Sep 2018 – Sep 2023 · 5 yrs · On-site

• Automated and compact fuel sensor
• Researched and developed a spectroscopy-based miniaturized IR sensor for prediction of “Derived cetane number” for Army relevant fuels using machine learning techniques.
• Created a spectroscopic database on MySQL by collecting IR absorption spectra of Jet fuels, neat hydrocarbons and their mixtures representing the key chemical functional groups present in the Army relevant fuels using FTIR and Raman spectroscopy.
• Developed a methodology for training machine learning models on neat liquid phase IR absorption data by avoiding the regions of saturation achieving prediction accuracy of 93.1% and mean percentage error of 3% using CNN model.
• Fabricated a narrow path length (<10µm) liquid flow cell for avoiding saturation using lithographic techniques with joint effort with Nano Core Facility at UIC.
• Constructed a spectral deconvolution methodology and chemometric model for predicting chemical functional group composition present in the hydrocarbon fuels using FT-ATR absorption spectroscopy, further used correlation for physiochemical properties.
• Investigated the use of narrow IR spectral ranges (<300cm-1) in collaboration with the University of Wisconsin Madison, in characterization of Army relevant fuels. IR region between 2700 – 2990 cm-1 found most useful in DCN prediction with R2=0.925.
• Built a customized, automated and miniaturized inline dispersive NIR fuel sensor for real time DCN prediction.
• Mentored and trained 6 UG students in chemical handling, data acquisition, and development of predictive ML models.

Apr 2018 – Sep 2023 · 5 yrs 5 mos · On-site

• High pressure high flow rate flow mixing apparatus.
• Designed and constructed an automated, portable, high pressure, high flow rate mixing apparatus for rapid, precise mixing of multiple gases and vapors suitable for supplying test mixtures to high through experimental devices like MISR saving hours of mixture preparation time.
• Gas sampled mixtures over multiple cycles were found to be highly repeatability, accurate and stable using GC/MS.
• Time resolved formaldehyde measurement in shock tube and gas cell for line strength and GC calibration.
• Developed a methodology to generate vapor phase formaldehyde using 1,3,5 trioxane precursor for accurate GC calibration.
• Designed and fabricated the optical window section to perform laser diagnosis on Low-pressure shock tube at UIC.
• Performed laser absorption experiments for line strength calibration of formaldehyde near 2814cm-1 using heated gas cell.
• Validating the experimental and simulated absorption profiles developed using Hitran data with GC/MS results for line strength and pressure broadening uncertainties.
• Miniaturized Ignition Screening Rapid Compression Machine (MISR)
• Helped in design, development, and assembly of MISR apparatus at UIC and successfully performed initial trials.
• Performed signal processing after noise filtration of high speed LVDT data to calculate ‘ms’ time response characterization of compression cycle using custom written Python codes to simulate and validate experimental data with model.
• Performed ignition delay experiments with high-speed imaging and OH* chemiluminescence for ethanol and n-heptane.
• Other projects
• Designed and fabricated a customized US/VIS/NIR range dispersive spectrometer with 0.01nm resolution capability.

Dec 2015 – May 2016 · 5 mos · Bengaluru, Karnataka, India · On-site

• Supervised two production lines of PepsiCo’s largest manufacturing plant in India.
• Responsible for handling planned Machine maintenance, productivity enhancement, measures for cost effectiveness, quick resolving of production run issues, root cause analysis, quality management in all stations and stages of the process.