Abstracts
Keynotes
The Evolution of Model-Based Design for Future Mobility
9:30–10:00
Change is underway in the automotive industry with trends in vehicle electrification, autonomous driving, and wireless connectivity. Our reliance on software is set to increase, thereby leading us to an era of software-defined vehicles. See how technologies are shaping the industry and how Model-Based Design is evolving to manage the complexity and scale of future mobility systems. Explore developments in the Model-Based Engineering platform in the areas of systems engineering, artificial intelligence, simulation, software development, and the collaborative environment that is accelerating these trends.
![R Vijayalayan R Vijayalayan](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/mainParsys/band/mainParsys/columns/0d3ab8ce-7781-45c0-be8f-d757bd1039b1/expand/expandItems/96d5e799-1749-475f-bb1a-0edbb05804f9/parsys/columns_copy_copy_co/2/image_copy.adapt.full.medium.png/1716282939278.png)
R Vijayalayan,
MathWorks India
![Chandan Sawhney Chandan Sawhney](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/mainParsys/band/mainParsys/columns/0d3ab8ce-7781-45c0-be8f-d757bd1039b1/expand/expandItems/96d5e799-1749-475f-bb1a-0edbb05804f9/parsys/columns_copy_copy_co_1264318312/2/image_copy.adapt.full.medium.jpg/1705940352220.jpg)
Chandan Sawhney,
Tata Motors
Software-Defined Vehicles: Workflows for In-Car and Cloud Applications
11:00–11:45
Our driving experience will soon be defined by the software running in the car and in the cloud to realize the megatrends of CASE (Connected, Autonomous, Shared, and Electrification). With this transformation, vehicle software is expected to be easily updateable, highly reusable, and abstracted.
In this session, explore workflows for agile product development and reduced dependency on hardware prototypes while meeting automotive industry standards.
Highlights:
- Building software for service-oriented architectures such as Adaptive AUTOSAR and DDS
- Augmenting advanced control algorithms with machine learning and deep learning
- Integrating Model-Based Design with continuous integration for the software factory
- Transitioning engineering workflows to the cloud
Panel Discussion: Virtualization: Accelerating the Future of Mobility
11:45–12:45
Join this panel discussion to discover how engineers are using virtualization to frontload developments of system, software, and data, and explore the challenges and solutions for increased virtualization while accelerating the future of mobility.
![Rashmi Gopala Rao Rashmi Gopala Rao](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/mainParsys/band/mainParsys/columns/0d3ab8ce-7781-45c0-be8f-d757bd1039b1/expand/expandItems/96d5e799-1749-475f-bb1a-0edbb05804f9/parsys/columns_copy_copy_co_2122032489/2/image_copy.adapt.full.medium.jpg/1665575712434.jpg)
Rashmi Gopala Rao, Moderator, MathWorks India
![Asif Tamboli Asif Tamboli](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/mainParsys/band/mainParsys/columns/0d3ab8ce-7781-45c0-be8f-d757bd1039b1/expand/expandItems/96d5e799-1749-475f-bb1a-0edbb05804f9/parsys/columns_copy_copy_co_2122032489/2/image_copy_copy.adapt.full.medium.jpg/1705940352501.jpg)
Asif Tamboli,
Tata Consultancy Services
![Neha Mishra Neha Mishra](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/mainParsys/band/mainParsys/columns/0d3ab8ce-7781-45c0-be8f-d757bd1039b1/expand/expandItems/96d5e799-1749-475f-bb1a-0edbb05804f9/parsys/columns_copy_copy_co_2122032489/2/image_copy_copy_copy.adapt.full.medium.jpg/1705940352515.jpg)
Neha Mishra, Cummins India
![Anand Bhange Anand Bhange](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/mainParsys/band/mainParsys/columns/0d3ab8ce-7781-45c0-be8f-d757bd1039b1/expand/expandItems/96d5e799-1749-475f-bb1a-0edbb05804f9/parsys/columns_copy_copy_co_2122032489/2/image_copy_copy_copy_959492811.adapt.full.medium.jpg/1705940352529.jpg)
Anand Bhange, FEV India
![Mike Sasena Mike Sasena](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/mainParsys/band/mainParsys/columns/0d3ab8ce-7781-45c0-be8f-d757bd1039b1/expand/expandItems/96d5e799-1749-475f-bb1a-0edbb05804f9/parsys/columns_copy_copy_co_2122032489/2/image_copy_copy_copy_2058352484.adapt.full.medium.jpg/1552322992496.jpg)
Mike Sasena, MathWorks
Electrification
Validation of AUTOSAR Software Via Virtual ECU Using MATLAB and Simulink
14:30–15:00
The virtual engine control unit vECU (virtual ECU) is a software replacement for a hardware ECU, which allows it to execute ECU software as it does on the target ECU hardware. The virtual ECU based on MATLAB® and Simulink® provides an effective simulation platform to integrate all the components and perform effective co-simulation to test and calibrate the ECU functions.
