MAHIM TRIVEDI

Experienced Electrical Engineer with over five years in substation automation and control systems. Proficient in developing and optimizing advanced electrical systems for pharmaceuticals and marine automation. Skilled in project management, technical marketing, and team leadership. Certified in AI and Python by Google and IBM, and a Siemens-certified PLC Automation Expert. Currently pursuing an MSc in Robotics.

• Google and IBM certified Ai and python analyst
• Siemens certified PLC Automation Expert
• Certified Robotics Technician (CRT)
• Certified Automation Professional (CAP)
• Siemens Mechatronic Systems Certification

• Registration Day at the University of Bolton – in 2018
• IEEE event at the University of Bolton
• GITEX for Schneider Electric
• IET at the University of Bolton
• ADIPEC for Voyage Marine Automation
• International Automation and AI feast in Dubai
• Expo 2020 Dubai
• GCC Technology summit in Dubai
• Google Developer Students Clubs Member Event in Dubai
• Wipro Event in Dubai Assistant
• Robotics & STEM GCC

• Google Developer Student Clubs, Vice-Captain and a member
• University of Bolton, Digital Marketing intern
• IEEE, Captain in University
• IEEE, Project group leader
• Schneider Electric Dubai, Lead Operations and Technical Marketing Intern

Robotics Projects
Autonomous Delivery Robot: Designed a robot for autonomous package delivery within a specified area, equipped with navigation and obstacle avoidance systems. It uses GPS and LIDAR for route planning and environment mapping, along with machine learning algorithms to adapt to changing environments and optimize delivery routes for efficiency and safety.

Swarm Robotics: Implemented a coordinated swarm of robots for collaborative tasks like search and rescue. These robots use distributed algorithms to communicate and share information in real-time, enabling them to collectively navigate complex environments, identify targets, and adapt to dynamic situations with high resilience and efficiency.

Robotic Arm for Industrial Automation: Made a robotic arm for repetitive industrial tasks like assembly and welding. The arm features precise motion control, sensor feedback integration, and programmable tasks, enabling high accuracy and flexibility in performing a wide range of industrial applications while reducing human error and labor costs.

Line Following Robot Using ROS: Made a robot that autonomously follows a line using ROS for path tracking and control. It uses a combination of infrared sensors and a PID controller for real-time path correction, ensuring smooth and accurate line following. ROS facilitates modularity and scalability in the robot’s software architecture, making it adaptable for various applications.

Human-Robot Interaction (HRI) System: Created a robot that interacts naturally with humans for applications like customer service. This robot employs advanced NLP to understand and respond to user queries, coupled with computer vision for gesture and facial expression recognition, making interactions more intuitive and engaging.

Self-Balancing Robot: Designed a robot that balances on two wheels and navigates various terrains. It utilizes gyroscopic sensors and accelerometers for maintaining balance, and dynamic control algorithms to adjust its movements, providing stability and agility across different surfaces and inclines.

Agricultural Robot: Developed a robot for agricultural tasks such as planting, weeding, and harvesting. The robot uses machine vision to detect crops and weeds, combined with precise actuators for performing agricultural tasks efficiently. It can operate autonomously in various field conditions, improving productivity and reducing manual labor.

Underwater Robotics: Created an autonomous underwater vehicle for marine research and inspections. The vehicle features robust waterproofing, buoyancy control, and sonar-based navigation. It can collect data and perform inspections in harsh underwater environments, providing valuable information for marine biology, environmental monitoring, and industrial inspections.

Robotic Exoskeleton: Designed a wearable exoskeleton to assist mobility or enhance human strength. It uses a network of actuators at key joints to amplify the user’s movements, coupled with sensors and control algorithms for seamless and intuitive operation. This exoskeleton can aid in rehabilitation and provide support for physically demanding tasks.

Automated Guided Vehicle (AGV): Developed an AGV for autonomous transport of goods in industrial settings. It features advanced path planning, obstacle detection, and fleet management capabilities, enabling efficient and safe material handling in warehouses and factories. The AGV can adapt to dynamic environments and optimize logistics operations.

Smart Intersection Controller: Created an intelligent traffic management system to optimize intersection traffic flow. It collects real-time traffic data from sensors and cameras, uses machine learning algorithms to predict traffic patterns and adjust traffic signal timings dynamically, reducing congestion and improving overall traffic efficiency.

AI Projects
AI-based Sentiment Analysis: Developed a system that analyzes social media posts to determine public sentiment using NLP techniques. This system can process large volumes of text data, categorizing sentiments as positive, negative, or neutral, providing insights for marketing, brand management, and public opinion analysis.

Predictive Maintenance: Created an AI model that predicts equipment failures in industrial settings by analyzing sensor data and historical maintenance records. This model uses machine learning to identify patterns indicative of potential failures, allowing for proactive maintenance and reducing downtime and costs.

AI-powered Chatbot: Designed a chatbot that provides customer support and answers queries using NLP and machine learning. This chatbot can handle complex conversations, learn from interactions to improve responses over time, and integrate with various platforms to enhance customer service and operational efficiency.

Image Recognition and Classification: Built a deep learning model that can recognize and classify images into various categories. This model can be used in medical diagnosis to identify abnormalities in medical images, in security to recognize faces or objects, and in content management for automated tagging and categorization.

Fraud Detection System: Implemented an AI system that detects fraudulent transactions in real-time by analyzing transaction patterns and behaviors. This system uses machine learning to identify anomalies that deviate from normal patterns, enhancing security and preventing financial fraud in banking and online transactions.

Personalized Recommendation System: Developed a recommendation engine that suggests products or content to users based on their preferences and behavior. Using collaborative filtering and deep learning, this system analyzes user data to provide personalized recommendations, improving user engagement and satisfaction in e-commerce, streaming services, and more.

AI-driven Traffic Management: Created a system that optimizes traffic flow in urban areas by analyzing real-time traffic data and predicting congestion patterns. Machine learning algorithms adjust traffic signals and provide route suggestions to drivers, reducing travel times and emissions, and improving overall traffic management.

Voice Recognition System: Designed an AI model that recognizes and transcribes spoken language into text. This system is used in virtual assistants and automated transcription services, improving accessibility and productivity by providing accurate and efficient speech-to-text conversion.