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WiDS @ SAP on May 25, 2022


Our WiDS @ SAP Americas Team was proud to present a great variety of sessions and inspiring speakers. Together, we applied data science principles in business cases and dove deep into concepts like human-centric data with our community from South and North America.


Make sure you did not miss anything and find our recorded sessions of the event below!






The session schedule for the Americas region is displayed in the Paficifc Daylight Time (PDT | UTC -7). 
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On Demand Sessions

Transforming the Order Management Process


Enterprise service providers process thousands of contracts & orders every year. We developed an order management workflow system using data analytics, to transform the overall orders process to increase their renewals and decrease disputes.

A Multi-Cloud Solution Towards Sustainability


the popularity of cloud services, data centers are increasingly becoming a major source of carbon emissions in our environment. Our team at SAP aims to reduce this impact by providing customers a dashboard to make business decisions regarding data center placement and utilization.



The Effect of Bias on Data


A representative sample is crucial to deriving insights from large sets of data. As we continue in the Information Age, it’s important now more than ever to ensure that the data we are gathering is inclusive and generalizable to the population we are trying to represent.

Fine Tuning Pre-Trained Transformer Model to Predict Car Type


Companies are interested in verifying car type for employee's rental reimbursement. To find car type requires auditor to read receipt, which is time consuming and labor intensive. To automate the process, we formulate natural language processing task to predict car type from receipt text.

Create a Trustworthy Data-Driven Organization


Data-driven Companies generate better business outcomes. Such transformation is cultural and entails re-inventing and sunsetting of current processes and is very challenging. Taking right steps help shaping the future of AI and protect our rights.

How to Recover Selection Bias from Sample and Survey Data


In Data Science, the data collection process could determine whether the analysis is biased. Anh will present standard techniques to remove those biases. When the necessary assumptions do not hold, she provides considerations about exploiting domain knowledge to recover partially from selection bias. 

Aakansha Neema
Senior Data Scientist


Aakansha Neema is a Senior Data Scientist at SAP, Palo Alto, CA on the GCS Multi Cloud Technology office team. She received her master’s in engineering management from Southern Methodist University, Dallas, Texas. Data Enthusiastic and passionate to solve data problems which can make common people life better. Her interests are machine learning, exploring visualization tools and data processing.

Anamarie Huerta Franc
Managing Director


As Managing Director for Labs US, Anamarie Huerta Franc is responsible for leading cross-company collaboration of employees developing cloud solutions. In her role, she oversees the location strategy for development, along with communications and employee engagement for the more than 5,000 development employees in the United States. She is a results-oriented, strategic thinker with more than 20 years of experience in the high-technology industry across multiple functions.

Anh Tran
Data Scientist


Anh is a passionate Data Scientist and an active public speaker who has a solid international background in data analytics and data management across Asia and Europe. With more than 11+ years of experience in different industries such as finance, ride-hailing, travel technology, manufacturing and wholesale, she is keen on bringing to the audience her unique perspectives, best practices and know-how when it comes to applying disruptive technologies.

Anjali Unnithan
Data Scientist


Anjali Unnithan is a data scientist at SAP in Palo Alto, CA on the GCS Multi Cloud Technology Office team. She received her Bachelor’s in Statistics and recently her Master’s in Data Science at UC Berkeley. Her interests in data science are machine learning, NLP, and exploring various data visualization tools.

Jenni Chan
User Researcher

Jenni is a UX researcher at SAP Labs with a background in Psychology and HCI. Through projects at SAP, she engages in ongoing conversations with end users that inform and ultimately impact products and experiences positively. Jenni is enthusiastic about continued education, both formally and through peers, and is a leader in her team’s User Research enablement effort, as well as a global co-lead of the Pride@SAP Education and Awareness workgroup. 

Jade Cock
Jade Cock
École Polytechnique Fédérale de Lausanne


Jade is currently a PhD student for the ML4ED lab led by Tanja Käser and working on early predictions of conceptual understanding in interactive simulations with a focus on fairness. She loves math and languages. Hence, she decided to travel through Europe during her studies to learn about Data Science and keep up with her language skills. It brought her so much fun that she practiced one skill more than the others! In her free time she loves to dance, play the piano, and escape the daily madness in Swiss landscapes.

Weikun Hu
Data Scientist
SAP Concur


Weikun Hu is a data scientist at SAP Concur where she works on building machine learning engines to support ExpenseIt product. She has a masters degree in applied mathematics and bachelors degree in statistics.

Margot Gerritsen
Associate Director, Stanford Data Science
Stanford University


Margot is Professor Emerita at Stanford University, and Executive Director of WiDS@Stanford and WiDS Worldwide. She received her MS from Delft University of Technology in the Netherlands, her PhD from Stanford, and before her 21 years as Stanford faculty, she spent 5 years at the University of Auckland, New Zealand. Her academic interests are in computational mathematics and range from fluid dynamics to numerical analysis to data science. Margot co-founded Women in Data Science in 2015.

Marsha Calfee
Sr. Director, Product Strategy, Data & Analytics
SAP Concur


In her role as Head of Product Success & Cross-Product Management for SAP Concur,  Marsha is responsible for the management of complex products that cross product teams, ISBN Lines of Business and are supportive of SAP’s strategy. Prior to SAP Concur, Marsha held a variety of senior management positions in product management and product marketing with BCD Travel, Genesys Telecommunications, and Infor. In addition she founded VisionLink, focusing on CRM consulting, integration and implementation. 