Using a vECU based on MATLAB and Simulink in the development process has many advantages:
- Desktop environment/emulator
- Easy setup
- Application software with virtual hardware for testing and calibration
- Additional degrees of freedom during testing
- Improved reproducibility of tests without actual hardware impact
- Non-destructive testing of various hardware components
- Cost optimization
Cross-Domain Vehicle Simulation for EV System Analysis and Development
15:00–15:30
An electric vehicle system is comprised of various subsystems, components, and elements and interacts with road and traffic environments. The vehicle driving behavior influences how the load is transferred from wheels to powertrain components that deliver energy. In today’s electrified, connected, and automated vehicle systems, cross-domain interactions are tightly coupled, and their detailed analysis is tedious. To predict component performance/degradation over the life cycle, it is necessary to estimate the real-load conditions, and virtual environment is a key enabler. Multi-domain virtual vehicle simulation serves this purpose by comprising multiphysics models, which can represent complex vehicle system architectures under normal and critical test conditions. In this example, an electric vehicle model with all the components relevant for energy flow has been built and validated with real-vehicle behavior for baselining the vehicle model. Once the base vehicle model is built, it can be used for various use cases ranging from component competitive assessment, deriving loads for HV battery over 24-hours duration, and more.
![Aurobbindo Lingegowda Aurobbindo Lingegowda](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/mainParsys/band/mainParsys/columns/0d3ab8ce-7781-45c0-be8f-d757bd1039b1/expand/expandItems/c42d639a-e618-43db-808c-b53d7ec5f55a/parsys/columns_copy_copy_co_675438112/2/image_copy.adapt.full.medium.jpg/1705940352914.jpg)
Aurobbindo Lingegowda, Bosch Global Software Technologies
Master Class: Virtual Development of Battery and BMS
16:00–17:10
Developing battery systems for modern electric vehicle applications is complex and requires a sophisticated control system. Design challenges arise at all stages of the V-cycle and a range of simulations are necessary at each stage.
In this master class, learn how to verify that a battery design meets the system requirements with the help of an EV system-level model. See the design of BMS algorithms models and an evaluation of the battery performance over a range of test cases including thermal behavior and range. Once these desktop simulation models meet the requirements, explore workflows for digital twin and predictive maintenance applications.
You will also discover how to:
- Determine battery pack size to meet system-level targets
- Design and analyze thermal management systems
- Develop control systems
- Realize digital twin and predictive maintenance applications
![Abhisek Roy Abhisek Roy](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/mainParsys/band/mainParsys/columns/0d3ab8ce-7781-45c0-be8f-d757bd1039b1/expand/expandItems/c42d639a-e618-43db-808c-b53d7ec5f55a/parsys/columns_copy_copy_co_1024506898/2/image_copy.adapt.full.medium.jpg/1530549856475.jpg)
Abhisek Roy,
MathWorks India
Automated Driving
End-to-End Closed-Loop Validation of Automated Driving (AD) Systems
14:30–15:00
Automated driving and its increasing demand have led to the surge in robustness validation of AD software in simulation. Validating multiple components of AD software in closed loop gives the opportunity to functionally validate the software in integrated setup at the simulation level.
