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ICSE 2023
Sun 14 - Sat 20 May 2023 Melbourne, Australia
Mandar Pitale

Registered user since Mon 23 Jan 2023

Name:Mandar Pitale
Bio:

Mandar Pitale have received his bachelor’s degree from University of Pune, India, in 2001. He is a seasoned software/system safety professional with more than 2 decades of experience automotive safety critical systems. In the field of ADAS/AD he has filed over 11 patent applications and few of them have been awarded by the US, Japan, China and European patent authorities. He is an expert in the International Software/System Safety Standards activities through the active participation in the following Working Groups (WG):

  • TC 22 SC 32 WG 8 US for ISO 26262: Road Vehicles – Functional Safety and ISO/PAS 21448: Road Vehicles – Safety of the Intended Functionality
  • TC 22 SC 32 WG 14 US for ISO/PAS 8800: Road Vehicles – Safety and Artificial Intelligence

He is also the sub-team 06 lead for ISO / PAS 8800 and responsible for Clause 9 - Selection of AI-Measures and design-related considerations, thereby establishing a leadership role for himself in determining the future of AI in automotive safety. He has contributed to the development of international safety standards BMW GS95014, ISO 26262, ISO 21448, IEEE P2851. He work in the area of safety of AI/ML is accepted in AAAI Conference 2020, SafeAI Workshop 2020, ICPS 2021 and CVPR 2021. He is the in the program committee of SafeAI 2022, AISafety 2022, SafeAI 2023, and reviewed papers for IEEE International Conference on Industrial Technology 2022, IEEE Sensors Journal 2022, IEEE Software Special issue on Deep Learning in Automotive Software.

Contributions:

Author of following papers:

  1. AAAI Conference 2020
  2. SafeAI Workshop 2020
  3. ICPS 2021
  4. CVPR 2021
  5. Committee Member in Program Committee of SafeAI 2022
  6. Committee Member in Program Committee of SafeAI 2023
  7. Committee Member in Program Committee of AISafety 2022
Country:United States
Affiliation:NVIDIA Corporation
Research interests:Functional Safety, System Safety, SOTIF, AI/ML Safety/Trustworthiness, Software/System Safety Engineering, Deep Learning, Computer Vision
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