ODSC 2022 Content Committees

Njeri Watkins

Njeri Watkins is a catalytic leader, business optimization advisor and subject matter expert with a distinguished career spanning the higher education, digital technology and startup sectors. Njeri is an influential advocate and thought leader in the areas of digital intelligence, data analytics and leadership. Njeri’s Data Excellence System is redefining change management with its integrative data-driven organizational methodology. In 2020, she received the distinguished recognition as one of the “100 Accomplished Black Canadian Women” and actively contributes to the next generation of entrepreneurs and business leaders as a startup mentor and leadership coach.

Veena B. Mendiratta, PhD

Veena Mendiratta is an applied researcher in network reliability and analytics at Nokia Bell Labs based in Naperville, Illinois, USA. Her research interests include network dependability, software reliability engineering, programmable networks resiliency, and telecom data analytics. Current work is focused on network reliability and analytics – architecting and modeling the reliability of next-generation programmable networks; and the development of analytics-based algorithms for anomaly detection, network slicing and network control for improving network performance and reliability. She has led projects on customer experience analytics using data mining and social network analysis techniques, and the development of algorithms and visual analytics for anomaly detection in telecommunications networks. She is a member of the SIAM Visiting Lecturer Program, Life Member of SIAM, Senior Member of IEEE, Member of INFORMS; member of ASA; and was a Fulbright Specialist Scholar for 5 years during which time she visited universities in India, Norway and New Zealand. She holds a B.Tech in engineering from IIT-Delhi, India, and a Ph.D. in operations research from Northwestern University, USA.

Introduction to Differential Privacy Concepts(Talk)

Dr. Chun-Kit Ngan

Dr. Chun-Kit Ngan is an Assistant Teaching Professor of Data Science in the Department of Computer Science at Worcester Polytechnic Institute (WPI) since January 2018. Before joining WPI, he was an Assistant Professor in the Division of Engineering and Information Science at the Pennsylvania State University-Great Valley (PSU-GV). His research interests are Decision Guidance and Support Systems (DGSS), including Decision Optimization Models, Deep/Machine Learning, Computational Algorithms, Natural Language Processing, Data Analytics and Visualization, and DGSS Applications, to guide domain-specific decision makers to make better decisions and provide them with actionable recommendations. He has published over 20 articles in various books, journals, and conferences. He received the Best Paper Award and the Best Student Paper Award at the 2013 and 2011 International Conference on Enterprise Information Systems respectively. His co-authored paper was selected as the Best Presentation Award in the Information Theory and Technology Session at the 2019 International Conference on Information System and Data Mining. He was the recipient of the 2013-2014 Seed Money Research Grant and 2015-2016 Early Career Award for Research and Scholarship Excellence at PSU-GV. He is also the Co-PI of the funded 2019-2022 NSF REU Site “Data Science for Healthy Communities in the Digital Age” at WPI.

Ayin Vala

Ayin Vala is the Co-founder and Chief AI Officer at VastBiome, an early stage biotechnology startup transforming cancer therapy through the microbiome. He is also a researcher at Stanford University’s Biomedical Data Science department where he specializes in cloud computing and machine learning on large medical records.
Ayin was the Chief Data Scientist at the nonprofit organization Foundation for Precision Medicine and in partnership a fellow at Google. His research and development team worked on statistical analysis and machine learning on electronic medical records, to advance medical research and healthcare delivery. On this effort, he started partnerships with Stanford University, Mayo Clinic, Yale School of Medicine, and Google.
He is the leading inventor of several patents in applying machine learning in Healthcare, Biotechnology, and Aerospace industry, including a patent approved by NASA. He was a researcher at the Big Data Systems Laboratory at Harvard University School of Engineering, and an entrepreneur at Launch Lab X at Harvard Business School. He holds a Master’s degree in Information Systems from Harvard University and resides in San Francisco.

Gilbert Song

Gilbert Song is a Staff Engineer at D2iQ, formerly known as Mesosphere. He is leading the AI/ML team and the container platform team. Taking advantage of the Cloud Native technologies and open-source deep learning frameworks, his team is focusing on building a secure, scalable, and stable machine learning enterprise product for data scientists and MLOps, to promote their AI/ML works from prototype to production. Prior to his work in AI/ML, Gilbert leads the container platform team and builds the containerization product for running data services in production. Gilbert contributes to multiple open-source communities, and he is Apache Mesos PMC/Committer, CNCF TOC Contributor and mentor of Apache ShardingSphere. He holds a Master’s degree in Computer Engineering from the University of California, Santa Barbara. He is passionate about highly available and scalable distributed machine learning systems.

