M.Eng. Graduates

Master of Engineering 2024

Yaa Achampong
Saud Alfakhri
Michelle Barth
Meredith Brafman
Seonae Breckenridge
Nathan Brown
Soobin Choi
Alexa Crist
Sunita Devi
Anukriti Dey
Paris Dickens
Yaopeng Ding
Maria Dobransky
Jonathan Ebenezer
Angelina Fahrenkrug
Yiwei Feng
Rutika Gavate
Kaelyn Gaza
Hayleigh Goodrich
Anagha Gopinath
Ana Grandgeorge
Shayona Gupta
Rachel Hercek
Ganqing(Luke) Hu
Yuqian Hu
Anica Huang
Yuan Jiang
Lakshmi Karuturi
Sofia Kashtelyan
Peculiar Lawrence
Xu Lian
Yiming Lu
Tianqi Lu
Yufei Ma
Vyshnavi Madala 
Advait Mani
Thomas Materdey
Angelique Jan Miane
Baisampayan Moitra
Daniel Morgan
Shahab Nassar
Shannya Niveyro
Ariana O’Brien
Nawal Panjwani
Rhianna Patel
Jianying Peng
Rishi Pothakamuri
Jiayin Qu
Reuben Rosen
Cody Rougeux
Pranav Sakre
Maria Santiago
Priyanka Seth
Yuancheng Shao
Purva Shenoy
Phyo Pyae Sone
Aniqa Tabassum
Joshua Turner
Veronica Vila
Jialiang Wang
Willa Wei
Sarah West
Myles Wood
Jingyi Xu
Yuhui Xu
Kyle Zappi
Jiahao Zhang
Vivian Zhao
Zimu Zhou
Maham Zia
Ian Zobrist



Team Projects

Novel secondary containment for advanced therapy transportation 

Ariana O’Brien, Rhianna Patel, Shahab Nassar

Advanced therapies are high value, high cost treatments for critical illnesses. To ensure that active pharmaceutical ingredient (API) integrity and efficacy is maintained, advanced therapies are transported at cryogenic temperatures. Current solutions fall short in their high number of unit operations and their inability to customize logistics for an individual therapy. Addressing these shortcomings, we designed a hybrid secondary containment module, combining passive and active cooling mechanisms to maintain temperatures less than –150 °C for transit time. We computationally modeled the design and experimentally tested various inputs for the parameters and converged on an optimized design of an internal apparatus scaled down to transport a single therapy using passive cooling. This internal apparatus will be placed within an outer system of active cooling to maintain cryogenic temperatures and protect API integrity for the entire duration of transportation. This design is recommended for implementation in future advanced therapy logistical applications to ensure the highest efficacy drug for patients, and its scope would likely apply to other types of cold-chain transportation as well.

Silent speech device for speech recognition

Aniqa Tabassum, Ganqing Hu

This project focuses on developing a silent speech device using surface electromyography (sEMG) to detect articulatory muscle movements aided by machine learning. Our device would allow intubated patients to significantly communicate their needs and problems by recognizing what they are trying to say. All patients would need to do is mouth the words. Our device comes with a facemask design that patients can put on comfortably. We have also developed a complete protocol to train our machine learning algorithm in clinical settings using data from human volunteers. The technology also has potential for applications for individuals suffering from permanent speech loss due to throat cancers or surgeries. 

Novel containment solution for global vaccines  

Seonae Breckenridge, Paris Dickens, Anjola Solola

The COVID-19 pandemic disrupted the vaccine landscape, heightening the need for a global containment solution suitable for large-scale manufacturing and distribution of mRNA LNP vaccines at sub-zero temperatures. There is a substantial need to prevent disease, but there is still a global disparity in vaccine accessibility due to price and an area of opportunity for more sustainable containment solutions. Accounting for cost-effectiveness and global sustainability, we developed a novel and scalable containment and administration solution suitable for the sub-zero criteria of mRNA LNP vaccines.

Leveraging machine learning frameworks to automate acute care assessment in hospitals

Advait Mani, Nawal Panjwani, Cody Rougeux, Reuben Rosen

In clinical settings, nurses are tasked with performing examinations on medical-surgical patients to establish a neurological baseline, an iterative process that significantly hampers their workload. To alleviate this burden, we developed an automated system employing audio-visual monitoring. By leveraging Python and machine learning, the system discerns and records patient responses to the MOCA exam, pupillometry, and pronator drift test. By promptly detecting any deviations from the norm, the system ensures that medical intervention is administered in a timely manner. This solution streamlines acute care and refocuses nurses’ efforts on direct patient care, potentially transforming the standard of healthcare delivery.

Improving blood line draws 

Sofia Kashtelyan, Priyanka Seth, Purva Shenoy, Yuancheng (Kevin) Shao

Two hundred fifty thousand cases of central line-associated bloodstream infections (CLABSIs) are recorded annually, with many onset by frequent blood draws through a central line catheter. Each new case of CLABSI can cost upwards of $46,000 to treat, placing a large burden on patients and the healthcare system. In an effort to improve blood line draws, our literature search and customer discovery interviews have demonstrated that the current blood draw workflow is far too complex and time-consuming. This significant finding led us to hypothesize that workflow complexity results in inadequate sterilization of the central line, and thus may cause CLABSI. Through the iterative design process, our team has designed an ergonomic integrated system which drastically reduces workflow to improve sample quality and minimize the incidence of bloodstream infections in patients with a central line.

