Tech Talk: Tackling the Knapsack problem: evolutionary algorithms in asset allocation

26 March 2025 (Wednesday) | 18:30 – 20:30 BG TIME | Pwrclub (17 Henrik Ibsen Str. 5 fl.), Sofia (Bulgaria)

We are excited to invite you to an insightful tech talk where Nikolay Penchev, Senior Software Engineer at Pwrteams Bulgaria, will address the challenge of portfolio optimisation by modelling asset allocation as a knapsack problem to achieve cost efficiency.

During his talk, Nikolay will demonstrate how evolutionary algorithms - genetic algorithms, memetic algorithms and evolution strategies - can navigate vast search spaces and deliver strong solutions. By comparing these methods with a Dynamic Programming baseline, he’ll explore key trade-offs in scalability, execution time and solution quality.

Join us to gain practical insights on selecting and fine-tuning optimisation techniques to balance risk and return, even under tight computational constraints.

Registration is free but required.

Agenda

Speaker

Nikolay Penchev

Nikolay is a Senior Software Engineer at one of Pwrteams’ leading FinTech teams. Nikolay brings over a decade of experience in the IT field. His expertise spans distributed systems, REST APIs and back-end development. A member of Mensa and a champion arm wrestler, he is also an avid Machine Learning enthusiast.

Currently, Nikolay is pursuing a PhD under the supervision of Dr. Angel Marchev Jr. In addition to his professional expertise, he has co-authored several research papers, including:

• 19th International Conference, AIMSA 2024
  Title: Testing the NEAT Algorithm on a PSPACE-Complete Problem
  Authors: Angel Marchev Jr., Dimitar Lyubchev, Nikolay Penchev
• 2024 IEEE 12th International Conference on Computer Science and Network Technology (ICCSNT)
  Title: On the Application of Neural Networks in Credit Scoring: A Case-Study Analysis
  Authors: Angel Marchev Jr., Nikolay Penchev
  
  

Who should attend?

• Data scientists and ML engineers tackling complex optimization problems who want to leverage evolutionary algorithms for better performance.
• Software developers building or integrating portfolio management solutions and aiming to optimize under tight resource constraints.
• Financial analysts, portfolio managers and quantitative analysts looking for innovative methods to balance risk and return.
• Researchers and students keen on evolutionary computation and its comparison to traditional methods like dynamic programming.
• Anyone interested in applying evolutionary algorithms and AI-based approaches to real-world decision-making in finance and beyond.

Register