neuroscience conference.
Performance Testing Analysis of the Upgraded CMS ECAL Barrel Readout Electronics for HL-LHC Awardee: Charlie Lange, COE’27 Mentor: Toyoko Orimoto, COS, Physics This project will analyze data from the 2025 test beam of the CMS Electromagnetic Calorimeter (ECAL) at CERN, evaluating the performance of upgraded electronics designed for the High-Luminosity Large Hadron Collider. Higher luminosity will improve the observability of rare physics events but poses major detector challenges, such as radiation tolerance, timing resolution, and data throughput. The project will review prior analyses, reproduce 2024 results, and investigate the 2025 dataset in collaboration with ECAL experts. The findings will be compiled into an internal CMS report and presented at the CMS Upgrade meeting and the 2026 RISE showcase.
Investigating Electrode Wettability for Lithium-Ion Batteries Using Controlled Droplet Deposition Awardee: Nathan Lim, COE’27 Mentor: Juner Zhu, COE, Mechanical & Industrial Engineering This project explores how liquid electrolyte moves through the porous structure of lithium-ion battery electrodes in a process known as wetting or imbibition. Understanding this behavior is key to improving battery manufacturing efficiency and enabling rejuvenation of spent batteries. Using a micromanipulator to deposit electrolyte onto the electrode surface, we will characterize wetting under different conditions to develop a model that predicts infiltration behavior. By improving our understanding of this process, the study could clarify the fundamental science of multiphase flow in porous media. I plan to present at RISE and the Battery Sustainability Workshop, with potential for academic publication.
Dynamic Pulsating Crystallization in Evaporating Salt Droplets Awardee: Aavi Lund, COE’26 Mentor: Xiaoyu Tang, COE, Mechanical & Industrial Engineering Salt droplets typically form rigid crusts when they dry, but we have observed a novel dynamic pulsating phenomenon during the crystallization of cesium chloride droplets. Through systematic experiments varying environmental conditions and chemical composition, this research will identify what controls this pulsating behavior and develop theories explaining the underlying physics. This research advances fundamental understanding of crystallization dynamics and has potential applications in pharmaceutical manufacturing and droplet based devices. Results will be shared at RISE and APS’s Division of Fluid dynamics conference, with later plans for a publication in scientific journals.
Haptic Teleoperated Robotic Underwater Manipulator for Low Visibility Environments Awardee: Isabella Mor, COE’25 Mentor: Peter Whitney, COE, Mechanical & Industrial Engineering This project aims to assist with the development of a custom teleoperated robotics arm for underwater environments, where real time visual feedback is crucial. I will design a low-latency camera streaming subsystem capable of operating in a low-visibility environment, and an easy to navigate user interface to assist in teleoptic operation of the arm. In addition to the camera subsystem, I will assist with the assembly of the arm and field testing at Woods Hole Oceanographic Institute. Results of this project will be shared to a journal article this fall and in a formal presentation to the Northeastern robotics group.
Bacterial Nitrogen Metabolism Engineering to Overcome Reabsorption in Hepatic Encephalopathy Awardee: Katerina Pashiardis, COE’25 Mentor: Neel Joshi, COS, Chemistry & Chemical Biology Hepatic encephalopathy (HE) is a brain disorder caused by ammonia buildup resulting from liver detoxification failure. Hyperammonemia triggers neuroinflammation and disrupts neurotransmission, causing cognitive and functional impairments in HE patients. Gut bacteria exacerbate ammonia’s entry into the bloodstream by converting urea to ammonium. Similar therapeutic attempts have failed as they produced ammonium compounds that were reabsorbed systemically. This project engineers gut bacteria to maximize ammonium nitrogen sequestration, reducing its diffusion into the bloodstream. Our approach targets amino acid transporters and induces nitrogen-rich protein production to permanently sequester ammonium nitrogen. We hypothesize this will reverse hyperammonemia, offering a novel therapeutic.
Bio-Inspired Origami-Patterned Actuator Design Awardee: Sangli, COE’28 Mentor: Kris Dorsey, Bouvé, Electrical and Computer Engineering This project aims to modify origami-patterned soft robotic actuators to allow for greater and more complex control. By studying biological systems, the principles of natural locomotion can be incorporated into the design and prototype of the actuator. The results of this research will be shared in a peer-reviewed journal.
