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nadirkhan83 Online Offline
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send events/properties to a proprietary API - FOR NADIRKHAN83 only!
“Great work - as always!”bbwalldorf 2 years ago.
Application event-reporting to proprietary API - part 2
“Always a pleasure to work with Nadir. Will definitely hire him again!”bbwalldorf 2 years ago.
OCR application of android
“Speedy delivery and good quality.”mamromer 2 years ago.
Rebuild image filter to android
“Delivered everything as discussed within time. Very professional work.”mamromer 2 years ago.
Neural Network system aids
“Excellent work with great understanding for the job / project requirement. Outstanding quality work and meet the objective of the project with good work ethic. Well done and looking forward to work with again in the future.”dj1228 2 years ago.
Application event-reporting to proprietary API
“Very professional coder. Nadir understood the challenge, asked the right questions and delivered superb code way ahead of schedule!”bbwalldorf 2 years ago.
Senior Software EngineerApr 2011
o Initially, worked on piping design and simulation software, AutoPIPE. Worked on exporting to a DGN file format (Bentley common file format), and later worked on GUI enhancement tasks. o Currently, working on offshore structural design and analysis software, SACS. Working on adding extra GUI features and consolidation of legacy FORTRAN-based modules.
Software EngineerJan 2007 - Dec 2010 (3 years)
o Optimized and refactored (for performance/speed) the Moldflow 3D Flow Analysis Solver application. o Optimized and refactored (for performance/speed) the Moldflow Midplane/Dual Domain Flow Analysis Solver application. o Optimized (for quality) the tetrahedral mesh generator algorithm. o Adopted the Ribbon UI look (as in MS Office 2007) for Moldflow products. o Integrated easy-to-use, 3rd party graphics-view manipulation tools into Moldflow products. o Integrated the Customer Involvement Program (CIP)
B.S. in Computer Systems Engineering2001 - 2005 (4 years)
Master of Computer Science [Minor Thesis]2006 - 2008 (2 years)
Online Urdu Ligature Recognition using Spatial Temporal Neural Processing
A scientific recognition of Urdu handwriting using computer-generated features of online sample handwriting is presented in this paper. Handwriting samples are taken through digitalized tablet, and digitized for processing on a computer. Measures (features) are extracted on the handwriting samples at the space and time level. We utilize newly developed spatio-temporal artificial neuron (STAN) to classify spatio-temporal patterns (STPs) present in handwriting. This neuron is embedded in ordinary artificial n
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