Über Rohit Yelukati Mahendra
I am Rohit Yelukati Mahendra, a Python/AI Developer at Xeal Pharma with over two years of experience in Python development, Django, NGINX, Gunicorn, Celery, and system architecture design. I have strong expertise in Machine Learning, IoT, Robotics, Android development, and OpenCV. I hold a Master's degree in Artificial Intelligence and Robotics from the University of Hertfordshire.
I contributed to AutoGPT by integrating image generation blocks using Flux models via the Replicate API, enabling AutoGPT agents to create images without the need for deep technical understanding. This contribution, accepted by Toran Bruce Richards, expanded AutoGPT's use cases to include viral video generation and social media content creation.
At Xeal Pharma, I developed DAX, a robust order tracking system, and a custom pricing calculator that integrates with DAX for customer-specific quotes. I also created the Curenetics cancer annotation tool, leveraging CNNs for automatic tumor detection, and worked on EEG-based emotion recognition during my master's thesis, achieving over 90% accuracy in emotion classification.
I was honored as a Young Innovator by T-Hub for my project Pet Me, a smart dog vest for mood detection. I have also developed UKPostCodeIO, a Python client for Postcodes.io, enabling postcode lookup and geolocation services.
I am adept at rapid development, bug fixes, and optimizing workflows, always providing innovative solutions to complex problems. I can build AI models, automate systems, and deliver efficient, scalable software solutions.
I contributed to AutoGPT by integrating image generation blocks using Flux models via the Replicate API, enabling AutoGPT agents to create images without the need for deep technical understanding. This contribution, accepted by Toran Bruce Richards, expanded AutoGPT's use cases to include viral video generation and social media content creation.
At Xeal Pharma, I developed DAX, a robust order tracking system, and a custom pricing calculator that integrates with DAX for customer-specific quotes. I also created the Curenetics cancer annotation tool, leveraging CNNs for automatic tumor detection, and worked on EEG-based emotion recognition during my master's thesis, achieving over 90% accuracy in emotion classification.
I was honored as a Young Innovator by T-Hub for my project Pet Me, a smart dog vest for mood detection. I have also developed UKPostCodeIO, a Python client for Postcodes.io, enabling postcode lookup and geolocation services.
I am adept at rapid development, bug fixes, and optimizing workflows, always providing innovative solutions to complex problems. I can build AI models, automate systems, and deliver efficient, scalable software solutions.
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