AmbientSense: Ambient Backscatter Communication for Air-Quality Monitoring Awardee: Shree Singhal, COE’26 Mentor: Stefano Basagni, COE, Electrical and Computer Engineering This project, AmbientSense, aims to design, prototype, and test an ultra-low-power, ultimately batteryless air-quality monitoring node for dense urban deployment. Leveraging ambient backscatter communication, where devices reflect existing signals rather than generating their own, AmbientSense enables continuous, maintenance-free sensing while reducing battery waste. By addressing the high cost and limited coverage of current monitoring networks, this project supports equitable, real-time monitoring for all communities. The final outcome will include a validated, scalable node prototype demonstrating the feasibility of this approach and lay the groundwork for scaling to city-wide networks, with findings disseminated through research showcases and an open-access report.
Applications of Nesocodin Formation in Scalable Proline-Sensing Hydrogels Awardee: Chloe Sivitz, COS’25 Mentor: Dan Wilson, COE, Chemical Engineering Enhanced proline production is a protective response in plants to biotic and abiotic stressors. In an age of heightened climate disaster occurrences and increased food requirements for a growing population, vegetation is increasingly under threat. A low-cost device that can be used as a front line detector for plant health deterioration without specialized lab equipment may play an important role for protecting environmental and human health. To address these concerns, I will use the formation of red-pigmented nesocodin derived from nectar in a gel matrix to optimize an accessible point-of-need sensor for plant stress via proline release.
Mechanical Characterization of Cell Suspensions in Flow Awardee: Ian Steele, COE’25 Mentor: Sara Hashmi, COE, Chemical Engineering Current methods for distinguishing cell types, such as identifying cancer cells from healthy cells, often depend on expensive and low-throughput assays. This project explores a faster and more cost-effective alternative by examining how cells deform when passing through small channels. By analyzing how different cell types respond to the mechanical stress, we aim to establish unique “mechanical fingerprints” for each type of cell. This label-free approach has the potential to transform medical diagnostics, enabling rapid cancer detection and efficient cell sorting. Findings will be presented at research conferences, including RISE and complex fluids, and targeted for publication in biomedical journals.
Building low-SWaP, High-Precision, Ruggedized 4-DOF Gimbal System for  Groundbreaking Aerospace Poin Awardee: Laura Teixeira, COE’27 Mentor: Josep Jornet, COE, Electrical and Computer Engineering In order to meet a significant technological gap in the wireless communications industry – ultra-precision pointing capabilties for modular payloads for high-gain antennas and laser terminals to operate on drones, satellites, and robotic vehicles– we are proposing and building a low size/weight/power/cost (SWaP-C), 4DoF gimbal pointing system capable of withstanding extreme environments including air and space (ruggedization) by embedding the system with an advanced vibration suppression algorithm. This technology, currently commercially unavailable in a SWaP-C form factor, would tremendously benefit laboratories in the Wireless Institute of Things and Institute for Experimental Robotics at Northeastern.
Targeted Nanomedicines for CNS Diseases Awardee: Waela Van Nostrand, COE’28 Mentor: Ganesh Thakur, Bouvé, Pharmaceutical Science This project aims to develop a targeted nanoparticle drug delivery system for central nervous system (CNS) diseases by overcoming the blood–brain barrier (BBB). By building on skills in nanoparticle fabrication, characterization, and cell culture gained in Dr. Shen’s lab, I will learn to measure drug loading efficiency and assess cellular uptake and efficacy. I will adapt these methods to optimize BBB permeability, therapeutic efficacy, and minimize toxicity. The collaborative opportunities, including BBB microfluidic modeling, will support early-stage in vitro studies. The objective is to enable more effective, less invasive CNS treatments with improved drug delivery and reduced systemic side effects.
