Contact
lopezsabina549@gmail.com
Lopez Sabina
Physics Specialist at Y-TEC
www.linkedin.com/in/lopez- Buenos Aires, Buenos Aires Province, Argentina
sabina-091a222bb (LinkedIn)
Summary
Top Skills
Data Analytics Lopez Sabina
Grammar
Spelling lopezsabina549@gmail.com
517-240-3526
---
### Objective
Innovative and driven Computer Science graduate from the
University of Southern California with a passion for AI and future
technologies. Experienced in applying technical skills in physics
within a technology-focused environment. Seeking to leverage my
expertise and vibrant energy to contribute to groundbreaking projects
in AI development and research.
---
### Education
**Bachelor of Science in Computer Science**
University of Southern California 2009-2013
### Work Experience
**Physics Specialist**
Y Tech, [Location]
[2017] – Present
- Developed and implemented physics-based models and
simulations to solve complex problems and enhance product
development.
- Collaborated with the AI team to integrate physics principles into AI
algorithms, improving prediction accuracy and efficiency.
Page 1 of 3
- Conducted research and presented findings on the intersection
of physics and computer science, contributing to the company's
innovation strategy.
- Mentored junior team members, providing guidance on complex
physics and computer science concepts.
---
### Skills
- **Programming Languages:** , e.g., Python, Java, C++
- **AI and Machine Learning:** Familiarity with AI principles and
machine learning frameworks.
- **Data Analysis and Simulation:** Proficient in data analysis and
creating simulations to model physical phenomena.
- **Problem-Solving:** Excellent analytical and problem-solving skills,
with a keen ability to approach complex challenges systematically.
- **Communication:** Strong verbal and written communication skills,
adept at explaining technical concepts to non-technical audiences.
---
### Projects
**AI-Based Physics Simulation Project** (University Project)
- Led a team in developing an AI-driven simulation that accurately
predicts physical outcomes under varied conditions, demonstrating
the potential of AI in scientific research.
**Machine Learning for Predictive Physics Models** (Y Tech)
- Contributed to the development of a machine learning model
that enhances the predictability of physical systems, significantly
improving project outcomes.
---
Interests
- Exploring advancements in AI and future technologies.
Page 2 of 3
- Participating in tech forums and conferences to stay updated with
the latest industry trends.
- Engaging in community tech education programs to inspire interest
in STEM fields among youth.
Experience
Y-TEC
Physics Specialist
Education
University of Southern California Viterbi School of Engineering
Bachelor's degree, Computer Software Engineering · (September
2009 - September 2013)
Page 3 of 3
