Bence Krénusz

- Self supervised research in Synthetic Biology

- Multi-agential Reinforcement Learning solution aiming to reproduce high-level cellular behaviour.

- Establishing mathematical differentiation of Individual and Collective cellular behaviour

- Serving as input for future research.

Achievement: The result have been reviewed and presented for the Computation subgroup of Tuft University under the supervision of Prof. Michael Levin.

• Strategical and Technical Lead of the Data Science Team: - Managing the Team throughout diverse project space and applying strategical decisions following Key Principals
• Delegating tasks considering the strengths of the Team members
• Working closely with Data Engineers and Solution Architects to cover the E2E solution as effective as possible
• Strictly following the guidelines of Continuous Education and Research to be up to date in all applied Data Science field
• Applying State-of-the-Art Deep Learning solutions (e.g
• Transformer architectures) to achieve the maximum effectiveness in Prescriptive Maintenance
• Enhancing classic Statistical Predictive analytics with ML and DL and with embedded Parallelization to create a Scalable solution on Enterprise level
• Experimenting with Deep Reinforcement Learning and Virtual and Real Simulation environments to create Robotic solution for Warehouse optimization.

• Developing and implementing various e2e Machine Learning solutions satisfying Business needs, following Lean AI methodology Coding in Python, Developing from scratch or Customizing various OpenSource solutions

• Leading the technical solution (of Python programming) to solve Business problems such as Predicting Supply Chain Delivery variables and Sales Opportunity information to optimize Resources and Sales Outcome
• Responsible for the End to End Automation solution for the Machine Learning Environment
• Developing predictive models in order to forecasting Human Resource needs for particular locations
• Support the project which Predicting Demand information as Data Science assistant (Time Series analysis)
• Supporting NLP project targeting customer satisfaction content
• Supporting the Analytics Community with Deep Machine Learning and Python programming knowledge
• Achieved 1st place on Datathon - International Predictive Analytics Competition.