Simulating and Fabricating Vortex-Pinning Superconducting Nanowire Single-Photon Detectors Awardee: Diego Velasquez, COE’28 Mentor: Marco Colangelo, COE, Electrical and Computer Engineering At the center of cutting edge research in quantum communication and computing, astronomy, and medical imaging are precise nanowire devices capable of detecting single photons. These Superconducting Nanowire Single-Photon Detectors (SNSPDs) are highly efficient superconductors. Although superconductors expel magnetic fields, small localized regions of magnetic field—called vortices—penetrate through an SNSPD’s nanowire. These unpredictable defects weaken the efficiency of SNSPDs, and are the focus of this project. Using the PHIDL and pyTDGL modules, I will design and simulate vortex-trapping SNSPD fragments; successful simulations will be fabricated using equipment from Northeastern’s and MIT’s cleanrooms and the tested results will be published.
The Role of Saltmarsh Soil in Carbon Storage Awardee: Cassandra Vongrej, COS’26 Mentor: Aron Stubbins, COS, Marine & Environment Sciences Saltmarshes are valuable ecosystems, as they provide habitat, flood protection, water quality enhancement, and carbon storage. However, due to climate change and resulting sea-level rise, these vulnerable ecosystems are threatened. There is a growing need to investigate how saltmarsh carbon cycling is impacted by these changes, specifically by looking at the soil. In this study, soil organic carbon (SOC) will be measured through dissolved organic carbon, fluroescent dissolved organic matter, and C and N isotopes. These parameters provide insight on saltmarsh carbon cycling and estimates on carbon storage mechanisms.
Mural Painting Robot Awardee: Oscar Wilmerding, COE’25 Mentor: Jahir Pabon, COE, Mechanical & Industrial Engineering Blank city walls often stay blank because commissioning a mural can cost tens of thousands of dollars, a prohibitive barrier for many communities. I’m developing a cable-based robot that moves like a plotter, firing paint valves timed in milliseconds to map digital images onto 20-foot facades. The project involves designing solvent-resistant micro valves, integrating them with stepper motor positioning, and testing on Boston’s legal graffiti wall. The result will be a full-color proof-of-concept mural plus freely available CAD files, code, and build instructions so artists and community groups can replicate or enhance the system and widen access to public art.
Low-Cost 5 DOF (Degree of Freedom) ROV (Remotely Operated Vehicle) Manipulator Awardee: Dylan Wolter, COE’27 Mentor: Bahram Shafai, COE, Electrical and Computer Engineering With the increase of robotics in studying the oceans, ROVs (Remotely Operated Vehicles) are on the forefront of exploration and require costly custom designed manipulators to be able to interact with their environment. In order to lower the barrier to entry, developing a low-cost solution would open the door for more researchers to have accessibility to this technology. My goal is to design, create, and test a low-cost electric 5 DOF (Degree of Freedom) Manipulator for small scale ROVs. My hope for the design is to allow this technology to be brought to more platforms and expand its utilization.
Creating a S1P-R1 Ex-vivo Knockdown Model Awardee: Emily Woo, COE’26 Mentor: Eno Ebong, COE, Chemical Engineering The goal of this project is to establish a line of S1P-R1 knockdown vascular endothelial cells to study the effects of the knockdown on endothelial cell glycocalyx (GCX) structure under disturbed and uniform flow conditions. I will participate in establishing the knockdown line with shRNA or siRNA methods, perform flow experiments using a millifluiic device, and stain for GCX structural components using immunocytochemistry. I will participate in data analysis and will present my results at both weekly lab meetings in PowerPoint format and at the annual RISE presentation in poster format in addition to a scientific publication.
Generalizable Neural Architectures for Metasurface Electromagnetic Modeling Awardee: Aaron Zhou, Khoury’28 Mentor: Yongmin Liu, COE, Electrical and Computer Engineering My project modernizes a proven approach to modeling electromagnetic scattering from metasurfaces, extending it with scalable and flexible neural network techniques. While traditional full-wave simulations remain computationally intensive and sensitive to size and shape, this work aims to build a neural model that generalizes across metasurfaces of arbitrary geometries. By capturing the underlying physics of light–matter interactions, the model offers a fast, differentiable pipeline for advanced optical systems such as holograms, lenses, and visualization devices to accelerate breakthroughs in medical imaging, ultra-fast data communications, and fields where precision optical design directly drives innovation and performance.

Related Departments:Bioengineering, Chemical Engineering, Civil & Environmental Engineering, Electrical & Computer Engineering, Mechanical & Industrial Engineering