In celebration of Women's History Month, IBM and its partners are amplifying the work of incredible women trailblazers and contributors to data science and quantum computing. Join us for a full day of talks, hands-on workshops, and networking to learn more about IBM's revolutionary launch into Quantum Computing, the current state of AI and Big Data and meet the women leading the charge.
This 2-part event kicks off with a deep-dive into Quantum Computing, including industry use cases, and introduction to Qiskit. Part 2 includes a data science showcase, demonstrations of Watson Studio and WML for Visual Recognition as well as AI Ethics.
There are scheduled breaks for lunch and networking as well as mentoring. Open to all - come prepared to get answers to your top questions while learning how to apply open source technology to accelerate your careers and digital transformation initiatives.
Kelcey Gosserand is the City Leader and Program Director for IBM’s Digital Business Group, overseeing Developer Advocacy for North America. Kelcey is driving the strategy and execution of developer engagements focusing on Blockchain and emerging tech. Kelcey is a pioneer in the blockchain landscape entering the scene as an early investor and participant in the crypto-economy. She founded the blockchain community building engine, Trellis, working with clients in new market development, brand positioning, and strategy. Kelcey is a community builder, storyteller, and blockchain evangelist.
Rachel is a Principle Research Scientist and manages the AI Consumability group at IBM T J Watson Research Center, Yorktown Heights, New York. In these roles, she leads an interdisciplinary team of human-computer interaction experts, user experience designers and user experience engineers. Her team is currently working on the user experience for several of IBM Research’s AI projects, including the AI Fairness 360 toolkit. She holds many patents and has published more than 70 research papers.
Sabra is a data strategy consultant with KPMG’s Digital Enablement practice. She is specifically aligned to the Healthcare and Life Sciences Sector with clients interested in leverage data integration tools, machine learning, predictive modeling among other advanced analytic tools to drive better insights and stay on top of the disruptive wave within healthcare.
Noemi Derzsy is a Senior Inventive Scientist at AT&T Labs within the Data Science and AI Research organization, doing lots of science with lots of data. Holding a PhD in Physics and research background in Network Science and Computer Science, her interests revolve around the study of complex systems and complex networks through real-world data.
Emily Dodwell is a Senior Inventive Scientist in the Data Science and AI Research organization at AT&T Labs, where she currently focuses on predictive modeling for advertising applications, the creation of interactive tools for data analysis and visualization, and research concerning ethics and fairness in machine learning. She is a member of R Forwards, the R Foundation task force on women and other underrepresented groups. Prior to joining AT&T Labs in 2015, Emily taught high school math for three years at Choate Rosemary Hall. She received her M.A. in statistics from Yale University and B.A. in mathematics from Smith College.
Kaoutar El Maghraoui is a senior research scientist at IBM Research AI organization where she is focusing on innovation at the intersection of systems and artificial intelligence. Kaoutar has extensive and deep expertise in HPC, systems software, cloud computing, machine learning, and AI. Kaoutar holds a PhD. degree from Rensselaer Polytechnic Institute, USA. She received several awards including the Robert McNaughton Award for best thesis in computer science, IBM’s Eminence and Excellence award for leadership in increasing Women’s presence in science and technology, IBM’s award for contributions to the foundational POWER software technologies and promoting these systems in Africa, and 2 IBM’s outstanding accomplishment awards for contributions to building cognitive virtual technical agents. She is a senior member of ACM, IEEE Computer Society, and the Society of Women Engineers. Kaoutar is the chair of the Arab Women in Computing organization and avid supporter and active member of several women in science and technology initiatives. Dr. Kaoutar is a frequent speakers at various technical conferences.
Vaisakhi Mishra is a Data Scientist in IBM Data and AI group. She received her Master’s in Information Management from University of Washington, Seattle, specializing in Business Intelligence and Data Science. During her capstone project she worked extensively with UNICEF to discover and bridge immunization gaps in SAARC and Central African Countries. Prior to joining IBM’S Data Science group, she worked with IBM supply chain engineering, developing a cognitive tool to match resources to projects and shadow project opportunities. Currently as part of the Data Science Elite Team, she is an advocate for adopting data science techniques for solving niche business problems in Oil and Gas and Healthcare industry.
Zairah is a Data Scientist in Watson Discovery, a service embedded with NLP capabilities, making it easy to build AI solutions that find relevant answers in complex, disparate data with speed and accuracy. She is also involved with a corporate-wide education program on AI Skills, where she serves as a subject matter expert and course content reviewer. She served as an instructor on two, week-long residency programs held in NY in 2019, mentoring teams in the areas of Sentiment Analysis, Time Series Data Analysis and Visual Recognition. Prior to joining IBM, Zairah received her M.S. in Computer Science from the University of Pennsylvania.
Eileen Scully is the Founder and CEO of The Rising Tides, which works to make the workplace better for women through consulting and advising corporations. She is an international speaker, and author of “In the Company of Men: How Women can Succeed in a World Built Without Them”, set for publication in the spring of 2019. She is a SheSource Expert with the Women’s Media Center, and has been interviewed by Forbes, the Boston Globe, Standard and Poor’s Global Market Intelligence, Thrive Global, Psychology Today, and Inc.. In June of 2016, she was invited by the Obama White House to participate in the United State of Women, one of five thousand global advocates for women and girls.
Aishwarya is a post-graduate in Data Science from Columbia University; she strives for innovation. She is a young researcher in machine learning and reinforcement learning, who is an energetic and enterprising person. She is an extrovert by nature and looks out for any learning opportunity. She utilizes her entrepreneurial skill to engage with clients and pitch to them about the team expertise. She is an advocate for Women in Data Science and actively participates in events and conferences to inspire budding data scientists. She is very focused on expanding her horizons in the machine learning research community including her recent Patent Award won in 2018 for developing Reinforcement Learning model for Machine Trading.
Hanhee Paik is a research staff member at IBM Q and has been studying superconducting qubit systems since the beginning of the field. Through her research career, she has been focusing on understanding and improving coherence mechanisms of superconducting qubits, and developing novel superconducting multi-qubit architectures. She received a PhD at Joint Quantum Institute, University of Maryland, and during her postdoc at Yale University pioneered a new design of superconducting qubits with breakthrough coherence time. She was integral in the development of the 16-qubit IBM Q Experience cloud device, which is available for free to the public.
33 Thomas Street (formerly the AT&T Long Lines Building) is an iconic 550-foot-tall (170 m) skyscraper in Civic Center, Manhattan, New York City. It stands on the east side of Church Street, between Thomas and Worth Streets. The building is an example of the Brutalist architectural style with its flat concrete slab facade.