Advanced Risk and Portfolio Management Quant Bootcamp | ARPM Expected: July 2024
· Quantitative Research, Stochastic Calculus, Financial Engineering, Quant Risk Management, Quant Portfolio Management.
IBM Certified Associate Developer - Quantum Computation | IBM Quantum January 2024
· Quantum circuit simulation, transpilation, quantum algorithms for communications, optimization, error correction, QISKIT.
Quantum computing | Qubit by Qubit & IBM Quantum December 2022
· Quantum circuit design, fundamentals, quantum algorithms for communications, networking, optimization, and error correction.
Data Management | Hewlett Packard Enterprise Data Science Institute April 2022
· Exploratory Data Analysis, data ETL, web scrapping, data exploration and analysis, statistical packages in Python.
Cluster Computing: Linux, shell scripting, queuing systems, cluster architecture, HPC| HPEDSI November 2021
Scientific Programming with Python | Hewlett Packard Enterprise Data Science Institute August 2021
· Data structures, NumPy, Pandas, SciPy, Jupyter, Matplotlib, Seaborn, OOP, scikit-learn.
Machine Learning | Stanford University – Coursera November 2020
· Regression, regularization, neural networks, time series, SVM, PCA, anomaly detection, recommender systems, system design.
Machine Learning, Quantitative research and Optimization:
Designed pipelines to assess customer credit worthiness and predict future default risk using Regression, Random Forest, XGBoost and neural networks (TensorFlow) with accuracies >92% and F1 scores >0.94.
Built and trained a model for household energy usage via time series analysis and K-means validation in Python to optimize the hyperparameters, leading to a 15% optimization in production.
Engineered and deployed Markov Chain Monte Carlo (MCMC) simulations in C++ and Python to solve Langevin dynamics and the 2d Ising model in a 50x50 lattice with 99% prediction accuracy.
Engineered a quantum support vector machine (QSVM) with parametrized circuits and error mitigation to classify handwritten digits from a dataset reaching 98% accuracy.
Optimized an algorithm to select a portfolio from a set of real stocks (time series from 2016 to 2018) by implementing a variational quantum eigensolver pipeline with a classical optimizer, achieving a 15% performance improvement.
Designed an AI hangman player in Python and trained it using a LSTM neural network architecture in Keras to automate gameplay resulting in a 62%-win rate.
Analyzed cumulative retail sales in the US and created interactive dashboards in Tableau to provide insights into the KPIs.
As part of my PhD, I’ve been actively learning quantum computing theory and applications. I participated in two IBM Quantum challenges, and in their last summer school, obtaining advanced badges in all of them. I have used dynamic circuits, error mitigation, and different quantum algorithms to tackle classification and optimization problems.
o I developed an undergraduate course in quantum computing, which covers quantum information, error correction and quantum communications, emphasizes physical intuition, and includes Qiskit lab sessions with hands-on examples. We aim for these resources to be available both in English and Spanish, so we are establishing collaborations with universities in the US and South America.
o Applied dynamic circuits and noise mitigation in Qiskit to boost the execution of quantum algorithms (communications, QAOA, QML, QEC) improving fidelity 200x over standard methods across 5 IBM Quantum events.
o Used mid-circuit measurements as feed-forward in iterative phase estimation, quantum teleportation, and error correction circuits, and implemented a 54-qubit GHZ state with stabilizers in a 127-qubit quantum processing unit.
o Designed a quantum support vector machine (SVM) pipeline with parametrized circuits and error mitigation to classify handwritten digits from a dataset.
o Built a quantum circuit using a variational quantum eigensolver and a classical optimizer to find the best selection for a portfolio from a set of real stocks using time series data from 2016 to 2020.
o Built quantum variational eigensolver circuits to tackle energy (Qiskit Nature) and portfolio optimization problems.
I also attended the QSim Summer School in Telluride, CO, where we reviewed different platforms that are used to implement qubits and quantum simulators, including ion traps, Rydberg atoms, and superconducting circuits. We also covered introductory and advanced topics in digital and analog quantum simulations, qubitization, and error correction.
(2024) APS March Meeting | The role of conformal symmetry and instability in determining the temperature of a causal diamond | Minneapolis, MN.
(2023) Princeton/TAMU Conference | Entanglement degradation in bipartite systems with a finite-lifetime observer| IQSE Texas A&M University | Casper, WY.
(2023) APS March Meeting | Entanglement degradation in bipartite systems with a finite-lifetime observer| Las Vegas, NV.
(2023) Physics Research Day at University of Houston | Presented poster.
(2022) Texas Section APS Meeting | Entanglement degradation due to the finite-lifetime of an observer | Rice University, Houston TX.
(2022) Quantum Information and Structure of Spacetime (QISS) Conference | QISS initiative/Templeton Foundation. London, Canada.
(2023) RQS Quantum Simulation Summer School | NSF Quantum Leap Challenge Institute for Robust Quantum Simulation | Telluride, CO.
(2023) Qiskit Global Summer School: From theory to implementation | IBM Quantum | Online.
(2023) Quantum Science Camp | IQSE Texas A&M University | Casper, WY.
(2022) School on Table-Top Experiments for Fundamental Physics | Perimeter Institute for Theoretical Physics. Waterloo, Canada.
(2022) Spring School on Open Quantum Systems | NSF Challenge Institute for Quantum Computation (CIQC).
(2018) Magnetics Summer School | IEEE. Ecuador.
(2014) Advanced Topics in Magnetism and Superconductivity AToMS | Centro Atomico Bariloche. Argentina.
(2014) School on Structural and Chemical characterization techniques | Universidad San Francisco de Quito. Ecuador.
Quantum Field Theory
Quantum Many-Body Theory
Computational Physics
Statistical Mechanics
Mathematical Methods for Physics I & II
Solid State Physics