An end-to-end closed-loop framework helps to design higher-quality products, reduce costs, and deliver innovations faster. The closed-loop validation framework helps designers to understand the cascaded impact of a module’s performance.
The major challenge in creating an end-to-end closed-loop setup is integration of multiple tools. The MathWorks product chain has helped to overcome this challenge. In this session, hear about initial development and setup for service-oriented architecture (SOA) and future work.
In this case study, an end-to-end closed-loop framework of AD systems involves these major steps:
- Developing AD components with Simulink® and C/C++.
- Creating scenarios using RoadRunner and the Driving Scenario Designer app.
- Configuring plant models and sensors.
- Integrating AD components as Simulink modules and S-functions using Automated Driving Toolbox™.
![Deepika CP Deepika CP](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/mainParsys/band/mainParsys/columns/0d3ab8ce-7781-45c0-be8f-d757bd1039b1/expand/expandItems/7ff2a9e5-ffa0-4307-83e3-0dc6a74e8f75/parsys/columns_copy_copy_co/2/image_copy_copy.adapt.full.medium.jpg/1705940353180.jpg)
Deepika CP,
KPIT Technologies
![Bhagayashree Mukkawar Bhagayashree Mukkawar](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/mainParsys/band/mainParsys/columns/0d3ab8ce-7781-45c0-be8f-d757bd1039b1/expand/expandItems/7ff2a9e5-ffa0-4307-83e3-0dc6a74e8f75/parsys/columns_copy_copy_co/2/image_copy_copy_copy.adapt.full.medium.jpg/1705940353194.jpg)
Bhagayashree Mukkawar, KPIT Technologies
![Chinmayi Jamadagni Chinmayi Jamadagni](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/mainParsys/band/mainParsys/columns/0d3ab8ce-7781-45c0-be8f-d757bd1039b1/expand/expandItems/7ff2a9e5-ffa0-4307-83e3-0dc6a74e8f75/parsys/columns_copy_copy_co/2/image_copy_copy_copy_1027125774.adapt.full.medium.jpg/1705940353208.jpg)
Chinmayi Jamadagni,
KPIT Technologies
![Sanket S Shinde Sanket S Shinde](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/mainParsys/band/mainParsys/columns/0d3ab8ce-7781-45c0-be8f-d757bd1039b1/expand/expandItems/7ff2a9e5-ffa0-4307-83e3-0dc6a74e8f75/parsys/columns_copy_copy_co/2/image_copy_copy_copy_744382687.adapt.full.medium.jpg/1705940353222.jpg)
Sanket S Shinde,
KPIT Technologies
![Srinivas Boppidi Srinivas Boppidi](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/mainParsys/band/mainParsys/columns/0d3ab8ce-7781-45c0-be8f-d757bd1039b1/expand/expandItems/7ff2a9e5-ffa0-4307-83e3-0dc6a74e8f75/parsys/columns_copy_copy_co/2/image_copy_copy_copy_1460902409.adapt.full.medium.jpg/1705940353236.jpg)
Srinivas Boppidi,
KPIT Technologies
Bringing Real World to Simulation for Virtual Testing of Automated Driving (AD)
15:00–15:30
Automated driving spans a wide range of automation levels, from advanced driver assistance systems (ADAS) to fully autonomous driving. As the level of automation increases, so does the uncertainty for operational environments, increasing the needs for virtual validation. Automotive companies typically have an abundance of real-world data recorded from a vehicle that is suitable for open-loop simulations. However, recorded data is often not suitable for testing closed-loop control systems since it cannot react to changes in vehicle movement. Creating scenarios from recorded vehicle data is complicated and involves multiple steps, from sensor selection and mounting and calibration to data collection, visualization, labeling, and working with maps. In comparison with US or European traffic and road conditions, Indian traffic conditions have different scenarios on the road, e.g., different types of vehicle classes, pet and farm animals in addition to pedestrians, bullock carts, tractors, etc. This leads to imminent requirements for virtual validation with real-world scenarios and the need to recreate scenarios from the recorded vehicle data. See a methodology to recreate virtual driving scenarios from recorded vehicle data to enable closed-loop simulation for testing ADAS functionalities.