Novel craniosynostosis distractor system

Myles Wood, Ashmita Sivakumar, Marlee Pincus, Mackenzee Rosin, Ramya Lakshminarasimhan

Craniosynostosis is a condition in which the bones of the skull of an infant fuse too early and can lead to devastating complications if not treated. This condition is treated using a method called osteogenic which involves placing spacers between to help separate the fused skull bones. This method uses external rods to provide the force required for this treatment but because this treatment requires open wounds it leads to a risk of infection in up to 30% of patients. Our team was tasked with optimizing a design used to solve this problem, which uses magnets instead of external rods to provide the force required for osteogenic distraction. This solution eliminates the need for external rods and therefore reduces the risk of infection and morbidity associated with this condition.

Behavioral monitoring for small animals with diabetes 

Anica Huang, Shannya (Shay) Niveyro, Tianqi (Leo) Lu, Yuqian (Joe) Hu

Our mission is to improve diabetes monitoring for pets and their caretakers. After surveying 11 owners of diabetic cats and dogs, we learned that 45.5% are not satisfied with the current options for monitoring diabetes in their pets. To address this issue, we have partnered with Med Dimensions, a startup revolutionizing veterinary healthcare, to develop a novel method of monitoring diabetes. Together, we are creating a sensor system that monitors data related to blood sugar levels, including activity level and food and water consumption, and communicates this information with personal devices

Meniscus repair via sub-ablative radiofrequency tissue welding

Yuan Jiang

In the United States, approximately 60 meniscus tears per 100,000 people occur, and 17 meniscus repair surgeries are performed per 100,000 people. Currently, there are two ways to repair the meniscus extensively. One, suturing, carries the risk of infection. The other, removing the torn part with meniscectomy, damages the integrity of the meniscus and has a slow recovery. Our team is developing a technology that can apply radio frequency AC voltage at both ends of the tear and has made great progress so far. The conceptual prototype is currently able to fuse the meniscus tissue. More studies and progress needs to be made before moving to animal models and pre-clinical trials.

A voice and speech collection device 

Soobin Choi, Peculiar Lawrence, Jingyi Xu, Maham Zia 

“Audiomics” is an interdisciplinary field of audio analysis to identify voice biomarkers of disease; features in the voice signal associated with a clinical outcome that can give insight into patients’ health status. In this emerging field, there is a lack of emphasis on creating a high-quality data collection tool that securely stores patient data. Thus, our team developed a platform for standardizing high-quality data collection, indexable annotations, and encrypted storage. This platform consists of hardware and software components; a dual MEMs stereo-setup and a LabVIEW VI-based user interface with infographics and audio prompts to increase patient accessibility. 

AutoKnee IsoTester

Lex Crist, Sunita Devi, Anagha Gopinath, Jianying Peng

Knee laxity is a metric used to evaluate the stability of the knee, which can aid in diagnosis of ligament injuries and in rehabilitation after knee surgeries. To facilitate quantitative analysis and increase inter-examiner reliability compared to existing solutions, the Hospital for Special Surgery (HSS) is developing the KneeTester arthrometer to evaluate knee laxity in multiple degrees of freedom. To assist in this development, our team automated the flexion-extension testing of the knee using a motor in real-time. We developed a set-up manual, control algorithm, and safety system for our prototype that we hope will facilitate integration of the motor into the existing HSS system.

The design of a real-time monitoring system for hydrocephalus patients with ventriculoperitoneal shunts

Maria Santiago, Myles Wood, Kyle Zappi
Ventriculoperitoneal (VP) shunts are used to treat patients with hydrocephalus which is caused by a buildup of pressure and fluid in the subarachnoid space surrounding the brian. These shunts allow cerebrospinal fluid to drain from the brain cavity and help alleviate this build up of pressure. However, very often VP shunts can fail and thus it can be difficult for providers to diagnose. Because of this challenge, we have designed a device that is designed to integrate with currently available VP shunts to detect failure. Our device uses a flow sensor and pressure sensor to monitor the fluid dynamics within the VP shunt to allow clinicians to monitor these dynamics and determine when device failure has occurred.

Management of hydrocephalus through third ventriculostomy for pediatric patients

Pranav Sakre, Michelle Barth, Xu Lian, Rutika Gavate, Kyle Zappi
Hydrocephalus is a condition in which cerebrospinal fluid builds up inside the brain, reducing the quality of life of pediatric patients. The current treatment option is an invasive surgery with a high mortality rate due to the likelihood of damaging important structures in the brain. To improve outcomes for these pediatric patients, we have developed a solution that integrates ultrasound imaging to provide real-time feedback to surgeons and a novel mechanical solution that provides a clean, uniform cut, minimizing the risk of damage to underlying structures and preventing occlusion, and thereby increasing the safety and efficacy of the procedure. 

