Enterprise AI Summit Enterprise AI Summit schedule

Presentation: Explainable AI for Addressing Bias and Improving User Trust

Explainable Artificial Intelligence (or XAI) has a long history of research, which has re-emerged as an active area in Deep Learning. With the growing popularity and success of Machine Learning and, especially, Deep Learning techniques, the community has been striving to open these “black boxes”. This session will show you how visual explanations can help expose harmful biases encoded by humans in the training data or model design.

Kai Xin Thia works at the intersection of data and product innovation. Over the last ten years, he has led data teams to develop machine learning products such as deep learning sentiment models, knowledge graphs, recommender systems, segmentation & targeting across industries like finance, media, jobs, eCommerce, and healthcare.

He holds a master's degree in computer science, specializing in interactive intelligence, designing systems where artificial intelligence and human intelligence can coexist harmoniously and thrive. He also co-founded DataScience SG, a data community with 10,000+ members that held 80+ meetups over the last eight years, and AI Professionals Association (AIP) for engineers and professionals working in AI-related roles.

Janet is passionate in helping clients create value for their businesses. She does this by combining her expertise in research, consultancy, advanced analytics and IT technologies. In the course of her career, Janet has provided expert advice on data science, big data analytics, artificial intelligence, and digital transformations for companies in various industries such as telecommunications, retail, smart cities, fintech, insurance, oil & gas, and manufacturing in Asia, Central America, and Africa.

Janet started her career in Globe Telecom, a telecommunications company in the Philippines, where she participated in projects ranging from quality management system implementation to new product development.

Case Study: Digital Transformation in Health Systems

Telemedicine, AI-enabled medical devices, and blockchain electronic health records are a few examples of recent innovations in healthcare. - What is the impact of the speed of these changes? - How do you maintain this evolution to deliver better patient outcomes? - Why is it important to enable organisations to innovate at scale?

Nicholas Lim is experienced in data analysis & processing, with a background in ML model training and deployment. He is interested in how to leverage the power of AI, Machine Learning and Deep Learning to solve challenging problems.

Nancy F. Chen received her Ph.D. from MIT and Harvard in 2011. She worked at MIT Lincoln Laboratory on her Ph.D. research in multilingual speech processing. She is currently leading research efforts in conversational AI and natural language generation with applications related to education, healthcare, journalism, and defense at the Institute for Infocomm Research (I2R), A*STAR. Speech evaluation technology developed by her team has been deployed at the Ministry of Education in Singapore to support home-based learning during the COVID-19 pandemic. Dr. Chen also led a cross-continent team for low-resource spoken language processing, which was one of the top performers in the NIST Open Keyword Search Evaluations (2013-2016), funded by the IARPA Babel program.

Dr. Chen has received numerous awards, including Singapore 100 Women in Tech (2021), Young Scientist Award at MICCAI 2021, Best Paper Award at SIGDIAL 2021, the 2020 P&G Connect + Develop Open Innovation Award, the 2019 L’Oréal Singapore For Women in Science National Fellowship, Best Paper at APSIPA ASC (2016), the Singapore MOE (Ministry of Education) Outstanding Mentor Award (2012), the Microsoft-sponsored IEEE Spoken Language Processing Grant (2011), and the NIH (National Institute of Health) Ruth L. Kirschstein National Research Award (2004-2008).

Dr. Chen is currently serving on the ISCA (International Speech Communication Association) Board (2021-2025) a senior IEEE member, an elected member of the IEEE Speech and Language Technical Committee (2016-2018, 2019-2021), senior area editor of Signal Processing Letters (2021-2022), associate editor of IEEE/ACM Transactions on Audio, Speech, and Language Processing (2020-2023), Neurocomputing (2020-2021), and IEEE Signal Processing Letters (2019-2021) and was the guest editor for the special issue of “End-to-End Speech and Language Processing” in the IEEE Journal of Selected Topics in Signal Processing (2017).

In addition to her academic endeavors, Dr. Chen has also consulted for various companies ranging from startups to multinational corporations in the areas of climate change (social impact startup normal), emotional intelligence (Cogito Health), EdTech (Novo Learning), speech recognition (Vlingo, acquired by Nuance), and defense and aerospace (BAE Systems).

For more info, please see http://alum.mit.edu/www/nancychen

Presentation: The Many Ways to Explain AI

Are you struggling to explain how AI and machine learning work? AI is a complex and often invisible technology. An explanation and understanding of AI is beneficial to many, but also brings many challenges. Hear how to explain AI to consumers, why it's hard to explain, and look at where an increased understanding of AI would be beneficial.

