Aliaksandr Nekrashevich

Biography

Ph.D. student researching revenue management and pricing optimization. Careful, persistent, patient, respectful, and competent. Improve business decisions using data science and optimization.

Previous corporate experience allows me to look into the industry from multiple perspectives. I have spent several years in Yandex (Russian Google), starting with a recommender system prototype and then improving speech recognition at Yandex SpeechKit. Later, I also participated in two Scotiabank internships, firstly doing the data science around deposit time series clustering and secondly looking into recency-frequency-monetary value marketing for day-to-day acquisition campaigns.

In my current academic field, I spend most of my time on resort revenue management and sea cargo modeling. Previously, I studied discrete optimization and approximate algorithms for scheduling on uniform processors. Now, I am looking for opportunities that allow me to improve my knowledge and experience in discrete optimization related to revenue management, modern stochastic subgradient methods, and decomposed reinforcement learning.

Educational Background

• Belarusian State University, Bs.C. in Computer Science, 2011 - 2017, Minsk, Belarus
• National Research University Higher School of Economics, Ms.C. in Statistical Learning Theory, 2017 - 2019, Moscow, Russia (joint program with Skoltech)
• Skolkovo Institute of Science and Technology, Ms.C. in Data Science, 2017 - 2019, Moscow, Russia (joint program with NRU HSE)

Published Papers

• General parametric scheme for uniform scheduling with two different speeds. Information Processing Letters 134, pp. 18-23 · Jun 1, 2018

Conferences & Presentations

• CORS 2024: Scalable Stochastic Model for Sea Cargo Revenue Management with Empty Container Transportation; CORS 2022: A Data-Driven Approach to Resort Revenue Management