Work Experience

Ride Operator

Six Flags Darien Lake

September 2024 - Present

  • Operate and monitor amusement park rides, ensuring the safety and enjoyment of guests by adhering to safety protocols and conducting routine equipment inspections. 
  • Provide excellent customer service by assisting guests with boarding, answering questions, and responding promptly to any concerns or emergencies.

Graduate Research Assistant

Wireless Networks for Smart Systems (WN4SS) Lab - University at Buffalo Department of Electrical Engineering

July 2024 - Present

  • Research under professor Fillipo Malandra to improve time synchronization over a distributed network.
  • Larger scope is to design a distributed optimization algorithm for a set of microprocessors in a smart grid network using 5g communication.

Software Development Engineer Intern

Amazon Web Services

June 2023 - August 2023

  • Member of the AWS Glue User Interface team (DBS Datapipelines, Glue), later AWS Maxdome
  • Given specifications of what needed to be improved on the AWS Glue front-end, drafted a design document with the what, how, why of everything to improve

Treasurer

University at Buffalo Theme Park Engineering Club

May 2023 - May 2024

  • Managed the club’s annual budget, ensuring accurate allocation of funds for various activities and events
  • Acted as the primary representative for the club at regional and national competitions, fostering relationships with other organizations

Intern

GCOM Software LLC

December 2019 - January 2020

  • Internship between highschool & college at a local software company to learn more about professional programming, and practices in the industry.

Student Assistant

Rensselaer Polytechnic Institute IT Department

September 2019 - December 2019

  • Intenship inbetween highschool & college at RPI’s IT department to learn about the troubleshooting process in the IT industry.

Extra Activities, Membership, Participation

Participanant
  • Qualtrics University Mentorship Program (September 2022 - January 2023)
  • Toronto Metropolitan University thrill design competiton by Universal Creative (November 2023)
Memberships
  • National Society of Black Engineers (NSBE) (August 2023 - Present)
  • Themed Entertainment Association (TEA) (August 2024 - Present)
  • International Association of Amusement Parks and Attraction (IAAPA) (November 2024 - Present)

Core Coursework

Calculus I - III

MTH 141, 142, 241

Covers the fundamental concepts of calculus, from single-variable to multivariable applications. Calculus 1 introduces limits, derivatives, and their applications to rates of change and optimization. Calculus 2 focuses on integration techniques, applications like areas and volumes, and infinite series. Calculus 3 extends these ideas to multiple dimensions, exploring partial derivatives, multiple integrals, and vector fields.

Math

Differential Equations

MTH 306

Analytic solutions, qualitative behavior of solutions to differential equations. First-order and higher-order ordinary differential equations, including nonlinear equations. Covers analytic, geometric, and numerical perspectives as well as an interplay between methods and model problems. Discusses necessary matrix theory and explores differential equation models of phenomena from various disciplines. 

Linear Algebra

MTH 309

Linear equations, matrices, determinants, vector spaces, linear mappings, inner products, eigenvalues, eigenvectors.

Applied Probability & Statistics

EAS 305

Application of probability theory and statistical methods to solve engineering problems. Basic probability concepts including discrete, continuous, and multivariate probability distributions are covered. Also, the fundamentals of descriptive and inferential statistics are discussed.

Electrical Engineering

Circuit Analysis

EE 202

Systematic development of network analysis methods. Topics include resistive circuits, Kirchhoff’s laws, equivalent subcircuits; dependent sources; loop and nodal analysis; energy-storage elements; transient analysis of first-order and second-order circuits; sinusoidal steady-state analysis; passive filters

Electronic Devices & Circuits

EE 310/312

Electronic devices, including operational amplifiers, diodes, bipolar junction transistors and field-effect transistors, the basic circuits in which these devices are used, and computer-aided circuit analysis for these devices and circuits.

Hardware & Software Integrated Design

CSE 450/453

Signals & Systems for Wireless Sensing

CSE 410

Computer Science & Engineering

Data Structures

CSE 250

A rigorous analysis of the design, implementation, and properties of advanced data structures. Topics include time-space analysis and tradeoffs in arrays, vectors, lists, stacks, queues, and heaps; tree and graph algorithms and traversals, hashing, sorting, and data structures on secondary storage. Surveys library implementations of basic data structures in a high-level language..

Realtime Embedded & Operating Systems

CSE 321

Topics include resource management, concurrency, secure coding practices, memory management, timeline design and analysis using metrics and schedulability tests, hardware interfacing, device driver programming, memory maps and boot kernels, firmware and ROM-resident system code, communications and networking, and debugging live systems.

Computer Architecture

CSE 490

Examines system architecture with 32- and 64-bit microprocessors. Topics include the design of high-performance computer systems, such as workstations and multiprocessor systems using recent advanced microprocessor. Considers the internal architecture of recent microprocessors, followed by vector processing, memory hierarchy design, and communication subsystems for I/O and interprocessor communication.

Machine Learning

CSE 474

Involves teaching computer programs to improve their performance through guided training and unguided experience. Takes both symbolic and numerical approaches. Topics include concept learning, decision trees, neural nets, latent variable models, probabilistic inference, time series models, Bayesian learning, sampling methods, computational learning theory, support vector machines, and reinforcement learning.