A virtual driving scenario is created by recreating roads using GPS sensor data and map import from OpenStreetMap®, and targets vehicles using the detections from automatic labeling of lidar point cloud data. To test an ADAS feature in closed loop, one must model the ego vehicle (sensor and dynamics) as well as the scenario (roads and target vehicles). In the scenario, the driver’s vehicle is referred to as the ego vehicle and other vehicles on the road are referred to as target vehicles. The created virtual driving scenario is integrated into a closed-loop simulation to assess and test the behavior of ADAS features.
![Ninad Pachhapurkar Ninad Pachhapurkar](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/mainParsys/band/mainParsys/columns/0d3ab8ce-7781-45c0-be8f-d757bd1039b1/expand/expandItems/7ff2a9e5-ffa0-4307-83e3-0dc6a74e8f75/parsys/columns_copy_copy_co_375889028/2/image_copy.adapt.full.medium.jpg/1705940353346.jpg)
Ninad Pachhapurkar, Automotive Research Association of India (ARAI)
![Jyoti Kale Jyoti Kale](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/mainParsys/band/mainParsys/columns/0d3ab8ce-7781-45c0-be8f-d757bd1039b1/expand/expandItems/7ff2a9e5-ffa0-4307-83e3-0dc6a74e8f75/parsys/columns_copy_copy_co_375889028/2/image_copy_copy.adapt.full.medium.jpg/1705940353360.jpg)
Jyoti Kale, Automotive Research Association of India (ARAI)
Master Class: Scenario Creation and Virtual Validation of AD/ADAS
16:00–17:10
Automated driving spans a wide range of automation levels, from advanced driver assistance systems (ADAS) to fully autonomous driving. As the level of automation increases, the need for testing these features on multiple scenarios becomes critical, making modeling and simulation essential. However, complex scenes and scenarios are difficult to model, and integrating these scenes and scenarios with the rest of simulation infrastructure is even harder.
In this master class, see how RoadRunner and RoadRunner Scenario can help you design environments and scenarios for the validation of automated driving algorithms. Discover how to incorporate these environments in a virtual test bench for open-loop and closed-loop validation in Simulink® .
You will also learn how to:
- Author scenes and scenarios interactively
- Recreate real world scenes and scenarios from recorded data
- Create scenario variants from seed scenario
- Perform open-loop and closed-loop testing for automated driving features and subcomponents
- Set up test automation framework for virtual simulation
![R Vijayalayan R Vijayalayan](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/modalParsys/vijayalayan/mainParsys2/columns/0503afe2-961a-4f28-98ca-e2b7a01fcfd1/image.adapt.full.medium.png/1716282939278.png)
Vijayalayan R
MathWorks
Vijayalayan R heads automotive industry and location field application engineering at MathWorks India. He and his team facilitate the adoption of Model-Based Design, empowering customers to embrace next-generation technologies on their journey towards electrification, AI, and software-defined vehicle projects. Vijayalayan is part of the management committee of the SAE India Bangalore section and has 23 years of industry experience. Prior to joining MathWorks, he worked in embedded systems leadership at Cranes Software International Limited and as a Scientist B at the Gas Turbine Research Establishment. Vijayalayan holds a bachelor's degree from Manonmaniam Sundaranar University and a master's degree in control and instrumentation from IIT Madras.
