Kerrie Mengersen, PhDDistinguished Professor, Statistics | Director QUT | QUT Centre for Data Science
Dipanjan (DJ) SarkarLead Data Scientist | Google Developer Expert - ML Constructor Learning, Zurich
Sonal AgarwalVice President – Consumer Customer Marketing and Personalization Decision Science American Express
Eve Psalti is 20+year tech and business leader, currently the Senior Director at Microsoft’s Azure AI engineering organization responsible for scaling & commercializing artificial intelligence solutions.
She was previously the Head of Strategic Platforms at Google Cloud where she worked with F500 companies helping them grow their businesses through digital transformation initiatives.
Prior to Google, Eve held business development, sales and marketing leadership positions at Microsoft and startups across the US and Europe leading 200-people teams and $600M businesses.
A native of Greece, she holds a Master’s degree and several technology and business certifications from London Business School and the University of Washington. Eve currently serves on the board of WE Global Studios, a full-stack startup innovation studio supporting female entrepreneurs.
Radhakrishnan G (Krish)
Krish joined American Express in 2002 and has held responsibilities in fraud and credit risk management teams across consumer and commercial portfolios globally. Krish is currently the Global Head of Commercial Risk Decision and Data Science for Global Commercial Card, Non-Card and Merchant portfolios. In the last 5+ years, his team has driven several data science innovations and modeling enhancements to transform Commercial Risk Models for American Express.
Krish has a strong track record of setting clear multi-year winning agendas and establishing strong partnerships that have been instrumental in rapidly deploying models with the best data intelligence and algorithms that are now a significant competitive advantage for the company. He is passionate about Data Science and Machine learning and over the last decade has played a leadership role in the adoption of machine learning in risk decisions within American Express.
As a senior leader, Krish has a well-deserved reputation for building a high-value talent pipeline through his keen eye at hiring and stewardship of the Learning & Development program that has transformed new hire onboarding and leadership training for the next generation of leaders. He is a voting member of several risk committees with American Express and leads the Talent Acquisition for India Centre of Excellence. He is also Amex appointed Board Member of SBFE (Small Business Financial Exchange).
Krish holds an MBA in Finance and Bachelors degree in Chemical Engineering.
Alison Cossette is a dynamic Data Science Strategist, Educator, and Podcast Host. As a Developer Advocate at Neo4j specializing in Graph Data Science, she brings a wealth of expertise to the field. With her strong technical background and exceptional communication skills, Alison bridges the gap between complex data science concepts and practical applications.
Alison’s passion for responsible AI shines through in her work. She actively promotes ethical and transparent AI practices and believes in the transformative potential of responsible AI for industries and society. Through her engagements with industry professionals, policymakers, and the public, she advocates for the responsible development and deployment of AI technologies.
Alison’s academic journey includes pursuing her Master of Science in Data Science program, specializing in Artificial Intelligence, at Northwestern University and research with Stanford University Human-Computer Interaction Crowd Research Collective. Alison combines academic knowledge with real-world experience. She leverages this expertise to educate and empower individuals and organizations in the field of data science.
Overall, Alison Cossette’s multifaceted background, commitment to responsible AI, and expertise in data science make her a respected figure in the field. Through her role as a Developer Advocate at Neo4j and her podcast, she continues to drive innovation, education, and responsible practices in the exciting realm of data science and AI.
Kerrie Mengersen, PhD
Kerrie Mengersen is a Distinguished Professor of Statistics and Director of the Centre for Data Science at QUT. Her career in statistical consulting and academic research has taken her across three states of Australia, the USA and France. Kerrie is a Fellow of the Australian Academy of Science, the Australian Academy of Social Sciences, and the Queensland Academy of the Arts and Sciences. Her overall ambition is to ‘use data better’, particularly in the fields of health, environment and industry. To this end, she has led over 30 major projects such as the current Long-term Benefits and Impacts Study with Queens Wharf Brisbane, the online interactive Australian Cancer Atlas and the Virtual Reef Diver program.
