Alumni Talk on Edge AI in Automotive
Organized By: Department of Artificial Intelligence & Data Science
Institution: Dr. Akhilesh Das Gupta Institute of Professional Studies
Speaker: Mr. Shubham Singla (AI Developer, Atlanta System Pvt. Ltd.), Alumni of Batch 2021-25
Date & Time: 20th April 2026, 10:00 AM onwards
Venue: Seminar Hall, AI & DS Department
1. Introduction
The Department of Artificial Intelligence & Data Science organized an insightful Alumni Talk on “Edge AI in Automotive: Challenges and Opportunities for Young Engineers”. The session was delivered by Mr. Shubham Singla.
The talk focused on real-time AI processing, autonomous systems, and challenges in deploying AI models on edge devices in automotive environments.
2. Objectives of the Talk
- Understand the concept and importance of Edge AI.
- Explore real-world automotive AI applications.
- Analyze challenges in deploying AI on edge devices.
- Identify industry trends and career opportunities.
- Bridge the gap between academics and industry.
3. Speaker Profile
Mr. Shubham Singla is an AI Developer specializing in Edge AI, Computer Vision, and Embedded Systems. He has worked on intelligent transportation systems, object detection, and AI optimization techniques.
4. Summary of the Talk
4.1 Introduction to Edge AI
Edge AI enables data processing directly on devices, ensuring low latency, real-time decision-making, and reduced cloud dependency.
4.2 Automotive Applications
- Advanced Driver Assistance Systems (ADAS)
- Autonomous Driving
- Real-time Object & Lane Detection
- Driver Monitoring Systems
4.3 Challenges in Deployment
- Limited computational resources
- Model optimization & compression
- Power consumption constraints
- Real-time processing requirements
- Reliability and safety concerns
4.4 Industry Trends
- AI integration with IoT and smart vehicles
- Growth of autonomous technologies
- Rising demand for Edge AI engineers
4.5 Career Guidance
- Strong programming & problem-solving skills
- Knowledge of ML & Computer Vision
- Hands-on project experience
- Participation in internships & competitions
5. Key Takeaways
- Edge AI is essential for real-time systems.
- Automotive AI offers vast career opportunities.
- Efficiency and optimization are critical challenges.
- Practical exposure is key to success.
- Interdisciplinary skills enhance employability.
6. Conclusion
The session was highly informative and successfully connected academic learning with industry needs. It inspired students to explore careers in Edge AI and intelligent automotive systems.