LinkedIn Profile
![Nukul Sehgal Nukul Sehgal](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/modalParsys/nukul/mainParsys2/columns/0503afe2-961a-4f28-98ca-e2b7a01fcfd1/image.adapt.full.medium.jpg/1661445999184.jpg)
Nukul Sehgal
MathWorks
Nukul Sehgal is a senior application engineer at MathWorks, where he leverages over a decade of software engineering experience as a technical strategist and SDV solution expert. He is passionate about supporting customers with cutting-edge solutions in software-defined vehicles, service-oriented architecture, embedded Linux, and high-performance computing. His deep knowledge encompasses cybersecurity, applied AI on embedded edge devices, cloud integration, and DevOps. Nukul previously led software engineering teams at Interface Microsystems, where he spearheaded projects in ECU design, software and firmware development, and functional testing. His expertise includes complete SDLC methodologies and adherence to industry standards like ASPICE and ISO 26262.
![Abhisek Roy Abhisek Roy](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/modalParsys/abhisek/mainParsys2/columns/0503afe2-961a-4f28-98ca-e2b7a01fcfd1/image.adapt.full.medium.jpg/1530549856475.jpg)
Abhisek Roy
MathWorks
Abhisek Roy is a senior application engineer at MathWorks India focusing on plant modeling and control design and automation. He works with automotive customers to address their challenges in the areas of powertrain modeling and vehicle dynamics studies. His areas of interest include the study of various automotive systems and controls systems. Abhisek earned his M.Tech in electrical engineering from the Indian Institute of Technology, Madras, specializing in control systems and robotics, and B.Tech in electrical engineering from Jadavpur University, Kolkata.
![Dr. Rishu Gupta Dr. Rishu Gupta](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/modalParsys/rishu/mainParsys2/columns/c4abe054-a2b6-4a17-bf9c-436656730b1d/image.adapt.full.medium.jpg/1530549872615.jpg)
Dr. Rishu Gupta
MathWorks
Rishu Gupta is a principal application engineer at MathWorks India. He primarily focuses on artificial intelligence and automated driving. Rishu has over 10 years of experience working on applications related to visual contents. He previously worked as a scientist at LG Soft India in the research and development unit. He has published and reviewed papers in multiple peer-reviewed conferences and journals. Rishu holds a bachelor’s degree in electronics and communication engineering from BIET Jhansi; a master’s in visual contents from Dongseo University, South Korea, working on the application of computer vision; and a Ph.D. in electrical engineering from University Technology Petronas, Malaysia, with a focus on biomedical image processing for ultrasound images.
LinkedIn Profile
![Munish Raj Munish Raj](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/modalParsys/munish/mainParsys2/columns/0503afe2-961a-4f28-98ca-e2b7a01fcfd1/image.adapt.full.medium.jpg/1663574277102.jpg)
Munish Raj
MathWorks
Munish Raj is an application engineer for automated driving at MathWorks. His areas of expertise are in scenes and scenario creation for automated driving, developing and testing perception, planning and control algorithms, and autonomous driving. He has an engineering degree in electronics and communications from VIT University, Vellore.
![Rashmi Gopala Rao Rashmi Gopala Rao](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/modalParsys/rashmi-gopala-rao/mainParsys2/columns/0503afe2-961a-4f28-98ca-e2b7a01fcfd1/image.adapt.full.medium.jpg/1665575712434.jpg)
Rashmi Gopala Rao
MathWorks
Rashmi Gopala Rao is an automotive industry manager at MathWorks India. She is responsible for strategic planning and technology rollout for the India region. Her focus is to foster industry adoption of Model-Based Design and MATLAB and Simulink. She has 20 years of industry experience working predominantly in diesel control systems with exposure to body control, chassis, and ADAS domains. Prior to joining MathWorks, Rashmi managed the hardware-in-the-loop business for India at ETAS Automotive India Private Limited. She also worked at Maruti Suzuki India Limited as manager of body control logics and at Robert Bosch India Limited on development of diesel control software. Rashmi holds a bachelor's degree from Ramaiah Institute of Technology and an executive degree in management (EPBM) from IIM Calcutta.
