Damoon Robatian, Phd Email & Phone Number

My professional evolution blends the fineness and meticulousness of pure mathematics with the pragmatism driving the world of data science.After an exhilarating odyssey through bachelor's, master's, and PhD studies in pure mathematics, I embarked on a captivating transition to the vibrant field of data science. Driven to enhance my expertise, I pursued a PhD in statistical learning, conducting extensive research on "reliable" learning from unrepresentative data. My thesis, Weakly-Supervised Learning from Unrepresentative Data, establishes foundations for consistent learning in scenarios where training data are censored and truncated. In such situations, standard machine learning methods produce biased outcomes.Shifting to machine learning marked a pivotal moment in my career by opening doors to the commercial world, intertwining my academic research roots with early exposure to the business realm.My corporate experience encapsulates diverse industries, organization sizes, project management methodologies, project types, stakeholder collaborations, and workplace types, illustrating extensive adaptability and versatility in my professional ventures.Concurrently, I've upheld ties with academia through instructing data science courses at McGill School of Continuing Studies. This dual career immersion has proven mutually beneficial, facilitating the exchange of insights between my academic pursuits and the businesses I've engaged with, akin to a liaison sharing valuable intel between the academic and industry domains.My core offerings for enterprises are🔸Expertise in machine learning, statistics, and mathematics🔸Innovative business insights driven by data🔸Research-backed data solutions🔸Project management capabilities🔸Cross-functionality and stakeholder management🔸Ethical mindset 🔸Cultural awareness, sensitivity, and empathy🔸Experience across continents🔸Passion, curiosity, and commitment to excellence🔸Continuous learning and development🔸Communication skills🔸Ability to work with minimal supervision🔸MentorshipI have a keen interest in diverse theoretical and applied subjects, including🔹Generative AI🔹Artificial narrow/general intelligence🔹Big data and distributed systems🔹EDA🔹Feature engineering🔹Data mining🔹Neural networks🔹Deep learning🔹NLP🔹Web scraping🔹Language models🔹Optimization🔹Data intrinsic dimensionality🔹Learning under sampling bias🔹Cloud computing🔹Imagery analysis and computer vision🔹predictive analytics🔹Applications of ML/AI in fintech and biotechnologyOutside work: 👪🎵🎬📚🐱🚲✈

Listed skills include Analysis, Research, Data Analysis, Statistics, and 9 others.