Divine Tawe Tarla

I have a strong foundation in mathematics, demonstrated through ongoing research in the field. My research interests include Machine learning, Neural networks, Numerical methods, Stochastic and Fractional PDEs, Numerical Optimization, Derivative pricing and Risk management. I have 12 years of teaching experience: 7 years in high school and 5 years in higher education.

• I hold student membership and affiliations with:
• Society for Industrial and Applied Mathematics (SIAM)
• Risk Management Society (RIMS)
• Society of Actuaries (SOA)

• Published or accepted papers
• 1. S.M. Nuugulu, K.C. Patidar, and D.T. Tarla: A Physics informed neural network approach for solving time fractional Black-Scholes partial differential equations, Optimization and Engineering, 26(4) (2025) 2419-2448.
• 2. S.M. Nuugulu, K.C. Patidar, and D.T. Tarla, Data-driven neural network approaches for pricing options, Physica D: Nonlinear Phenomena, 484(13499) (2025) 134992.
• 3. S.M. Nuugulu, K.C. Patidar, and D.T. Tarla, An efficient physics-informed neural network solution to the time-space fractional Black-Scholes equation, Operations Research Forum, 6(4) (2025).
• 4. K.C. Patidar and DT Tarla, An efficient series solution to nonlinear Black-Scholes PDE with application to option pricing, News Bulletin of Calcutta Mathematical Society, 48 (1-3) (2025) 1-20.
• Submitted papers under Review
• 5. S.M. Nuugulu, K.C. Patidar, and D.T. Tarla, Physics-informed neural network approach to time fractional Black-Scholes models with rough volatility: Pricing Down-and-In Parisian Options under rough volatility, submitted for publication.
• 6. S.M. Nuugulu, K.C. Patidar, and D.T. Tarla, An efficient physics-informed neural network with fractional activation function for solving time-fractional Black-Scholes equations with rough volatility: A down-and-in Parisian option pricing case study, submitted for publication.
• 7. S.M. Nuugulu, K.C. Patidar, and D.T. Tarla, A hybrid GJR-GARCH-FHMCS–LSTM model for market risk and VaR forecasting, submitted for publication.
• Some accomplished work after PhD studies: draft manuscript undergoing revisions and related to risk management.
• 8. DT Tarla, KC Patidar and V. Lawack, Real-time risk management and regulatory-compliant stress testing using machine learning.
• 9. DT Tarla, KC Patidar and V. Lawack, Advanced cash flow forecasting with anomaly and stress modeling: mathematical foundations and practical implementation.
• 10. DT Tarla and KC Patidar, Greeks under fractional PDE dynamics: New formulas and numerical computation via PINNs.
• Collaborative work
• 11. DT Tarla et al., A Novel Edge Detection Methods using a Modified Sobel Operator with Fractional Gradients Enhancement. Submitted for publication to Pramana Journal of Physics.

• Surname: Tarla
• First names: Divine Tawe
• ID Number: AA663194
• Citizenship: Cameroonian
• Title: Dr
• Female:
• Male: X
• Place of birth: NDU
• Date of birth: 1989-10-10
• Population group: African X
• Department: Department of Mathematics and Applied Mathematics, University of the Western Cape
• Position: Part Time Associate Lecturer
• Direct Telephone: +27663155345
• Direct Telefax:
• E-mail: tarlajobs@gmail.com

• Continuing Education: THE FIRST CYCLE SECONDARY SCHOOL TEACHER DIPLOMA (LE DIPLÔME DE PROFESSEUR L'ENSEIGNEMENT DE SECONDAIRE GRADE 1ER (DIPES I))
• Institution: HIGHER TEACHER TRAINING COLLEGE, UNIVERSITY OF BAMENDA
• Year: 2010-2013
• See, transcripts for granular educational courses passed during this program.

• Courses presented
• Course: Further Mathematics (Upper Sixth Science, 11 students)
• Level: Advance Levels
• Self developed: No, Syllabus exist but I created the notes I used in teaching.
• Course: Mathematics (Form 1 to Form 5, an average class size of 90 students)
• Level: Ordinary and Advanced Levels
• Course: MAT105 (About 384 students; teaching with other two lecturers)
• Level: First year BSc
• Self developed: No
• Course: MAT126 (About 200 students; teaching with one other lecturer)
• Course: QSC131 (About 900 students; teaching with four other lecturers)
• Course: MAT221 (About 300 students; Working as a Graduate assistant under two lecturers)
• Level: Second year BSc
• Course: MAT211 (About 300 students; Working as a Graduate assistant under two lecturers)

• 4.1 I designed and presented the following poster at the MegaMath Festival 2025.
• D.T. Tarla, Financial derivative pricing using machine learning techniques, poster presented at MegaMath Festival, University of the Western Cape, Cape Town, South Africa, Poster MathsMAP#17, (2025)
• 4.2 Teamwork and collaboration with others
• Other researchers (national and international)
• During my PhD research work, I collaborated with my supervisors, Prof KC Patidar from University of the Western Cape and Dr SM Nuugulu of the University of Namibia, to write various papers on my research topic.
• Besides collaborating with my supervisors after the completion of my PhD journey, I collaborating with Gam Deaudonne (University of Bamenda), Gassan Farah (University of the Western Cape to write other articles which we are currently drafting. I am working to intentionally create as more external collaborations as possible.
• Industry
• Besides my teaching and research opportunities, I founded Tawet Consulting with the support of Gam Deaudonne whose research focuses banking and finance.
• Tawet consulting is a risk management consulting firm that leverages the power of available data to identify risk, measure the extent of adversity of the risk exposure and further work to develop customize solutions that places this exposure within acceptable tolerance if it can’t be completely avoided or eradicated.
• 4.4 Dissertations or theses (own M or PhD outputs)
• Machine learning techniques for solving a class of stochastic and fractional PDEs arising in computational finance, PhD thesis, University of the Western Cape, 2025. (Supervisor: Kailash C. Patidar, Co-supervisor: Samuel M. Nuugulu)
• Divine T. Tarla, Analysis and simulations of nonlinear option pricing problems, Master's thesis, University of the Western Cape, 2022. (Supervisor: Kailash C. Patidar)