Presentation: The Many Ways to Explain AI

Are you struggling to explain how AI and machine learning work? AI is a complex and often invisible technology. An explanation and understanding of AI is beneficial to many, but also brings many challenges. Hear how to explain AI to consumers, why it's hard to explain, and look at where an increased understanding of AI would be beneficial.

Case Study: Discover AI Best Practices. Harness Potential, and Deploy AI Responsibly

• What are the best practices to align technical considerations with business opportunities?
• What are the main advantages of different AI models from a technical & business perspective? - What kind of internal structure do you need in your business to ensure ethical AI?

With more than 14 years of working experience across the space industry, Airline, and Logistics, Fawzi built up an expertise in operations research, AI/ML, and data science with an objective of promoting a data driven and a data informed vision.

Data science/product leader with a proven record of building diverse cross-functional teams to create exceptional value creation through Data.

Currently leading a portfolio of Data and AI products across eCommerce, Fintech, MNO.

Speaker at Conferences - Property Guru Data Summit SG 2017, TM Forum SG 2017, Big Data world SG 2017, Singapore Fintech Festival SG 2018, Future of Information Conference, US 2018, Big Data and AI Leaders Summit SG 2019, Experian & IDC Roundtable Conference SG, 2019, Singapore Fintech Festival, SG 2019, CDO Innovation Forum SG 2021.

Case study: Applying Artificial Intelligence to Chronic Disease Management

AI can help providers navigate the complexities of chronic disease management, leading to more effective, quality treatments. Selena+, a system which analyses retinal photographs across the nation for diabetes screening will be deployed. Join the session to learn about: How to adopt a human-centric approach, Why it’s important to focus on delivering tangible benefits How this can be applied to other chronic diseases.

Pavitra is a researcher and innovator, who develops cutting-edge AI capabilities to address critical needs in the healthcare ecosystem. With her team, she has advanced infrastructure and deep technology to readily leverage real-world patient data for diverse health intelligence applications.

At Alpha Millennia Technology Our Mission is to transform insurance from just “products” to “services” that is affordable, accessible, customisable and invisible to the customers worldwide connected through the day-to-day commercial supply chains networks and community ecosystems.

Currently leading Data & AI Solutions for Asia Pacific & Japan at Microsoft, serving as the key interlock between Strategy and Implementation of Data, Analytics & AI solutions across Microsoft Asia / APJ.

Also serving as a key public / keynote speaker in AI, Responsible AI and Technology Business Coach.

Data & AI driven professional with over 10 years of experience in data and analytics strategy and insights. Specialised in leading Digital Strategy (Data, Analytics, AI, & Digital Globalisation), Artificial Intelligence implementation & Insights.

Executive-level experience in spearheading demonstrated strategic changes to C-level stakeholders for moving the organisations to a Data & AI driven future.

Highly recognised for the ability to break down complex problems & find best practice solutions, whilst effectively communicating abstract concepts to diverse audiences. Proven ability to successfully build and lead teams.

Previously a PhD Physics student at the University of Colorado (Boulder), holding a Master of Science in Quantum Physics and a Bachelors in Mathematics and Physics (distinction and honors) from Wellesley College (MA, USA).

Madhan's goal lies in becoming a top notch in the field of Artificial Intelligence & Machine Learning, Text Analytics, Lean Six Sigma, Process Excellence & Consulting. He offers over 17 years of experience in the field of RPA Delivery, Machine Learning, Text Analytics (NLP), Data Analytics, Lean Six Sigma, Process Excellence, Consulting, Program Management, Coaching & Mentoring and driving strategic initiatives. Equipped with hands-on experience in building Text Analytics, NLP, NLU, Machine Learning, Statistical Learning & Deep Learning models, he also has built on hands-on experience in Python Programming scikit learn, tensor flow, pandas, word2vec, word embeddings, CNN, RNN LSTM, Artificial Neural Networks, NLTK, Gensim, Spacy along with experience in driving business intelligence with POWER BI, Spot fire & Tableau.

Madhan also has led the discovery, planning & execution of multiple continuous improvement projects on Automation, Data/Text Analytics, process improvements, Lean Six Sigma Green Belt & Black Belt; successfully mentored over 40 Lean & Six Sigma Projects. A NLP & ML Trainer, he has delivered trainings on NLP, Machine Learning, Deep Learning, Advanced Statistics, Lean Six Sigma trainings to Leadership, Green Belts & Black Belts in the organization.