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Michael Mersinias

Data Scientist | Graduate Student at UT Austin

Based in Seattle, WA


I work on projects which turn data into insights and insights into high-value products or business solutions.




2022 - 2023

Graduate Research Assistant at UT Austin NLP Lab

• Developed an effective method for ChatGPT models (GTP‑3.5 and GPT‑4) to detect and correct their own errors, by combining two differently prompted instances of the model in order to emulate the human cognitive process associated with reasoning. • Improved the performance of AI text generation models (GPT-3 and GPT-J) by incorporating natural language inference in order to dynamically adjust the decoding strategy parameters and perform controlled text generation. • Increased the effectiveness of AI natural language inference models (BERT, BART and ELECTRA) by proposing a novel method of data augmentation, combined with contrastive learning and a hybrid loss function.

2019 - 2021

Data Scientist at Pharmasept SA

• Conceptualized and developed a recommendation algorithm, based on machine learning and time-series forecasting, to automatically schedule the daily route of each sales consultant to their extensive network of customers, as a result minimizing the risk of failed sales visits and increasing annual revenue generation by 11%. • Designed the budget forecast for the sales department using predictive analytics, resulting in a sales target for each product. • Utilized statistical techniques, such as a weighted ABC analysis and K-means clustering, for product and customer segmentation. • Communicated findings and visualizations to advise the stakeholders on strategic decisions for the company.


2021 - 2023

MS in Computer Science, The University of Texas at Austin

GPA: 4.00 - Major: Computer Science, Minor: Data Science and Business Analytics

2013 - 2019

BEng and MEng in Electrical and Computer Engineering,Technical University of Crete

Class Rank: 7th