![Dr. Vivek Venkobarao Dr. Vivek Venkobarao](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/modalParsys/vivek-venkobara/mainParsys2/columns/0503afe2-961a-4f28-98ca-e2b7a01fcfd1/image.adapt.full.medium.jpg/1705940354262.jpg)
Dr. Vivek Venkobarao
Vitesco Technologies
Vivek Venkobarao works in plant model development and vECU validations for charging technologies. He is also an expert in artificial intelligence applications to software controls. He has 11 granted patents in US, Germany, and India, and has published more than 30 papers in various international journals and conferences. Vivek has a Ph.D. in electrical engineering.
![Aurobbindo Lingegowda Aurobbindo Lingegowda](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/modalParsys/aurobbindo-lingegowda/mainParsys2/columns/0503afe2-961a-4f28-98ca-e2b7a01fcfd1/image.adapt.full.medium.jpg/1705940354325.jpg)
Aurobbindo Lingegowda
Bosch Global Software Technologies
Aurobbindo Lingegowda leads a team of engineers at Robert Bosch working in multi-disciplinary simulation tools for cross-domain subsystems. His focus is on model-based systems engineering for identifying the model libraries in specific tools, using real test data for model validation, and applying credible methods. He works at creating a simulation environment for various use cases like vehicle-level requirements to components specs determination, 24-hour battery real-load data generation, traffic influence for cross domain vehicle function evaluation, system SIL topics, and thermal system influence in EV range. Aurobbindo has over 17 years of work experience in the automotive industry and has expertise in IC engines and hybrid and electric vehicles. He has also worked at General Motors and Honeywell. He has 4 patents published and has presented in several national and international conferences. His area of expertise is model development and cross-domain vehicle system simulation using a co-simulation approach. Aurobbindo has a bachelor’s degree in automobile engineering from Mysore University and a Master of Technology degree from National Institute of Technology (NITK)–Surathkal in mechanical engineering.
![Ninad Pachhapurkar Ninad Pachhapurkar](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/modalParsys/ninad-pachhapurkar/mainParsys2/columns/0503afe2-961a-4f28-98ca-e2b7a01fcfd1/image.adapt.full.medium.jpg/1705940354387.jpg)
Ninad Pachhapurkar
Automotive Research Association of India (ARAI)
Ninad Pachhapurkar works in the Technology Group at ARAI and is an active team member of ARAI’s Intelligent Vehicle Technology (also known as SwaymGO) project. He works on different fields of ADAS, including sensor data acquisition and annotations, sensor fusion, and AI/ML model developments for perception. He has been at ARAI for 9 years, starting in the Structural Dynamics Department, where he gained experience in different research projects and published conference papers. Ninad graduated from IIT Kharagpur.
![Jyoti Kale Jyoti Kale](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/modalParsys/jyoti-kale/mainParsys2/columns/0503afe2-961a-4f28-98ca-e2b7a01fcfd1/image.adapt.full.medium.jpg/1705940354450.jpg)
Jyoti Kale
Automotive Research Association of India (ARAI)
Jyoti Kale leads the ADAS/AV team at ARAI, focusing on India-specific dataset generation for ADAS/AV, solutions for Indian use cases, and ADAS/AD verification and validation setup. She has 15 + years of research and development experience in automotive systems and specializes in ADAS-AV, vehicle dynamics, suspension systems, steering systems, and AI-ML. Jyoti completed an M.Tech. in automotive engineering from VIT, Vellore, and is pursuing a Ph.D. in artificial intelligence from IIT Hyderabad.
![Konstantin Alexeev Konstantin Alexeev](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/modalParsys/alexeev/mainParsys2/columns/0503afe2-961a-4f28-98ca-e2b7a01fcfd1/image.adapt.full.medium.jpg/1705940354512.jpg)
Konstantin Alexeev
Vitesco Technologies
Konstantin Alexeev is an expert in embedded systems and calibration by simulation. He works mainly on development tools for model-based calibrations, tool design for calibration, framework development for calibration tools, and virtual calibration of embedded software.
