Research
Research, in all forms, scratches my brain in the best way. I have had the opportunity to explore unique problems and contribute to novel solutions, and you can find some of what I’ve worked on below.
Bioelectronic fabric for whole organ modulation
Bioelectronics Group, MIT
Bioelectronics, Neuroengineering, Medical Devices, Optogenetics
The Bioelectronics Lab has pioneered the use of thermally drawn multifunctional fibers to interface with point populations of neurons in the brain. This project aimed to apply that technology to the gastrointestinal tract (GIT), which houses the enteric nervous system (ENS) and is particularly interesting for neural recording and stimulation experiments. Tissue is soft and dynamic in nature, so a neural interface device has to be: a) soft and flexible enough to not cause organ damage and scarring, b) functionalized with electrodes and LEDs along a two-dimensional surface, c) manufactured in a highly versatile approach that enables scalability and flexible shape configurations. These would allow for non-damaging stimulation of neurons involved in digestion and satiety. I focused on developing the fibers that make up the fabric, aiming to optogenetically modulate specific neural activity via stretch neurons in the GIT, which are connected to brain satiety centers through the gut-brain axis..
I spent a lot of time troubleshooting and iterating to figure out what worked best, and over time, some of the fibers I made were used in experiments to test stimulation setups and refine the design. It was a mix of mechanical, electrical, and biological work, and I got to work fairly independently after the first few months, which helped me get comfortable moving between tools, protocols, and ideas in the lab setting.
This was my introduction to academic research, so it holds a special place in my memory. I became comfortable using protocols and learned how to think through technical problems with a medical goal in mind. Looking back, this was where I started to see how engineering and medicine overlapped. I’m especially grateful to Rajib Mondal and Prof. Polina Anikeeva for their guidance and support.
The fiber (lit, and unlit), wrapped around a mouse stomach model
An early depiction of the fiber,
under microscope
Real-time monitoring of recombinant carbonic anhydrase for optimized CO2 capture in bioreactor systems
Biotechnology Process Engineering Center, MIT
Bioprocess Engineering, Sustainable Chemical Engineering, Sensor Integration, Lab Automation
This project focuses on enabling real-time monitoring of recombinant carbonic anhydrase (rCA), an enzyme used in CO₂ capture systems. Enzyme-based approaches to CO₂ capture are often limited by production cost and process instability, so improving upstream control during fermentation is useful for the yield, consistency, and scalability of the entire workflow. CA accelerates the conversion of CO₂ to bicarbonate, which is especially useful for mineral carbonation processes, and therefore has applications in cement production, soil treatment, and carbon sequestration. So, the project aims to support carbon reduction and sustainable carbon sourcing.
My work centered on integrating a GFP-linked fluorescence sensor into our fermentation workflow, using GFP as a proxy for rCA expression. The rCA used in our system was recombinantly expressed as a fusion protein with GFP, which allowed me to track production in real time via the sensor without relying on post-hoc assays. I began by first calibrating the CST PX2+ fluorescence sensor using purified GFP standards, then moved on to develop a more realistic calibration method using culture-based dilutions to account for optical noise present in the culture during fermentation. These refinements made the sensor increasingly viable for real-time use inside a live bioreactor environment. Once calibrated, I ran a series of fermentation experiments using GFP-expressing auto-induction strains and tested different conditions (culture density, mixing speed, probe positioning) to assess how the sensor responded under realistic growth dynamics, aiming to produce a reliable signal that could track GFP expression trends with enough resolution to inform fermentation optimization decisions.
To extend the system’s usefulness beyond manual monitoring, we began collaborating with a startup focused on lab automation and bioreactor integration. We discussed how to progress the project towards a feedback-driven control system that would allow the sensor to both observe enzyme production in real time and actively modulate process parameters (i.e. temperature, media flow rate) to optimize yield with minimal human intervention. Having built a system that measures expression dynamics in real time, this begins setting the stage for adaptive control and scalability, which is a step toward a plug-and-play solution for industrial bio-manufacturing.
An example of a 1.5L bioreactor experimental run