Tirthajyoti Sarkar, PhD

Dr. Tirthajyoti Sarkar works as a Sr. Principal Engineer at ON Semiconductor, where he leads Artificial intelligence and Machine learning projects and develops advanced semiconductor technology and products which power everything from smartphones and data centers to electric cars.
He has published data science books, and regularly contributes highly cited AI/ML related articles on top platforms. Tirthajyoti has also developed multiple open-source software packages in the field of statistical modeling and data analytics. He has 5 US patents and ~30 technical publications in IEEE journals/conferences.
He conducts regular workshops and participates in expert panels on various AI/ML topics and contributes to the broader data science community in numerous ways. Tirthajyoti holds a Ph.D. from the University of Illinois and a B.Tech degree from the Indian Institute of Technology.

Kranthi Patcha, PhD

Kranthi Patcha is a Healthcare Technology Leader, Enterprise architect with over 20 years experience. He does Professional Services Consulting for Edifecs. He has led several complex Healthcare and Clinical Interoperability projects, B2B, SaaS, Cloud, Big Data and Advanced Analytic Solutions. Expertise in transformation solutions for HL7, CCDA, FHIR, X12 standards, Claims adjudication, Partner Ecosystems, System integrator and Implementation operations. Adviser to multiple Blue plans and industry speaker. He has a Masters degree in Software Engineering

Kexin Xie, PhD

Kexin Xie is a Senior Director of Data Science and Software Engineering at Salesforce, responsible for data science research, practices, and computing architecture for Marketing Cloud Einstein. He leads the team enabling large scale AI initiatives, processing over 7 billion monthly unique users, and making tens of trillions of weekly predictions. Before Salesforce, Kexin has worked in different sectors building large-scale data science platforms that perform machine learning, data mining and online/offline analytics in the space of data management, real-time bidding, intelligent marketing, anti-fraud and anti-money laundering. He holds a Ph.D. in computer science and has publications in top tier journals and conferences like ACM TODS and VLDB.

Navneet Rao

Navneet works on scaling machine learning at Thumbtack, a Sequoia backed online marketplace, connecting customers to professionals who can get their tasks done. Prior to this, he was the engineering lead for a team of ML engineers and research scientists innovating on Watson Assistant, IBM’s conversational AI platform. His experience in data science & machine learning spans across areas like search and relevance, conversational AI, intent detection, representation learning for text etc. He is an alumni of the Language Technologies Institute, at the School of Computer Science at Carnegie Mellon University.

Kelly Wan

Kelly Wan is a Senior Data Scientist at LinkedIn. Kelly has been with LinkedIn since 2018 and has worked on Customer Experience via NLP, experimentation via A/B testing and causal inference, and data pipeline via Spark Scala. Kelly championed entrepreneurship spirit and was a frequent speaker at various conferences (GHC, Strata and LinkedIn Tech Talk). Prior to joining LinkedIn, Kelly was working in quantitative finance at Investment Bankings around 5 years.

Karuna Lakhani

Karuna Lakhani is an n electronics undergraduate from the Mumbai University, she worked with Accenture Technologies for three years before taking up masters in Data Science in 2019 at the renowned British Columbia, Canada. Today, she is a researcher, CTO and founder of Daten and Wissen. Data Scientist with certifications in SAS, Machine Learning, and programming languages SQL, Python. She is a certified Neo4j professional with expertise in Hadoop, Machine Learning, Neural Networks, Graph Database, Data Mining techniques for Predictive Modelling and Analytics, Data Integration and Natural Language Processing. Knowledgeable and detail-oriented data scientist with over five years of experience in utilizing statistical models, she has successfully delivered projects with customer-centric companies to build graph database from website logs. It aided in drawing fundamental analysis and subsequent impactful recommendations. Karuna can create easily understandable visualization reports from complex information. To satiate her quest for novelty, she concurrently continued her research and published a paper on how to use word embedding to analyze system logs at the SMCE 2019 Conference in Italy. Additionally, she has worked on Azure ML, AWS ML and Docker. Based on her interest and capabilities, she wishes to contribute to the revolutionary technological development individualistically and hence founded an AI research-driven company Daten and Wiseen.