Machine Learning Computer Vision

ABDUL ADEEL MOHAMMED

**** ****** ***

Windsor, ON, N9B 0B6

Tel: 519-***-****

*****.********@*****.**

PROFESSIONAL SUMMARY

I have 15 years of research and development experience in image processing, computer vision, machine learning, artificial intelligence, sensor fusion and their application in robotics and Advance Driver Assistance Systems (ADAS). RESEARCH INTERESTS

Autonomous system, estimation and detection problems, image and video processing, computer vision, machine learning, multi-modal sensor fusion, human factor analysis, HCI development and embedded hardware development

(inc. compliance to ISO26262, and SOTIF requirements). TECHNICAL SKILLS

• C / C++, Matlab/Simulink, Python.

• Experience with open-source tools / software: OPENCV and OPENGL

• Familiarity with ARM Cortex embedded processors.

• Knowledge of CAN, LIN and Ethernet network protocols.

• Experience with CAN tools and CAPL scripting.

• Excellent technical writing and communication skills. EDUCATION

• Doctor of Philosophy (Ph.D.), Electrical Engineering, University of Windsor, Canada, 2010.

• Master of Applied Science, Electrical and Computer Engineering, Ryerson University, Canada, 2005.

• Bachelor of Engineering, Electronics and Communication Engineering, Osmania University, India, 2001. DISSERTATION & THESIS

• Abdul Adeel Mohammed, Biometric Applications based on Multiresolution Analysis Tools, Doctorate Dissertation, Department of Electrical Engineering, University of Windsor, Windsor, ON, Canada, 2010.

• Abdul Adeel Mohammed, Wavelet Based Image Compression using Mathematical Morphology and Self- Organizing Feature Map, master’s degree Thesis, Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON, Canada, 2005.

PROFESSIONAL EXPERIENCE

MOBIS TECHNICAL CENTER OF NORTH AMERICA, PLYMOUTH, USA 2019 – 2024 Senior Research Engineer in Autonomous Vehicle Advanced Engineering (AVAE)

• Research and development of solutions to detect Alcohol based driver impairment using multi modal sensing set(s). Some of the solutions explored for alcohol impairment detection includes In-cabin camera, steering column angle / torque information, and vehicle CAN data.

• Development of driver distraction / drowsiness detection for GSR compliance in EU region.

• System development for Driver monitoring, In-Cabin monitoring, Occupant detection, Gesture recognition using eye, lips, face, head, and other driver metrics for commercial and non-commercial vehicle environments.

• Analysis and study of safety regulations pertaining to In-Cabin monitoring (Driver distraction, inattention, impairment, etc.) from GSR, Euro NCAP, NHTSA, USNCAP, other State and Federal agencies.

• Additional projects include development of SAE L2-3 ADAS systems using camera, radar and lidar sensing technologies.

• Development of system, software, and architecture requirements, planning and decision-making modules for L3

-L4 ADAS using all external sensing modalities.

FIAT CHRYSLER AUTOMOBILE USA LLC, AUBURN HILLS, USA 2016 – 2019 Automated Driving Engineer in Advanced Driver Assistance Systems (ADAS)

• Involved in projects related to ADAS systems using various sensing technologies, i.e., camera, radar and ultrasonic sensors.

• Projects include surround view and rearview camera systems, autonomous emergency braking, driver monitoring, free space estimation, object detection and classification, automated parking, lane keep assist and emergency lane keep assist, pedestrian / bicyclist emergency braking and other Euro NCAP mandated features.

• Lead advanced development and production intent projects for various vehicle platforms with different Tier 1 suppliers.

• Conducted tests for pedestrian/bicyclist emergency braking, lane keeping and other Euro NCAP mandated protocols at CSI Automotive (Milan, Italy).

