• Developed a real-time ball tracking and trajectory prediction system using OpenCV, enhancing prediction accuracy and motor response efficiency by optimizing algorithms for servo motor control.• Collaborated with a multidisciplinary team of engineers to establish a reliable communication pipeline between Raspberry Pi and Arduino, ensuring seamless data exchange and precise motor adjustments.• Leveraged GitHub for version control, streamlining project iterations and integrating code contributions.

As a member of SHPE, I am part of the nation's largest organization dedicated to advancing Hispanic leadership in STEM. SHPE provides me with access to a supportive community, professional development opportunities, and a network of like-minded individuals who are passionate about making an impact in our fields. Through SHPE, I am empowered to grow both personally and professionally while contributing to the broader mission of increasing Hispanic representation in science, technology, engineering, and mathematics.

Active member dedicated to empowering Latinx and Black individuals pursuing Computer Science education through participation in workshops and events conducted by industry leaders such as NVIDIA, Bloomberg, and Capital One. Gained valuable insights into diverse programming skills and enriching practices, contributing to elevating representation and fostering excellence within the tech industry.

• Consulted by members of the Bloomberg Engineering Team, engaged in an in-depth hands-on exploration of RabbitMQ.• Collaborating closely with a peer, harnessed Python and RabbitMQ for the development of a robust interaction framework between producers and consumers within messaging systems. Together, the team synergized thought processes and brainstormed ideas to craft an efficient messaging system.• Through this experience, honed collaborative skills in multidisciplinary settings, became adept at asking clarifying questions to grasp objectives, and developed proficiency in articulating thought processes to ensure assignee understanding and alignment.

• Participated in a 3-day workshop facilitated by NVIDIA professionals to gain practical experience in the fundamentals of deep learning techniques.• Utilized Jupyter Notebook, Pandas, and the TensorFlow machine-learning library for data manipulation to develop skills in training AI models. Engaged with NVIDIA experts for guidance and clarification on project inquiries and tasks.• Successfully achieved a model accuracy rate of 98% in detecting rotten fruit among ripe fruit from provided images and received certification for demonstrated proficiency in AI model development and training.