Intravaginal neural stimulation device for acute and chronic pelvic pain 

Yaa Achampong, Angelina Fahrenkrug, Yiwei (Claire) Feng, Ana Grandgeorge

Our proposed intravaginal electrical stimulation device is a revolutionary device for patients experiencing chronic pelvic pain and endometriosis, conditions that significantly affect the quality of life of many individuals. However, current treatment options are limited. We developed a solution based on literature reviews, patient surveys and collaborations with healthcare professionals at Weill Cornell Medicine. Our device offers a non-pharmacological treatment option, reducing the reliance on medications like opioids. The device will utilize controlled electrical impulses to modulate nerve activity, thereby alleviating pain and discomfort. Further research and experimentation are needed to validate device effectiveness and safety, ensuring it meets regulatory standards and provides a viable alternative for patients.

Refluxible: A real-time pH monitoring device for gastroesophageal reflux (GER)

Kaelyn Gaza, Mingyang Huang, Joshua Turner, Veronica Vila

Infant gastroesophageal reflux (GER) is a common condition affecting up to 50% of infants, characterized by the backflow of stomach contents into the esophagus. While most infants outgrow GER by their first year, severe cases (known as GERD) can impact a child’s development and health. To address the limitations in currently available diagnosing and monitoring tools, we have developed a pacifier capable of testing spit-up using the infant’s natural sucking motions. The collected fluid interacts with a sensor suite located at the back of the pacifier, providing accurate and continuous readings. Our approach offers a low-effort way to collect accurate reflux data, easing parental burdens and improving infant health.

Minimizing surgical dead space via tissue adhesion device 

Maria Dobransky, Ganga Dripaul, Shayona Gupta, Silene Reyes, Emma Taigounov

Plastic and reconstructive surgery play vital roles in restoring tissue form and function to individuals impacted by trauma, disease, or congenital malformations. Our project aims to investigate challenges regarding anatomical dead space formation in patients post-surgery. Dead space is referred to as empty spaces formed between two layers of tissue that often accumulate fluid as a response to trauma and, as a result, lead to impaired tissue function, and potentially infection. To combat this issue, we formulated multiple designs to develop a novel device that can effectively promote tissue adhesion while simultaneously minimizing the prevalence of dead space in patients post-surgery.

Centrifuge and habitat system to study the effects of altered gravity on neurodegeneration

Angelique Jan Miane, Baisampayan Moitra, Phyo Pyae Sone, Rishi Pothakamuri
Space exploration poses unique challenges to human health, potentially disrupting protein clearance mechanisms, cerebrospinal fluid dynamics and volume regulation under altered gravity conditions. Our study aims to address these intricate issues by developing a modular centrifuge system coupled with animal testing to investigate hypergravity’s effects on the aforementioned factors. The team engineered a long-arm centrifuge and animal habitation module capable of sustaining variable forces for at least four simultaneous modules. The centrifuge design integrates advanced features, including a hub motor, T-slotted aluminum railings and habitat modules with environmental sensors and video feeds. Key objectives involve providing controlled artificial gravity up to 4G and ensuring continuous operation for up to eight weeks.

Cannulation system for pediatric mechanical circulatory support 

Rachel Bocian, Samantha Symons, Xiaoze Yang, and Zimu Zhou
Congenital heart defects (CHD) are structural heart abnormalities present at birth. Annually in the U.S., 40,000 pediatric patients are born with CHD, with 25% requiring invasive treatment in their first year, including transplantation or mechanical circulatory support (MCS). As the most common MCS, a ventricle assist device (VAD) alleviates the issue of donor shortage by extending a patient’s life for an available transplant. However, at the pediatric level, small device size and difficulty of placement regularly cause clotting, ischemic strokes and neurological dysfunction. PediaCannula is a revolutionary VAD-compatible cannulation system that grows with the patient with guiding technology, satisfying the increasing flow requirement and ensuring the accurate device placement to minimize the risk of functional complications.

Individual Research Projects

Simulation of bioluminescence neural recordings

Saud Mahmoud Alfakhri (advised by Nozomi Nishimura)

Experimental analysis of lymphatic function in valvular endothelium

Anukriti Dey (advised by Jonathan Butcher)

Dynamical systems modeling of DSL-notch specificity in oscillatory signal transduction

Lakshmi Venkata Saran Karuturi (advised by Benjamin Cosgrove)

Development of Lipid Nanoparticle Enhance Vaccine Endosomal Escape to Combat Melanoma

Yufei Ma (advised by Shaoyi Jiang)

Quantifying mouse behavior in a strategic game via Q-learning algorithms

Jiayin Qu (advised by Alex Kwan)

Development of mRNA lipid nanoparticles for cancer vaccines

Jialiang Rachel Wang (advised by Shaoyi Jiang)

New type of shimming coil for the MRI imaging

Yuhui Xu (advised by Yi Wang)

Quantitative analysis of lymphatic phenotype in healthy and diseased aortic valves

Jiahao Zhang (advised by Jonathan Butcher)