Passionate about improving manufacturing and business decisions using data science and optimization. Careful, persistent, patient, respectful, and competent. Received Ph.D. from Queen's University in Kingston in the area of revenue management and pricing optimization. A genuine team player committed to group success and growth. Sincere and honest with a high level of personal and professional integrity.
Previous corporate experience allows me to look into the industry from multiple perspectives. I have spent several years at 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 data science around deposit time series clustering and secondly looking into recency-frequency-monetary value marketing for day-to-day acquisition campaigns.
My current academic research focuses primarily on dynamic pricing and industrial scheduling in the context of manufacturing marketplaces. I also continue to research resort revenue management and sea cargo modeling to move my PhD-pursuing research to publication. Previously, I studied discrete optimization and approximation algorithms for scheduling on uniform processors. Now, I am looking for opportunities to improve my knowledge and experience in discrete optimization related to revenue management, modern stochastic subgradient methods, general scheduling, and decompositions for reinforcement learning.
Professionally, I am searching for a post-doctoral opportunity related to operations research, computer science, machine learning, and artificial intelligence, preferably somewhere in between. My current industrial and theoretical research stack is most relevant to decision-making and data analytics in revenue management. Decisions or machine learning in healthcare and manufacturing are highly relevant among neighboring disciplines. I am also open to investigating discrete approximation algorithms again or starting research related to theoretical stochastic optimization and deep reinforcement learning. Please send me a message if you have something to discuss.