• Participated in a training session at IIHS testing facility in Ruckersville, VA. COLLEGE OF COMPUTER AND INFORMATION SCIENCE, AL IMAM MUHAMMAD IBN SAUD ISLAMIC UNIVERSITY, RIYADH, KINGDOM OF SAUDI ARABIA 2012-2014

Assistant Professor in Computer Science Department

• Courses Taught

o CS 106 – Digital Logic, Fall 2013 / Spring 2014. o CS 221 – Computer Architecture, Spring 2012/ Fall 2012/ Spring 2013. o CS 224 – Computer Organization, Spring 2013.

o CS 242 – Data Structures, Fall 2012.

o CS 340 – Artificial Intelligence, Fall 2012/Spring 2014. o CS 430 – Mobile Communication Networks, Spring 2012.

• Funded Research Projects:

o Context-aware Facial Expression Analysis for the Development of Socially Assistive Robots (Principal Investigator, October 2012 – March 2014)

o Study and Implementation of IEEE 802.11 based Wireless Ad hoc Networks (Co-Investigator, October 2012 – October 2013)

DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING, UNIVERSITY OF WATERLOO, CANADA 2010-2011 Post-Doctoral Fellow, DISCOVER project researcher/coordinator with the Centre for Pattern Analysis and Machine Intelligence.

Advisor: Dr. M. S. Kamel, Co-advisors: Dr. F. Karray and Dr. O. Basir.

• Supervised a team of three engineers (PhD degree candidates) to simultaneously work on various tasks associated with the DISCOVER project.

• Development of a closed-loop surveillance system that optimally combines sensing and data fusion using a pervasive multi-modal surveillance system.

• A novel approach that enables fusion of soft (human generated) data along with conventional hard (electronic sensor based) data within the random set theoretic framework was implemented.

• Cooperative object detection and tracking module for head motion tracking using a coarse-to-fine particle filter was developed.

• A distributed constrained optimization problem modeling was proposed to overcome target allocation crisis in sensor networks.

DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING, UNIVERSITY OF WINDSOR, CANADA 2006-2010 Research Assistant, PhD. Candidate, Computer Vision and Sensing Systems (CVSS) Group. Advisor: Dr. Q.M. Jonathan Wu, Co-advisor: Dr. Maher A. Sid-Ahmed. Research projects include:

• Human Face Recognition System

o Highly discriminative feature computation through exploitation of curve singularities in higher dimensional space.

o Non-linear subspace projection for improved feature discrimination. o Extreme learning machine for simple, fast and accurate classification framework.

• Incremental Action Recognition Based on Snippets o Implementation of recursive analytic training model using clusters of training samples. o Feature computation based on multi-resolution analysis of oriented gradients. o Shape approximation based on weak-appearance constancy with dynamically changing window sizes for intensity histogram computation.

o Transformation of training data into simple and small linear representations.

• Depth Map Reconstruction Using Single Camera

o Analysis/pre-processing of various datasets for depth-from-focus computation. o Multi-resolution approach for shape-from-focus that exploits curve and line singularities in higher dimensional space with fewer coefficients.

o Depth-from-focus computation in constant time irrespective of neighborhood window. o Robust depth map computation using steerable filter to eliminate limitations associated with gradient scheme.

• Object Recognition

o Hybrid feature selection for object recognition and the use of an extremely fast learning module to eliminate inherent limitations of traditional learning frameworks. o Performance analysis of recognition accuracy using cross-fold strategy and use of publicly available datasets for reliable comparison against existing schemes.

o Projection of features into bi-directional Eigen space to preserve pixel correlation. Graduate Teaching Assistant

• Conducted tutorial sessions, labs, marked assignments, midterms and final exams for junior and senior level undergraduate courses in electronics, communications and controls. VISTA SOLUTIONS INC., WINDSOR, ON, CANADA 2006-2009 Vision Researcher, Industrial Research Assistance Program Supervisors: Michael Sirizzotti, Dean Scarlett and Jun Yang.

• A real-time algorithm for 3D analysis of non-repeatable targets in random orientation was developed using a single camera. The process consisted of camera calibration, pose estimation and robot eye-hand calibration.

• A stereo-vision module that uses neural network for 3-D orientation and position estimation of a circular feature was proposed.

• Developing methods based on literature review, performing simulations and compiling experimental observations.

