• Suki

  • Vamsi Reddy Chagari
VC

Vamsi Reddy Chagari

ASR Machine Learning Lead at Suki

Vamsi Reddy Chagari has worked at various companies in a variety of roles since 2014. In 2020, they began working as a Senior Software AI/ML Engineer at Suki. From 2018 to 2020, they were a Software Engineer at Intel Corporation, where they worked on the Next Generation Standards Group and developed 5G NR gNB L1 Software. From 2016 to 2018, they were an Embedded Systems Research Engineer and Research and Development Intern at KYOCERA AVX Components Corporation. From 2014 to 2016, they were a Master Thesis Student and Graduate Research Assistant/Associate at Arizona State University, where they worked on Software Defined Radio and developed and integrated WIFI Lite Fixed Point Model and accelerated Frame Detection, Channel Estimation, and Equalization Algorithms. From 2013 to 2014, they were a Software Engineer and Software Engineering Intern at Aricent, where they did System Integration Testing, Automation Script Development, and Testing for Qualcomm Access Points and developed a Generic Protocol Automation Suite.

Vamsi Reddy Chagari has a Master's degree in Computer Engineering from Arizona State University and a BTECH in ECE from Vellore Institute of Technology. Vamsi Reddy also has several certifications, including a Certificate of Merit for the course on "Embedded Systems Design, Wireless Protocols and Standards" from TIFAC, as well as certifications from Coursera in Convolutional Neural Networks, Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization, Machine Learning, Stanford University, Neural Networks and Deep Learning, and Structuring Machine Learning Projects.

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San Francisco, United States

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Suki

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Suki is an AI-powered, voice-enabled digital assistant for doctors that lifts the burden of documentation, enabling them to focus on what they love: treating patients. By using artificial intelligence, Suki is able to be personalized to each doctor, gets smarter as they use it, and is rapidly and inexpensively scalable. Moreover, it is easy to implement and even easier to use, not getting in the way of the physician and the patient. Suki is like having an assistant in the exam room who knows how a doctor practices and, as a result, makes the work day easier.


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