Cornell University · Jiang Laboratory

Engineering polymer networks for biological systems.

I’m Aayam Dhakal, an MS Chemical Engineering researcher at Cornell working at the interface of polymer science and biomaterials. I design zwitterionic hydrogel systems for extracellular vesicle preservation and stem-cell microenvironments.

Current degreeMS Chemical Engineering
Research focusHydrogels · EVs · HSPCs
LocationIthaca, New York
Portrait of Aayam Dhakal
MS Chemical Engineering · Cornell University Jiang Laboratory · Zwitterionic biomaterials
Research lensFrom molecular design to biological function.
01ChemistryZwitterionic & thermoresponsive polymers
02Network architecturePorosity · crosslinking · mechanics
03BiofunctionEV preservation · HSPC microenvironments

01 · Research

Research at the interface of polymer science and biology.

I study how chemistry, network architecture, transport, and mechanics can be tuned to preserve biological function and create controlled cellular microenvironments.

01

Extracellular vesicle preservation

Porous zwitterionic hydrogels for EV capture and room-temperature preservation.

I engineer porous zwitterionic matrices and study how pore architecture and transport influence EV loading, recovery, structural integrity, and biological functionality during storage and release.

Design variablesPorosity · transport · hydrogel chemistry
Biological systemExtracellular vesicles
02

Stem-cell microenvironments

Thermoresponsive zwitterionic hydrogels for CD34+ HSPC expansion.

I am developing PNIPAAm–poly(carboxybetaine)–PNIPAAm triblock copolymer hydrogels as ultralow-fouling 3D matrices, tuning polymer composition, physical crosslinking, stiffness, and viscoelasticity to support primitive HSPC phenotypes.

Polymer architecturePNIPAAm–PCB–PNIPAAm
Cell systemCD34+ hematopoietic stem & progenitor cells
Interactive transition

Drag the temperature slider to follow polymer association and formation of a physically crosslinked 3D gel.

20°C37°C
20°Cpolymer solution
solution3D gel
03

Computational chemical engineering

Machine learning for chemical processes, drug-property prediction, and environmental data.

Before moving into biomaterials, I worked across process systems and applied machine learning. Select a project to explore the technical workflow.

01
Feedforward neural network for benzene–toluene distillationOperating variables → separation behavior → FNN surrogate model
BENZENE–TOLUENE COLUMN PROCESS VARIABLES FEEDFORWARD NEURAL NETWORK
A chemical-process modeling workflow centered on benzene–toluene separation, using process variables and simulated separation behavior to train a feedforward neural-network representation of the system.
SystemBenzene–toluene distillationModelFeedforward neural networkPurposeProcess modeling & optimization
02
Aqueous solubility prediction for drug-like compounds and candidate APIsMolecular structure → descriptors → gradient-boosted models
DRUG-LIKE STRUCTURE MOLECULAR DESCRIPTORS LIGHTGBM / XGBOOST
A cheminformatics workflow for aqueous-solubility prediction, transforming chemical structure into machine-readable descriptors and using LightGBM and XGBoost for drug-development and pre-formulation screening.
PropertyAqueous solubilityContextDrug-like compounds / candidate APIsModelsLightGBM · XGBoost
03
Ground-sampling and satellite-assisted PM₂.₅ estimationParticulate sampling + remote sensing → machine-learning estimation
SATELLITE OBSERVATIONS GROUND SAMPLING ML MODEL PM₂.₅ SPATIAL ESTIMATE
An environmental data-integration workflow combining particulate-matter sampling, black-carbon related analysis, and satellite observations to estimate ground-level PM₂.₅ patterns.
TargetGround-level PM₂.₅InputsSampling · satellite observationsPurposeSpatial air-quality estimation

02 · Research trajectory

A progression from process systems to biointerfaces.

My research path has moved from process modeling and environmental data toward polymeric biomaterials, while keeping the same engineering emphasis on structure, transport, and measurable function.

2023–24
Pulchowk Campus

Computational chemical engineering

Feedforward neural-network modeling of benzene–toluene distillation and machine learning for aqueous-solubility prediction of drug-like compounds.

2024–25
Kathmandu Institute of Applied Sciences

Air quality & environmental modeling

Particulate-matter sampling, black-carbon related analysis, satellite observations, and data-driven air-quality estimation.

2025
Cornell University

Transition into biomaterials

Graduate research in the Jiang Laboratory focused on zwitterionic interfaces, polymer synthesis, and soft-material design.

Now
Jiang Laboratory

Hydrogels for EVs and stem cells

Engineering porous and thermoresponsive networks for preservation, transport, and control of cellular microenvironments.

03 · Publications

Peer-reviewed work.

01
International Journal of Energy and Water Resources · 2025

Physio-chemical analysis of water from different altitudes of Kathmandu Valley, Nepal.

Mahara, P., Paudel, Y., Chaudhary, P., Gaihre, S., Dhakal, A., & Pandey, B.

DOI ↗

04 · Engineering practice

Professional experience beyond the research lab.

Industry roles in quality systems, production engineering, and plant operations shaped how I approach experimental rigor, process variability, and engineering decisions.

Aug 2024 — Aug 2025

Sahas Multipurpose Pvt. Ltd. · Kathmandu, Nepal

Quality Assurance & Quality Control Manager

Developed and implemented water-quality protocols for local distribution and international export, supported PRP, OPRP, and HACCP compliance, and coordinated QA audits with production and distribution teams.

25% fewer internal-audit non-conformities15% improvement in on-time delivery
May 2024 — Jul 2024

First Choice Food Pvt. Ltd. · Rupandehi, Nepal

Production Engineering Intern

Worked on fryer operation and CIP scheduling, using process data and temperature and downtime analysis to improve production consistency and yield.

5% reduction in off-spec production~3% increase in process yield
Oct 2023 — Dec 2023

Varun Beverage Limited · Kathmandu, Nepal

Quality Assurance Engineering Intern

Analyzed production data, supported in-line quality reporting, performed packaging and product quality tests, and gained exposure to cooling, syrup preparation, and beverage manufacturing operations.

21% faster response to equipment failures and breakages

05 · Methods & capabilities

Methods spanning polymer synthesis, biointerfaces, and computation.

Synthesis

ATRP
RAFT
Photopolymerization
Hydrogel fabrication
Lyophilization

Characterization

NMR
Rheology
GPC
SEM
DLS / NTA
LC–MS

Biological

2D cell culture
3D cell culture
EV handling
Biomaterial interfaces

Computational

Python
scikit-learn
TensorFlow / PyTorch
MATLAB
Aspen Plus

06 · Contact

Research conversations & collaborations.

I’m interested in connecting with researchers working in polymeric biomaterials, hydrogel engineering, extracellular vesicles, stem-cell microenvironments, and related areas.