![Prasanna Deshpande Prasanna Deshpande](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/modalParsys/prasanna/mainParsys2/columns/0503afe2-961a-4f28-98ca-e2b7a01fcfd1/image.adapt.full.medium.jpg/1666979318875.jpg)
Prasanna Deshpande
MathWorks
Prasanna Deshpande is manager of the automotive industry application engineering team with MathWorks India and specializes in the fields of automotive electrification, model-based control design, and automation. He and his team members closely work with automotive OEMs, suppliers, startups, and services in adopting Model-Based Design for system simulation, embedded code generation, and real-time testing. Prasanna has more than 16 years of experience with various clients from the automotive industry. Prior to joining MathWorks, he was a technical leader in the automotive group of KPIT Technologies Ltd., where he gained expertise in rapid control prototyping and hardware-in-the-loop simulation technologies for various automotive customers. He also worked as an assistant manager at Mahindra & Mahindra Ltd. Prasanna holds a bachelor’s degree in electronics and a master’s degree in instrumentation from the University of Pune.
![Neha Mishra Neha Mishra](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/modalParsys/neha/mainParsys2/columns/0503afe2-961a-4f28-98ca-e2b7a01fcfd1/image.adapt.full.medium.jpg/1705940354680.jpg)
Neha Mishra
Cummins India
Neha Mishra leads corporate shared services and capability building for the India Tech Organization at Cummins. She joined Cummins in 2017 and led corporate customer engineering and research and technology groups that were responsible for developing process and tools for simulation-based product development and supported customers with effective installation of Cummins products in their applications. Prior to Cummins, Neha joined Indian Space Research Organization at VSSC, Trivandrum, where she was responsible for design and validation of digital autopilot for launch vehicles, mostly for upper atmospheric stages. She then joined Eaton Corporation and worked on hybrid vehicle controls. She has one patent in microgrids control and several papers in national conferences. Neha completed her master’s in controls system engineering from IIT Delhi.
![Anand Bhange Anand Bhange](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/modalParsys/anand/mainParsys2/columns/0503afe2-961a-4f28-98ca-e2b7a01fcfd1/image.adapt.full.medium.jpg/1705940354750.jpg)
Anand Bhange
FEV India
Anand Bhange is a technology leader for software-defined vehicles at FEV. He is a technologist and entrepreneur in the fields of electronics and software with 25+ years of industry experience and 15+ years in automotive software. He has worked on multi-domain (automotive, telecom, and industrial) products, systems, and software. He has built practices in multiple automotive domains such as eCockpit, ADAS/AD, cybersecurity, cloud, and connectivity.
![Mike Sasena Mike Sasena](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/modalParsys/mike/mainParsys2/columns/0503afe2-961a-4f28-98ca-e2b7a01fcfd1/image.adapt.full.medium.jpg/1552322992496.jpg)
Mike Sasena
MathWorks
Mike Sasena is a product manager focusing on the automotive products developed at the MathWorks office in Novi, Michigan. Prior to joining MathWorks, Mike spent 14 years working on model-based systems engineering projects for the automotive industry. His experience includes hybrid electric vehicle modeling for fuel economy analysis, modeling predictive controls development, and heterogeneous system simulation. Mike received his Ph.D. in mechanical engineering from the University of Michigan.
![Asif Tamboli Asif Tamboli](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/modalParsys/asif/mainParsys2/columns/0503afe2-961a-4f28-98ca-e2b7a01fcfd1/image.adapt.full.medium.jpg/1705940354926.jpg)
Asif Tamboli
Tata Consultancy Services
Asif Tamboli is an autonomous driving (AD) domain consultant at TCS and works on both solution development as well as rollouts with leading car manufacturers. He has more than 18 years of experience with multiple patents in autonomous control and artificial intelligence. His primary focus area is the end-to-end development of autonomous vehicles.