A TEDx speaker, Dom brings a wealth of data storytelling experience to StoryIQ from his career at QBE, one of Australia’s largest insurance companies. At QBE, he was a senior leader in data analytics and business improvement, presenting data-driven strategy recommendations to the company’s senior executives and producing reports for the Group Board of Directors.
Helen Thompson is an Associate Professor of Statistics in the School of Mathematical Sciences and the Centre for Data Science at QUT. She specialises in statistical modeling and machine learning. With expertise in high-dimensional data analysis, space-time modeling, and optimum experimental design, she has made significant contributions to various fields including health, environment, and social sciences. She has published extensively in leading journals and her work provides valuable insights into complex datasets, uncovering hidden patterns and informing optimal decision-making processes in projects including Optimal Resource Extraction with BHP, Emergency Department Demand Modelling with Queensland Metro South Health and Hospital Services, Great Barrier Reef monitoring programs, and the Australian Cancer Atals.
Dipanjan (DJ) Sarkar
Dipanjan (DJ) Sarkar is an acknowledged Data Scientist, published Author and Consultant with over nine years of industry experience in all things data. He was recognized as a Google Developer Expert in Machine Learning by Google in 2019, and a Champion Innovator in Cloud AI\ML by Google in 2022. He currently works as a Lead Data Scientist at Constructor Learning (formerly Schaffhausen Institute of Technology (SIT) Learning), Zurich.
Dipanjan has led advanced analytics initiatives working with Fortune 500 companies like Intel, Applied Materials, Red Hat / IBM. He works on leveraging data science, machine learning and deep learning to build large- scale intelligent systems. Dipanjan also works as an independent consultant, mentor and AI advisor in his spare time collaborating with multiple universities, organizations and startups across the globe. His passion includes solving challenging data problems as well as educating and helping people upskill in all things data. Find more about him at https://djsarkar.com
My name is Seth Juarez. I currently live near Redmond, Washington and work for Microsoft.
I received my Bachelors Degree in Computer Science at UNLV with a Minor in Mathematics. I also completed a Masters Degree at the University of Utah in the field of Computer Science. I currently am interested in Artificial Intelligence specifically in the realm of Machine Learning. I currently work as a Program Manager in the Azure Artificial Intelligence Product Group.
I’ve been married now for 21 years to a fabulously talented woman and have two beautiful daughters, and two feisty sons.
Session Title: Ask the Experts! ML Pros Deep-Dive into Machine Learning Techniques and MLOps
Abstract: Experienced machine learning engineers and data scientists care about ways to easily get their models up and running quickly and share ML assets across teams for collaboration. Collaborate and streamline the management of thousands of models across teams with new, innovative features in Azure Machine Learning. Come and join us in this interactive session with our product experts and get your questions answered on the latest capabilities in Azure Machine Learning!
Vaishali is a lead data scientist at Indium Software, a leading digital engineering company. She has 9 years of experience in the advanced analytics domain. She manages a large data science team, does project planning and builds enterprise grade analytics models for various real-world usecases. As a technology evangelist, Vaishali also coaches aspiring professionals on data science, machine learning and various advanced analytics technologies like natural language processing, computer vision, deep learning etc., She holds a professional postgraduate in Artificial Intelligence & Machine Learning.
Transformers for Document Understanding(Tutorial)
Hugo Bowne-Anderson, PhD
Hugo Bowne-Anderson is a data scientist, writer, educator & podcaster. His interests include promoting data & AI literacy/fluency, helping to spread data skills through organizations and society and doing amateur stand up comedy in NYC. He does many of these at DataCamp, a data science training company educating over 3 million learners worldwide through interactive courses on the use of Python, R, SQL, Git, Bash and Spreadsheets in a data science context. He has spearheaded the development of over 25 courses in DataCamp’s Python curriculum, impacting over 170,000 learners worldwide through my own courses. He hosts and produce the data science podcast DataFramed, in which he uses long-format interviews with working data scientists to delve into what actually happens in the space and what impact it can and does have. He earned PhD in Mathematics from the University of New South Wales, Australia and has conducted biomedical research at the Max Planck Institute in Germany and Yale University, New Haven.
