Arvind Srinivasa

Experience

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  EDS-HP

  Jul 2007 - Sept 2008

  System Engineer
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  Telibrahma Convergent Communication Pvt Limited

  Jul 2010 - Nov 2012

  Senior Research Member - Machine Learning

  Responsible for developing a Image processing solution, like image registration, image matching, Optical Character recognition, classification.. working on natural scene images captured from smart phone or camera.- Developed an architecture & implemented algorithms for accurate image search based on features.- Developed an architecture & implemented algorithms for reduction of large image feature dataset training Areas of expertise: Digital Image Processing, machine learningProgramming skill set: C, C++, Opencv Show less

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  Bosch Global Software Technologies

  Nov 2012 - Sept 2016

  Specialist - Image processing & machine learning

  Responsible for developing state of art Image processing, computer vision & machine learning algorithms for Advance Driver Assistance System (ADAS)Following are the few relevant work1) Detection and classification of blindness scenarioDeveloped algorithms which will detect and classify different blindness scenario like blur & diffusion,occlusion,glare.2) Detection and classification of self glare scenarioDeveloped algorithms which will detect thick foggy situation during night time which will cause self glare situation. 3) Optimal exposure control for high dynamic range imagingImage acquisition is the elementary step on the way to a performing vision-based driver assistance system(DAS). developed automatic exposure and gain control algorithm using optimization techniques. for different exposure time resulting in dark and bright in the image accurately for high dynamic range imager. 4) Developed and maintained MATLAB based performance analysis framework for blindness & glare detection functionalities. Actively tested performance for every release & suggested possible solution to improve the performance 5) Simulation algorithm for HDR exposure camera control Developed a HIL filter which will simulate the working of HDR camera exposure control & same can also be used to check performance of the exposure control of the camera. Show less

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  Cognizant Global technology office

  Sept 2016 - Sept 2019

  Technology specialist : Machine learning: Cognitive Computing and Data Science Research Lab

  Working as Technology Specialist in Development of Vision and Lidar based solution for L3 and L4 functionality for Autonomous vehicle program at Cognitive computing and data science research lab. Brief summary of project undertaken for autonomous vehicle.1) Traffic light recognition system using deep learning.- Designed Deep learning frame work system architecture for traffic light recognition using deep learning and machine learning approach - Developed traffic light detection and classification methodology which work in real time using deep learning concepts.- Algorithm is deploying on the test vehicle and tested on test track & on-road.- Validation of the developed algorithm and bench marking is done by testing on real world data as we as on standard traffic light data set.2) Road sign detection and classification for autonomous vehicle - Designed a novel hierarchical training based methodology for training different road signs using deep learning method.- Developed both machine learning based & deep learning based road sign detection algorithm which can work in real time day/night situations.- Algorithm was tested by deploying on the test vehicle and tested on test track & on-road.- Validation of the algorithm is conducted on standard traffic light online data set.3) Vision based speed breaker detection for autonomous vehicleSpeed breaker is one of the obstacles detection in autonomous vehicle, developed a novel image processing and machine learning technique to detect different type of speed breakers. This method is been deployed on autonomous vehicle and tested on test track speed breakers. 4) Vision based Vehicle detection for autonomous vehicle using based deep learning methodologyVehicle Detection is one of the challenging problems in autonomous vehicle development. Vision based vehicle detection using deep learning methodology is been developed and tested on various multiple type of vehicles Show less

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  A*STAR - Agency for Science, Technology and Research

  Nov 2019 - now

  • Experienced in AI/ML development and team leadership, managing and mentoring.• Led end-to-end AI/ML clinical projects from TRL6 to TRL9 for Singapore national health initiatives.• Expertise in MLOps, spearheading workflows ensuring efficient machine learning operations.• Transformed research into viable products for market deployment.• Initiated and developed proofs of concept from scratch.• In 2023, trained/mentored 12 employees/interns with advanced ML/DL concepts.• Hands-on experience in debugging and deploying solutions in hospital settings for clinical trials. Show less Working on algorithm development for radiology applications using deep learning and machine learning concepts in Signal and Image processing lab of SBIC, A*STAR. Responsible for research, design, and development of new deep learning architectures, algorithms, and tools for pre-clinical and clinical studies using MRI, CT data. Working on advanced cutting-edge research topics likes federated learning, large cohort studies using multi-contrast data.  Part of A*Star AI3 program to develop research solution for projects under RIE 2025. Responsible for mentoring and training students and co-researchers. Show less

  • Lead Research Officer II

    Jun 2022 - now

  • Senior Researcher

    Nov 2019 - Jun 2022