Experience

Aloft Sensing, Inc.

• United States
• Defense and Space Manufacturing
• 1 - 100 Employee

• Senior Research Engineer

  • Feb 2023 - Present

  Ann Arbor, Michigan, United States



Cornell University

• United States
• Higher Education
• 700 & Above Employee

• Postdoctoral Associate

  • Aug 2020 - Jan 2023

  a) Permanent Scatterer Interferometry (PSI) and InSAR analysis • Project: PSI and InSAR analysis using Sentinel-1 and TerraSAR-X data for mapping and monitoring surface displacements in Ithaca, and Cayuga lake area (New York) due to underground salt mining. b) InSAR algorithm development and processing. • Project: Pattern-based InSAR phase unwrapping approach. A pattern-based strategy was developed for unwrapping interferometric phases over landslides where current… Show more a) Permanent Scatterer Interferometry (PSI) and InSAR analysis • Project: PSI and InSAR analysis using Sentinel-1 and TerraSAR-X data for mapping and monitoring surface displacements in Ithaca, and Cayuga lake area (New York) due to underground salt mining. b) InSAR algorithm development and processing. • Project: Pattern-based InSAR phase unwrapping approach. A pattern-based strategy was developed for unwrapping interferometric phases over landslides where current unwrapping methods fail due to fast deformation rates. The algorithm was tested using ALOS-1 PALSAR-derived simulated data and actual UAVSAR data over Slumgullion landslide and was proved to be successful in unwrapping interferograms with very fast deformation rates (Molan and Lohman, 2021). - Funding: The NASA grant NNX16AK57G and 80NSSC19K1496. c) InSAR time series algorithm development and processing. • Project: Augmentation of InSAR time series analysis with SAR intensity and optical data. Developing a new approach to improve deformation time series using optical images and SAR intensity information. A proposal was submitted to NASA ROSES-2021. d) Algorithm development for soil moisture estimation in vegetated areas. • Project: Developing statistical and machine learning soil moisture models using ground measurements, SAR data, and optical images in SMAPVEX12 Cal/Val site. Show less



Southern Methodist University

• United States
• Higher Education
• 700 & Above Employee

• Postdoctoral Fellow

  • Jun 2020 - Jul 2020

  Dallas, Texas, United States - NASA's NISAR dithered product comparison Comparing the phase and amplitude of non-dithered data (CX), dithered with the gaps in the data (CG), and dithered without gaps in the data (CD) of UAVSAR AM/PM project.

• Research And Teaching Assistant

  • Aug 2015 - May 2020

  Dallas/Fort Worth Area a) Algorithm development for decorrelation analysis and modeling. • 434 NISAR Ecosystems ALOS2 Scenes were used to model InSAR coherence as a function of SAR intensity changes and snow depth changes (Molan et al., 2018a) - Funding: The NASA Earth Surface & Interior Program, grant number NNX16AK56G b) Algorithm development for modeling the statistical properties of multi-looked pixels. • The influence of the statistical properties of single-looked pixels’ phase and… Show more a) Algorithm development for decorrelation analysis and modeling. • 434 NISAR Ecosystems ALOS2 Scenes were used to model InSAR coherence as a function of SAR intensity changes and snow depth changes (Molan et al., 2018a) - Funding: The NASA Earth Surface & Interior Program, grant number NNX16AK56G b) Algorithm development for modeling the statistical properties of multi-looked pixels. • The influence of the statistical properties of single-looked pixels’ phase and intensity on multi-looked InSAR phase, coherence, and closure phase is modeled. The algorithm was evaluated exploiting C-band and L-band simulated and actual SAR data over different landcover types (Molan et al., 2020, Molan and Lu, 2020a). - Funding: The NASA Earth Surface & Interior Program: NISAR Science Team, grant numbers 80NSSC19K1491, and NNX16AK56G c) Algorithm development for modeling InSAR phase and SAR intensity. • InSAR phase and SAR intensity changes induced by soil moisture and soil structure were modeled and evaluated using real SAR data and ground measurements (Molan and Lu, 2020b) - Funding: The NASA Earth Surface & Interior Program, grant numbers 80NSSC19K1491, NNX16AK56G d) InSAR processing and algorithm development for deformation modeling. • Ground surface deformation associated with permafrost degradation in Alaska was mapped, modeled, and evaluated using ground truth data (e.g., Molan et al., 2018b) - Funding: The NASA Earth and Surface Interior Program, grant number NNX16AK56G; U.S. Geological Survey, grant number G14AC00153 e) Algorithm development for analyzing soil moisture-induced changes using polarimetric data. • UAVSAR polarimetric (HH, VV, and HV) InSAR phase, and SAR intensity were used to statistically model the influence of soil moisture on InSAR phase over vegetated areas in Arkansas.



Sahand University of Technology

• Iran
• Higher Education
• 1 - 100 Employee

• Faculty Member

  • May 2010 - Jul 2015

  Tabriz, Iran Research in remote sensing: a) Algorithm development for hyper-spectral remote sensing data analysis. • New approaches, i.e., “virtual verification” and “moving thresholding”, for evaluation the results of optical image were introduced, and algorithms were developed to implement the new approaches (Molan et., 2014) - Funding: Geological Survey of Iran (GSI) b) GIS, and geospatial data analysis for geological mapping. • Developed a new GIS-based knowledge-driven… Show more Research in remote sensing: a) Algorithm development for hyper-spectral remote sensing data analysis. • New approaches, i.e., “virtual verification” and “moving thresholding”, for evaluation the results of optical image were introduced, and algorithms were developed to implement the new approaches (Molan et., 2014) - Funding: Geological Survey of Iran (GSI) b) GIS, and geospatial data analysis for geological mapping. • Developed a new GIS-based knowledge-driven exploration model for mineral potential mapping using remote sensing-driven images (Molan and Behnia 2013) - Funding: Madan-Karan Angouran Company (MKAC) c) Algorithm development for light reflectance on rough surfaces. • Developed a novel 3D Bidirectional Reflectance Distribution Function (BRDF) model for rough surfaces. Algorithms in IDL and Maple were created to develop the model and generate the results (Kalantari and Molan, 2016) Courses Taught: Computer Methods, Geology, Geotechnics (Soil Mechanics), Mathematics Show less



Geological Survey of Iran

• Iran
• Information Services
• 1 - 100 Employee

• Remote Sensing Data Scientist

  • Mar 2009 - May 2010

  Tehran a. Algorithm development and optical remote sensing data processing for environmental mapping, geological mapping, and lithological classification, and identification. b. Algorithm development for calibration, preprocessing, and processing of multi-spectral and hyper-spectral remote sensing data. c. Algorithm development for spectral analysis using HyMAP airborne hyper-spectral data. d. Geospatial data analysis and generating mineral exploration maps using optical data for… Show more a. Algorithm development and optical remote sensing data processing for environmental mapping, geological mapping, and lithological classification, and identification. b. Algorithm development for calibration, preprocessing, and processing of multi-spectral and hyper-spectral remote sensing data. c. Algorithm development for spectral analysis using HyMAP airborne hyper-spectral data. d. Geospatial data analysis and generating mineral exploration maps using optical data for mining and geology companies. Show less



Madan Karan Angouran Company

• Remote Sensing Data Analyst

  • Jul 2007 - Sep 2009

  Zanjan, Iran - Optical remote sensing data processing for mineral mapping, lithological classification, and identification of geological structures and features. - Geospatial data analysis and generating mineral potential maps (exploration maps) in GIS environment using optical data products.