Meet Team Kinetik

David is a results-oriented strategy, marketing, business development, and venture capital executive. He has experience in B2B software, IT Services, and Technology markets.

David has held multiple marketing and strategy executive roles. He develops market strategy, go-to market strategy, and portfolio strategy.

Prior to joining Kinetik, David led strategy and operational consulting engagements as a Senior Manager at Cap Gemini Ernst & Young, Ernst & Young, and Andersen Consulting (Accenture).

Yuvraj is a full stack software engineer at Kinetik with a focus on developing AI and statistical functions. Prior to Kinetik, he conducted AI research at the DepenD Lab in the Department of Neuroscience at UNC. He also has experience as a software engineer at UNC Hospitals.

Yuvraj is experienced in a broad set of data science and cloud-based development tools including Python, Java, JavaScript, TypeScript, React, Rest API, Keras, Pytest, Jupyter, Git/GitHub, Visual Studio, Docker, Kubernetes, Agile Framework, JIRA, Kanban, Scrum, Machine Learning and Artificial Intelligence.

Asna brings strong expertise in applied artificial intelligence, machine learning, automation, and data-driven system design. She has completed an MSc in Artificial Intelligence at the University of Huddersfield where her work focused on building, evaluating, and deploying end-to-end AI solutions grounded in both theory and real-world application.

In industry, Asna works as an AI Engineer at Kinetik, contributing to enterprise-scale intelligence and analytics platforms. Her work spans large-scale automation of previously manual business processes, scalable data pipeline design, feature engineering across multi-source datasets, and the development of predictive scoring models.

Yueci Sun is a full stack developer at Kinetik with experience in software development, data analytics, and applied AI. She holds a master's degree in Computer Science and a bachelor's degree in Data Science. Prior to joining Kinetik, she gained industry experience through data analytics and machine learning roles at KPMG and 1 Token, where she worked on automation, large-scale data pipelines, and ML-driven insights.

Yueci is experienced in a broad set of software engineering, data science, and cloud-based tools, including Python, Java, JavaScript, SQL, C/C++, React, Node.js, Django, FastAPI, PyTorch, MongoDB, MySQL, Git/GitHub, Docker, AWS, Linux, and RESTful APIs.

Rish brings specialized expertise in NLP and Deep Learning to the deployment team at Kinetik. Currently pursuing an MSCS at UNC Chapel Hill, he possesses a strong foundation in both research and practical implementation. Previously, as a researcher at NIT Rourkela, he focused on medical image analysis, implementing U-net architectures for brain lesion segmentation.

Rish has engineered predictive risk models at American Express and automated creative pipelines at Shopalyst. Rish utilizes a robust technical stack including Python, TensorFlow, and LangChain to build agentic AI and scalable software solutions.

Crystal is an AI engineer specializing in deep learning and computer vision. She is currently pursuing a Bachelors degree in Computer Science at Duke University, where she has conducted research through the Pratt School of Engineering and the UNC School of Medicine.

Her project experience includes developing automated pipelines to segment vagus nerve images and using deep learning to automate the diagnosis of eosinophilic esophagitis.

Her technical toolkit includes Python, Java, C/C++, PyTorch, Keras, OpenCV, and Git, with a focus on deploying robust machine learning models to solve complex real-world problems.