Research engineer specializing in materials characterization, aerospace systems, and AI-assisted analysis. New York University graduate, AMBER Lab researcher contributing to the Emirates Lunar Mission.
I'm a recent Mechanical Engineering graduate from New York University (May 2026, Full Merit Scholarship), currently working as a researcher at the AMBER Lab under Prof. Kemal Celik.
My research centers on µCT-based microstructural analysis of cementitious materials and lunar regolith simulants, with work affiliated with the Emirates Lunar Mission (MBRSC). I build ML pipelines for image segmentation and run physical testing under space-simulated conditions.
Outside the lab, I founded UrbanNerve — an AI-assisted emergency coordination platform — and led the Falcon Aerospace Engineering Club. I believe research credibility and entrepreneurial execution are two sides of the same coin.
Targeting graduate school (Fall 2027) in materials engineering or aerospace, with a long-term goal in AI-assisted materials diagnostics and smart infrastructure inspection.
Characterizing lunar regolith simulant samples affiliated with the Emirates Lunar Mission (MBRSC). µCT-based volumetric analysis of particle morphology, void fraction, and pore structure — contributing materials validation data to the mission pipeline.
Developing a novel multi-method segmentation comparison framework — manual thresholding vs. Multi-Otsu vs. ML-based — for particle size and morphology analysis of LHS-1 lunar simulant. Manuscript in preparation targeting Powder Technology (Elsevier).
Designed and deployed a deep learning segmentation pipeline (U-Net, FCN) on NYUAD's Jubail HPC cluster. Achieved 93% accuracy on a 500,000-image µCT dataset — enabling 3D microstructural reconstruction of cracks, pore growth, and void evolution.
Morphological analysis of OPC cement paste µCT data across 25–1000°C thermal cycles. Quantified pore coarsening, porosity evolution (0.17–0.18%), and microcrack growth. Combined with TGA/DTG and XRD for full materials characterization suite.
Engineered electrospun PTFE membranes and used deep learning on SEM images and XRD data to characterize pore morphology and crystalline behavior. Optimized performance for nanofiltration (NF) and reverse osmosis (RO) applications.
Used high-fidelity Large Eddy Simulations (LES) to investigate thermochemical mixing properties of fluid elements contacting an electronically activated glow plug structure, simulating fuel-air mixing enhancement and combustion dynamics.
Led a 12-member team engineering a human-powered Martian rover from concept to race-ready prototype at NASA Marshall Space Flight Center. 21% weight reduction, SF > 2.0, 100% mission task completion. Awarded Best Technical Innovation.
Battery-electric five-rotor VTOL aircraft for remote clinic pharmaceutical delivery. Blade-element momentum theory + ANSYS Fluent CFD, honeycomb sandwich panel fuselage, autonomous ROS2/PX4 flight stack. 12% lift-to-drag improvement.
View on GitHubFull-stack AI-assisted emergency dispatch platform. React/Node.js web app deployed live, React Native mobile app (Android), real-time GPS tracking, SOS flow, and ETA prediction. Piloted in real-world conditions with structured bug logging.
Visit urbannerve.orgPeer-reviewed research on the socioeconomic impact of automation in Bangladesh's garment industry. Presented at the International Conference on Global Social Science, Berlin, August 2025. Co-authored with Prof. Nancy Gleason.
Read PaperOpen to research collaborations, internship opportunities, and grad school conversations. Open to opportunities worldwide.
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