Mengyuan Liu
Research Manager, Data Science
SAP Concur


 Mengyuan is a data science manager at SAP Concur working on building AI solutions to revolutionize expense management and reporting. Before joining Concur, Mengyuan obtained a PhD in bioengineering from the University of Washington, specializing in applying machine learning and computer vision technologies to medical imaging. Mengyuan is passionate about supporting women in technology and has co-founded and been an organizer for Women in Data Science Puget Sound Conference for the past 3 years. 

Neda Edalat
Senior Data Scientist


Neda is a Senior Data Scientist working for SAP for over 5 years now. Her backgrounds are stochastic optimization and machine learning techniques. She is interested in bringing intelligence to LoBs. 

Nisha Balaraman
User Experience Researcher


Nisha Balaraman is a UX researcher at SAP Labs who is passionate about listening to end users to develop a deeper understanding of how we can transform complex technology into simple and enjoyable user experiences. Outside of SAP, Nisha is a board member of the non-profit organization, UX Research and Strategy 501(c)3. She also enjoys teaching Indian classical dance, traveling, and reading.

Puntis Palazzolo
Senior Data Strategist
SAP SuccessFactors


Puntis Palazzolo is a Sr. Data Strategist at SAP where she supervises the SuccessFactors data science topics and team in her role in Product Management team. She has more than a decade of experience in software design and development, machine learning systems and database technologies in different industries. Puntis has several research publications in the field of Machine Learning and Data Science and has patented ideas in the field of Recommendation Engines. Her academic background is in Computer and Electrical Engineering, Computer Science and Software Engineering.

Renee M. P. Teate
Director of Data Science


Renée M. P. Teate is the Senior Director of Data Science at HelioCampus and author of "SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis". At HelioCampus, Renee develops predictive models and interactive dashboards for university decision-makers. She is known to many as "Data Science Renee" on Twitter, and as the creator of the "Becoming a Data Scientist" podcast. She loves helping others transition into data analytics and data science careers from a variety of backgrounds.



Sally Lawler Kennedy
Sr. Director Innovation & Customer Experience


Sally has been driving innovation and championing human-centered design with world-leading companies for more than 20 years. She is the Sr. Director of Innovation and Customer Experience at SAP AppHaus. Sally focuses on leading and teaching teams to create delightful, usable, and useful software for business users. Sally was core contributor to the establishment of the Design at Business Association and was recently elected to their Board of Directors. She is also a co-lead for the SAP Business Women's Network (BWN) Bay Area group.

Samantha Weller
Data Engineer


Samantha Weller is a Data Engineer at Summersalt. As a Data Engineer she has worked directly with Data Scientists across the domains of healthcare, agriculture, and now Direct to Consumer apparel. After starting her career as a software engineer she shifted to the data space, attracted by the fact that companies are more enabled than ever to allow data to drive their business and the engineers role in building foundational data architectures.

Shruti Bhargava
Data Scientist
SAP Ariba


Shruti Bhargava is a Data Scientist at SAP Ariba, part of the Procurement Data Science team in Palo Alto. She graduated from Stanford University with a Masters in Computational and Mathematical Engineering - specializing in Data Science. She obtained her undergraduate degree in Computer Science and Engineering. At SAP, she works on applying deep learning and machine learning to enterprise use cases. Domains which interest her include Natural Language Processing and Biomedical Informatics.

Shubhi Asthana
Research Senior Software Engineer
IBM Almaden Research Center


Shubhi Asthana is a Research Senior Software Engineer at IBM Almaden Research Center in San Jose, CA. Her research interests are in the area of Cloud Services, IOT & Predictive Analytics. She has 7 years of experience developing end-to-end solutions and analytical tools for managing complex services on the cloud. Her work has appeared at several top-tier services and machine learning conferences. In addition, her innovative work has led to filing 15+ patent disclosures and winning multiple IBM Outstanding Technical Achievement Awards as well as external awards. 

Sonja Pohle
Senior Data Scientist


Sonja is a Senior Data Scientist at the SAP GCS Innovation Office with a three year Data Scientist experience. Before joining SAP, she completed a Ph.D. in Social Sciences at the University of Mannheim, Germany. Her focus is on time series analysis- and forecasting of technical KPIs.

Varsha Sankar
Data Scientist
SAP Ariba


Varsha Sankar is a Data Scientist at SAP, as a part of the Ariba Data Science team. She works on developing cutting edge AI based solutions to challenging problems in the domain of Enterprise procurement. Before joining SAP, Varsha graduated with a Masters from Stanford University, where she focused on Deep Learning and Computer Vision. Some of her areas of interest include Computer Vision and AI for social good. 

Vinitra Swamy
École Polytechnique Fédérale de Lausanne


Vinitra Swamy is a researcher at Ecole Polytechnique Federale de Lausanne(EPFL) in Switzerland, working on explainable machine learning at scale. Last year, she spoke at WIDS Silicon Valley as a lead engineer of the ONNX engineering team at Microsoft AI, collaborating with community partners to promote an open ecosystem for interoperable and efficient machine learning. Before joining Microsoft, Vinitra was a student and lecturer at UC Berkeley, where she helped scale Jupyter infrastructure and develop curriculum for the undergraduate data science major.

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WiDS @ SAP on May 25, 2022
1 Event | 10 Hours | 20+ Time zones | Virtual

Join us for Women in Data Science around the World!

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