Global spend on AI is predicted to be $98 Billion by 2023, up from 37.5 Billion in 2019. Maybe not unexpected for those witnessing it up close, but a whopping growth trajectory nonetheless. While machine learning models strive to mirror and predict real life as closely as possible, the people behind these models don't represent the real world. Despite this rapid forecasted growth, women still only make up a 12% of the ML workforce.
At Sama we believe in inclusive AI that benefits everyone, and believe highlighting role models is a key part in this work. With that in mind, we put together a celebratory list of some of the women we look up to and have spearheaded development in AI and Machine Learning in 2020. While it was near impossible to narrow down our list, we highly encourage you to connect with them and follow their incredible work going into 2021.Feryal Behbahani, Research Scientist, DeepMindFeryal obtained her BEng from Heron-Watt University in 2006, later going on to receive her MSc in Artificial Intelligence and Doctor of Philosophy in Machine Learning from Imperial College London. Post graduation, Feryal worked as a mentor at OpenAI and as a Research Scientist for Latent Logic (now Waymo). In 2019, Feryal started working as a Research Scientist at DeepMind, alongside volunteering at the Women in Machine Learning initiative as a director. Freyal’s work is currently focussed on Reinforcement Learning.
The desire to understand the universe led Martine to study physics at the University of Ottawa where she ultimately completed a Ph.D. in 2012. She then held Post-Doctoral Fellowships at the University of Carleton and her alma mater before undertaking a career as an industrial Research Scientist. She tackled challenges in computational chemistry at the Chemical Computing Group, natural language processing at Stradigi AI, and medical imaging at Imagia before joining Sama as Lead AI where she now steers ML R&D efforts and guides the development of the MLOps infrastructure.
Jenny Sy, Data Scientist, USA for UNHCR
Currently working as a Data Scientist at the UNHCR, an organization which protects refugees and empowers them with hope and opportunity, Jenny is focussed on building the organizations analytics database, developing key department metrics, conducting research and more. Jenny obtained her B.Sc from Ateneo de Manila University and her MBA in Business Administration from China Europe International Business School. Alongside working at UNHCR, Jenny also volunteers as a Treasurer for the Women in Machine Learning organization, supporting Women in STEM fields.
Julia Kroll, Data & ML Engineer, Amazon
Julia Kroll is a Data and ML Engineer at Amazon, currently advising engineers at enterprise companies on migrating to and innovating with the AWS cloud. Julia also works on implement performant, scalable, and secure solutions on AWS, specializing in big data, analytics, and machine learning applications. Julia has also worked as a Data Engineer at Alexa artificial intelligence, following her role as a software engineer at HubSpot.
Kallirroi Dogani, Machine Learning Engineer, Facebook
Earlier this year, Facebook gained a brilliant Machine Learning engineer in Kallirroi Dogani. Having previously worked as a ML Scientist at ASOS and Data Scientist at Tractable and Workable. Kallirroi obtained her second MSC in Artificial Intelligence from the University of Leuven, having received her first a year earlier from the University of Athens in Advanced Information Systems.
Lucy Wang, Machine Learning Engineer, Twitter
Currently working as a Machine Learning Engineer at Twitter, Lucy is focussed on the use of Machine Learning in Healthcare. Lucy previously held positions of Staff and Senior Data Scientist as Buzzfeed having earlier graduated from Columbia Engineering with an M.S in Computer Science. Aside from ML, Lucy holds interests in Natural Language Processing and Deep Learning.
Tobi obtained a BA in Mathematics from the University of Pennsylvania and MSE from John Hopkins University in Applied Mathematics and Statistics before beginning her career as a Software Engineer at JPMorgan Chase. In the years since, Tobi has held positions as a Data Scientist at Sprint, Researcher at John Hopkins University and Lead in ML at Capital One, all prior to becoming the founder of Ilekun Health, a smart technology company in the healthcare space. Ilekun Health is a technology company that gleans insight around provider quality, services offered, and price from a complex deluge of unstructured health data using artificial intelligence (AI)—currently raising initial pre-seed.
Tian Su, Director of Machine Learning, Walmart
As an experienced Data Scientist, Tian is currently working as Director of ML at Walmart. Having previously held positions of Senior Data Scientist & Head of AI/ML at 7-Eleven, Tian has been heavily focussed on personalization and delivery for customers in the CPG market. Dr Tian holds considerable experience and skill in Advanced Analytics, Data Mining, Statistical Modeling, Machine Learning, Databases and Artificial Intelligence. She also boasts a strong research background with a Ph.D. from Yale University and Master’s Degree focused on Computer Science from Georgia Institute of Technology.
Nicole Barberis, Machine Learning & Quantum ML, IBM
Nicole currently works as a Deep Learning and Quantum ML Developer for IBM in the US, aiding in the development of IBMs python solution. Nicole is a big believer in doing quantum machine learning (QML) research as she states this evolving field will eventually complement your modern suite of analytics solutions (machine learning, deep learning, etc.) Nicole worked at IBM for nine years as a Data Scientist and Information Security Analyst, before landing at her current position after two years at Bloomberg as a Data Scientist. Nicole received her MS in Applied Statistics from the University of Wyoming.
Having held several data science positions at companies including Verisk Analytics, Simarian and Farmers insurance, Saeedeh currently works as an Applied ML Scientist at Amazon in San Francisco. For the past two years, Saeedeh has been improving Amazon’s augmented reality pipeline acceptance rate using CNNs as well as building a CNN-based solution with 95% accuracy, eliminating the need for manual data annotation for shoe vendors. Saeedeh received her MSc in Systems Engineering from Boston University having also studied Industrial Engineering at the University of Tehran.
After achieving a 3.95 GPA in her Statistics PhD, Qian stayed at the University of Colorado State for five years, first as a statistical consultant and latest a graduate teaching assistant. In 2018, Qian moved out of the educational setting altogether, starting as a Data Scientist/ML Engineer at the Expedia Group, working on conversational AI to provide intelligent and personalized automatic customer service. Having spent 18 months at Expedia, Qian moved to Google in April of this year. Qian is Proficient in Python (tensorflow/keras/pandas/scikit-learn/numpy), AWS, Linux, R and SQL. Hands-on Big Data experience with Spark.
Galina Malovichko, PhD, Applied Machine Learning Scientist, Lyft
Galina obtained her PhD from UC Davis in Condensed Matter and Material Physics, having previously received an MS in Physics from the Moscow Institute of Physics and Technology. Whilst studying, Galina worked as a PhD Student Researcher and Teaching Assistant, later moving to Lyft in 2018. Initially working as a Data Scientist analyzing new features for machine learning models, predicting Lyft rides ETA, Galina later moved on to be an Applied ML Scientist, a position she has held for the last two and a half years. In her current role, Galina has built an ML stack to predict travel times, built traffic detection models and more.