HONORS & AWARDS

• Natural Sciences and Engineering Research Council of Canada funded Industrial Post Graduate Scholarship (March 2006 - February 2009) in Partnership with Vista Solutions.

• Doctoral Tuition Scholarship (January 2006 – December 2009), Faculty of Graduate Studies and Research, University of Windsor, Canada.

• Ontario Graduate Scholarship (September 2003 - August 2004), a provincial scholarship program for graduate students in Ontario.

• Ryerson Graduate Student Award (September 2003 - August 2004), Department of Electrical and Computer Engineering, Ryerson University, Canada.

• Ryerson Graduate Program Scholarship (September 2002 - August 2003), School of Graduate Studies, Ryerson University, Canada.

• Certificate of Merit for Securing 3rd Position in a Batch of 62 during Bachelor of Engineering Program. SELECTED PUBLICATIONS

• Rashid Minhas, Abdul Adeel Mohammed, Q.M. Jonathan Wu, Incremental Learning in Human Action Recognition Based on Snippets, IEEE Transaction on Circuits Systems for Video Technology, Vol. 22, Issue 11, pp. 1529-1541, 2012.

• Rashid Minhas, Abdul Adeel Mohammed, Q.M. Jonathan Wu, An Efficient Algorithm for Focus Measure Computation in Constant Time, IEEE Transaction on Circuits and Systems for Video Technology, Vol. 22, Issue 1, pp. 152-156, 2012.

• Abdul Adeel Mohammed, Rashid Minhas, Q.M. Jonathan Wu, Maher A. Sid-Ahmed, Human Face Recognition Based on Multidimensional PCA and Extreme Learning Machine, Elsevier Pattern Recognition, Vol. 44, Issues 10- 11, pp. 2588-2597, 2011.

• Rashid Minhas, Abdul Adeel Mohammed, Q.M. Jonathan Wu, Shape from Focus Using Fast Discrete Curvelet Transform, Elsevier Pattern Recognition, Vol. 44, Issue 4, pp. 839-853, 2011.

• Rashid Minhas, Abdul Adeel Mohammed, Q.M. Jonathan Wu, A Fast Recognition Framework Based on Extreme Learning Machine Using Hybrid Object Information, Elsevier Neurocomputing, Vol. 73, Issues 10-12, pp. 1831- 1839, 2010.

• Abdul Adeel Mohammed, Rashid Minhas, Q. M. Jonathan Wu, Maher A. Sid-Ahmed, A Generic Fingerprint Image Compression Technique based on Wave Atoms Decomposition, International Conference on Image Processing, 2009, Egypt.

• Abdul Adeel Mohammed, Q. M. Jonathan Wu, Maher A. Sid-Ahmed, Application of Bidirectional Two-dimensional Principal Component Analysis to Curvelet Feature Based Face Recognition, IEEE Conference on Systems Man and Cybernetics, 2009, Texas USA.

SEMINARS & WORKSHOPS

• Oral presentation at IEEE International Conference on Electro/Information Technology, Canada.

• Presentations at International Conference on Image Analysis and Recognition, Canada.

• Completed NX 100 robot programming course at Yaskawa Motoman Canada Ltd.

• Lecture on Biometric advances and challenges, University of Waterloo, fall 2010. Speaker: Dr. David Zhang (Hong Kong Polytechnic University).

• Attended workshops for teaching development conducted by the Centre for Career Action at the University of Waterloo.

• First Pass System Success Application Workshop for High Performance Electronic Design organized by ANSOFT Corporation in Detroit, USA.

• Distinguished lecture Series on Recent Advancements in Image, Video and Multimedia Processing, Ryerson University, fall 2002. Speakers: Dr. Thomas S. Huang (University of Illinois Urbana-Champaign), Dr. Sanjit K. Mitra

(University of California, Santa Barbara).

PROFESSIONAL AFFILIATIONS

• Member of Professional Engineers Ontario.

OTHER SKILLS / TRAINING

• Design Failure Mode Effect Analysis.

• Fault Tree Analysis.

• ISO 26262 Functional Safety

• HARA

• Design for Six Sigma

• Share Point Administrator.

• Nintex Workflow.

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