![Tracy Austina Zacreas Tracy Austina Zacreas](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/modalParsys/tracy/mainParsys2/columns/0503afe2-961a-4f28-98ca-e2b7a01fcfd1/image.adapt.full.medium.jpg/1705940354995.jpg)
Tracy Austina Zacreas
Tata Technologies
Tracy Austina Zacreas is a technical learning and development professional at Tata Technologies. She has witnessed the growth of technical L&D over two decades of diversified experience. Her areas of expertise include automotive software standards, automotive electronics, and allied technologies; as well as building organization-wide technical competency development strategies across different employee levels and key customers. She is the Tata Business Excellence Model qualified internal assesor for TTL, and has been the course director and board member for universities across India and abroad. She is a regular speaker at forums including SAE, Embedded Systems Conference, and Economic Times HR Phoenix, and is a member of the SAE Western Chapter, a visiting faculty for ARAI. Tracy holds a master’s degree from Coventry University, UK, in automotive electronics. She was recently awarded an Indian patent for a revolutionary car accessory.
![Sandhya Anilkumar Sandhya Anilkumar](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/modalParsys/sandhya/mainParsys2/columns/0503afe2-961a-4f28-98ca-e2b7a01fcfd1/image.adapt.full.medium.jpg/1705940355060.jpg)
Sandhya Anilkumar
Varroc Engineering (Tech Center)
Sandhya Anilkumar is the head of department for Software CoC, Verification Validation CoC, and Software Quality CoC at Varroc Engineering. She is responsible for ensuring delivery of quality software for two-, three-, and four-wheeler new product development for the Electronics Business Unit. She is also responsible for improving development and testing efficiency by driving automation and process improvements. Sandhya has over 23 years of experience in research and development of diverse new products and technologies across industrial, automotive, and process control segments at companies like Spark Minda, Eaton, Tata Elxsi, and Emerson. She is a Certified Project Management Professional, Six Sigma Green Belt, and is the recepient of Functional Safety Level 1 for engineering and process excellence. She has three patent applications filed in automotive segments.
![Chandan Sawhney Chandan Sawhney](https://fr.mathworks.com/company/events/conferences/automotive-conference-india/2022/abstracts/_jcr_content/modalParsys/chandan/mainParsys2/columns/0503afe2-961a-4f28-98ca-e2b7a01fcfd1/image.adapt.full.medium.jpg/1705940355125.jpg)
Chandan Sawhney
Tata Motors
Chandan Sawhney is head of Advanced Engineering at Tata Motors. He joined the company in 2015 after a decade at Delphi Automotive and has over 25 years of experience in the automotive industry. During his diverse career, he has worked in product lifecycle management, business development, and product development in areas such as infotainment, body electronics, ADAS, connected vehicles, and powertrain solutions for electric, hybrid, and fuel cell vehicles.
Sélectionner un site web
Choisissez un site web pour accéder au contenu traduit dans votre langue (lorsqu'il est disponible) et voir les événements et les offres locales. D’après votre position, nous vous recommandons de sélectionner la région suivante : .
Vous pouvez également sélectionner un site web dans la liste suivante :
Comment optimiser les performances du site
Pour optimiser les performances du site, sélectionnez la région Chine (en chinois ou en anglais). Les sites de MathWorks pour les autres pays ne sont pas optimisés pour les visites provenant de votre région.
Amériques
- América Latina (Español)
- Canada (English)
- United States (English)
Europe
- Belgium (English)
- Denmark (English)
- Deutschland (Deutsch)
- España (Español)
- Finland (English)
- France (Français)
- Ireland (English)
- Italia (Italiano)
- Luxembourg (English)
- Netherlands (English)
- Norway (English)
- Österreich (Deutsch)
- Portugal (English)
- Sweden (English)
- Switzerland
- United Kingdom (English)
Asie-Pacifique
- Australia (English)
- India (English)
- New Zealand (English)
- 中国
- 日本Japanese (日本語)
- 한국Korean (한국어)