Work with thought leaders and academic experts from Yeshiva University

Travis Oh, PhD earned his doctoral degree in marketing with a focus on consumer behavior at Columbia University. His research primarily examines the underlying psychological processes and meanings of consumption experiences, with a focus on conceptualizing and investigating *fun* in people's lives. Prior to completing his PhD, Travis worked extensively as a market research analyst, involved in product development, pricing and promotions, and sales team management. ​ Travis specializes in consumer survey research, depth interviews & focus groups, and statistical analysis of survey data. As the founder of Apex Solution Consulting Inc., Travis has helped hundreds of small to large businesses make informed decisions based on primary research data. With many clients who are themselves consultants and professionals, Travis has a reputation as a "consultant for consultants."

Computational and Theoretical Physicist specializing in network materials, structures, and systems. My research areas have included the following: data pipeline creation, presence detection, machine learning compilers, 3D reconstruction, object detection, face detection, and facial recognition at SmartThings; deriving and simulating mechanical properties of fibrous network materials at the University of Pennsylvania; and simulations of current distribution and cascading failures of electrical power grid networks at Yeshiva University. To solve the mathematical equations I develop which govern the given research phenomena, I use optimization techniques, Machine Learning architectures (Naive Bayes, Decision Trees and Random Forests, XGBoost, and LLMs) and frameworks (such as PyTorch, TensorFlow, and Scikit-learn), and computational systems solvers such as CFD (OpenFOAM) and FEA (Abaqus, COMSOL), as well as custom solvers, scripts, and programs. I have extensive experience with writing, debugging, and running code in Python, MATLAB, and C/C++, including for parallel computing with MPI on Linux high-performance computers (HPC) and on cloud platforms such as AWS.