Rafael Cerna Loli — AI Researcher
Quantitative researcher with a PhD in signal processing, optimization, and machine learning, specializing in stochastic processes, time series analysis, and numerical optimization. Strong programming skills in Python, Java and C++, with experience in financial modeling, volatility surface fitting, and derivatives pricing. Proven ability to develop and implement mathematical models for data-driven decision-making.
Stackforce AI infers this person is a Telecommunications and Fintech expert with strong quantitative analysis and software engineering skills.
Location: London, England, United Kingdom
Experience: 11 yrs 9 mos
Skills
- Quantitative Models
- Quant Finance
- Wireless Engineering
- Machine Learning
- Algorithmic Trading
- Software Engineering Practices
Career Highlights
- PhD in signal processing and machine learning.
- Published multiple journal papers in top IEEE publications.
- Expertise in quantitative finance and algorithmic trading.
Work Experience
Morgan Stanley
Equity Volatility Quant (Associate) (1 yr)
Equity Derivatives Quant (Off-Cycle Intern) (6 mos)
Apple
Wireless Systems Engineer (4 mos)
Optiver
Optiver & Imperial Trading Academy Participant (0 mo)
Jane Street
Quantitative Trading Camp Participant (0 mo)
Imperial College London
Graduate Researcher - Signal Processing, Optimisation, and Machine Learning (3 yrs 6 mos)
Hacom Technologies
Telco Software Developer (3 yrs 1 mo)
Entel Perú
Core O&M Intern (1 yr 3 mos)
Pontificia Universidad Católica del Peru - PUCP
Wireless Communications Laboratory Researcher and Instructor (5 yrs 11 mos)
Education
Doctor of Philosophy - PhD at Imperial College London
Master of Science - MS at Imperial College London
Bachelor of Engineering - BE at Pontificia Universidad Católica del Perú