Anbazhagan E Email & Phone Number

Graduate with 3+ years of University project experience and 2+ years of University research experience in Artificial Intelligence and a Novice Web Developer. I am keen on leveraging my skills in Jave, Python, Machine Learning, and Deep Learning to contribute effectively to dynamic projects. Seeking challenging Software development roles to apply AI expertise while remaining open to diverse opportunities. As an enthusiastic learner, I relish tackling complex logic problems and exploring technology. My proficiencies lie in programming, science, and biology, which I thoroughly enjoy integrating to foster innovative solutions. I am determined to continuously augment my knowledge and expertise in these domains, keeping abreast of the latest advancements and trends.As a fresh Computer Science graduate from Amrita Vishwa Vidyapeetham specializing in Artificial Intelligence, I've honed my skills in several exciting projects, ranging from vehicle detection using CNN models to pioneering drug recommendation systems using ML. My stint as a Deep Learning Engineer Intern at IntellifAI Labs, Toronto, involved hands-on work with innovative models like Stable Diffusion's ControllNet and ESRGAN for image enhancement, achieving exceptionally high-quality outputs.What sets me apart? My ability to blend technical prowess with real-world applications. I've successfully integrated AI in areas of healthcare, vehicle navigation, and safety systems, proving AI's transformative impact. In the realm of research, I was proud to present my work at international conferences, pushing boundaries in drug discovery and sentiment analysis for healthcare improvements.Keen on exploring AI's potential further? Let's connect and discuss the endless possibilities! 🌐

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  Machine Learning Engineer Intern

  Intellifai Labs Inc

  Jul 2023 - Oct 2023 - Toronto, Ontario, Canada

  As a Deep Learning Engineering Intern at Intellifai Labs Inc., • I contributed to the finetuning and testing of Text-to-Speech (TTS) and Retrieval-based-Voice-Conversion (RVC) models for voice cloning applications to refine voice quality and realistic speech synthesis for 10+ voice samples of my colleagues. • I have worked on finetuning various models besides Stable Diffusion such as ControllNet with 5-10 masks, MCNET, and ESRGAN for image enhancement and generation. • I have also explored techniques like Quantization to optimize pre-trained models while maintaining high-quality image outputs with 95% retainment of weights with 2-10% quality trade-off.