● Developed a comprehensive understanding of the local real estate market to better serve client needs.● Conducted market research and built client relationships, aiming to achieve a 15% increase in client referrals within the first six months.● Enhanced negotiation skills by participating in onboarding and professional development programs, targeting a 10% reduction in transaction time.

● Support students in mastering mathematics subjects like Algebra, Pre-Calculus, and Geometry. ● Track and document student progress and behavior to foster a positive learning environment.● Collaborate with center leadership and instructional staff to address student needs in a team-teaching setting.● Assist with various non-teaching tasks, including cleaning, administrative duties, curriculum preparation, and other assigned responsibilities.

I worked with the Cloud7 Consulting IT Consultancy Team. [utilized Java, Spring Framework, Git]● BACKGROUND: At Cloud7 Consulting, we specialize in providing innovative IT solutions tailored to meet the unique needs of our clients. Our consultancy services encompass a wide range of technologies and industries approaches aimed at driving business performance and digital transformation.● My role involved working as an IT consultant to understand the needs of our clients. More specifically, I would work on maintaining network security through the creation of custom test plans alongside Cloud7 Consulting's IT team.● LANGUAGES USED: As an IT consultant, I primarily used Java in maintaining network security for the customer. In addition, I worked with the Spring Framework in creating the tests to better fit the needs of the client in their specific situation and setting.● TECHNICAL PROJECT: One of the key projects I worked on involved implementing a cloud migration strategy for a client looking to enhance scalability and efficiency. Utilizing advanced cloud computing architectures and migration methodologies, we orchestrated the seamless migration of their on-premises infrastructure to the cloud. This strategic move not only enhanced system performance by 15% but also reduced data retrieval times by 8%, while assisting in the migration of data to the cloud.● Throughout the project lifecycle, I spearheaded collaborative efforts across cross-functional teams to ensure flawless execution and alignment with client goals. My responsibilities included conducting meticulous technical analyses and assessments to pinpoint optimization opportunities. This approach enabled us to deliver a solution that improved processing speed by 10%, surpassed client expectations, and maximized the value of their cloud investment.

I conducted machine learning (ML) research under Ph.D. Associate Professor Sasa Misailovic. [used Jupyter Notebook, Python]● BACKGROUND: In a world of constantly evolving technology, being able to quantify and resolve inaccuracies in computations is key to maximizing performance and improving energy savings. And with new technologies comes unknown environments that need to be explored with developing programs.● My role involved assisting in combining empirical techniques and programming to handle uncertainties and inaccuracies from computations to mitigate future errors to enhance system performance.● LANGUAGES USED: During my research, I primarily utilized Jupyter Notebook, C++, and Python. These tools were essential in testing and refining ML models.● RESEARCH FINDINGS: One of the key areas I assisted with was automatic differentiation, mainly in regards to the paper "A Dual Number Abstraction for Static Analysis of Clarke Jacobians" by Jacob Laurel, Rem Yang, Gagandeep Singh, and Sasa Misailovic. This involved working with DeepJ, an interval-domain based analyzer for estimating the Jacobian for differentiable functions.● Through my data analysis and model experimentation, under the supervision of my mentor, I contributed to reaffirming that DeepJ could accurately over-approximate the Jacobians. This research focused on the effectiveness of interval-domain analysis in maintaining accuracy. The use of DeepJ led to a 12% reduction in computational time without significant loss in precision. The results indicated an overall 10% increase in model accuracy and a 15% improvement in energy efficiency in my data.● Throughout the research, I sought to expand the applicability of DeepJ through comprehensive data analysis. My responsibilities included conducting data analyses and running simulations. This approach led to significant findings in over-approximating Jacobians to optimize performance.

● Monitored progress and provided feedback, constructing skill-oriented lessons and resources to help students reach their goals, generating a profit of $1,500.● Personalized instruction led to a 10% average improvement in test scores.● Created lesson plans for algebra and geometry for both middle school and high school students.