Mehrnoosh Sameki, PhD
Mehrnoosh Sameki is a principal PM manager at Microsoft, where she leads emerging Responsible AI technology and tools and for the Azure Machine Learning platform. She has cofounded Error Analysis, Fairlearn and Responsible AI Toolbox and has been a contributor to the InterpretML offering. She earned her PhD degree in computer science at Boston University, where she currently serves as an adjunct assistant professor, offering courses in responsible AI. Previously, she was a data scientist in the retail space, incorporating data science and machine learning to enhance customers’ personalized shopping experiences.
Ville has been developing infrastructure for machine learning for over two decades. He has worked as an ML researcher in academia and as a leader at a number of companies, including Netflix where he led the ML infrastructure team that created Metaflow, a popular open-source framework for data science infrastructure. He is a co-founder and CEO of Outerbounds, a company developing modern human-centric ML. He is also the author of the book Effective Data Science Infrastructure, published by Manning.
Minsoo is a Senior Product Manager at Microsoft Azure Machine Learning designing and building out Responsible AI tools for data scientists. She’s worked with OSS tools such as InterpretML, Fairlearn, Responsible AI Toolbox and contributed to the UX of the Responsible AI dashboard now released in Azure Machine Learning. She has bachelor’s degrees in Applied Mathematics and Painting from Brown University and Rhode Island School of Design (RISD). Coming from an interdisciplinary background with experience in building machine learning models and products, analyzing data, and designing UX, she is always finding work at the intersection of AI/ML, design, and social sciences to empower data and ML practitioners to work ethically and responsibly end-to-end.
Giulia Carella is a Data Scientist at CARTO. She holds a PhD in Applied Statistics and has experience in the development and application of statistics and machine learning methods for spatio-temporal data, with applications ranging from climate science to spatial demography.
Unlocking Spatial Data Science in the Cloud (Demo Talk)
Raghav is a seasoned Data Science professional with over a decade’s experience of research & development of large-scale solutions in Finance, Digital Experience, IT Infrastructure and Healthcare for giants such as Intel, American Express, United HealthGroup and DeliverHero. He is an innovator with 10+ patents, a published author of multiple well received books & peer-reviewed papers and a regular speaker in leading conferences on topics in the areas of Generative AI, Recommendation Systems, Computer Vision, NLP, Deep Learning, Machine Learning and Augmented Reality.
Bharti Motwani is the sole author of many books “Data Analytics with R” (Wiley), “Data Analytics using Python” (Wiley), “HR Analytics: Practical Approach using Python” (Wiley), “Machine Learning for Text and Image data: Practical Approach with Business Use Cases”
(Wiley) etc. Ambitious and analytical professional; IT and analytics consultant and corporate trainer; Result driven and articulate academician who can think “out of the box”, with more than 25 years of experience in teaching at professional and premium institutes at global level, research and software development. Demonstrated proficiency in writing books, editing and reviewing journals, and writing more than 50 research papers in leading international and national journals.
Big Data Analysis with PySpark (Workshop)
A M Aditya
Aditya is a tech enthusiast with more than 7 years of experience across various technologies in data science, machine learning, deep learning and computer vision. He has completed his Masters in Data Science from the National University of Singapore. He has worked across various domains including automotive, banking, retail among others consulting various clients around the globe. He is a true believer of ‘You got to see it work to know it works’ and sets goals towards achieving the same in any of the endeavours he undertakes. Being highly inclined towards technology, he founded Xaltius Pte. Ltd in Singapore which has a major focus on building solutions in Data Science and AI and educating students and professionals in the same areas. He also founded Code for India which specializes in delivering top notch skills in Data Science and AI as required in the industry today. Apart from work, he loves to engage with kids and get involved in social work.
Danni Li is an AI Resident at Meta. She is interested in building efficient AI systems and applications to solve real-world problems. Her current research focuses on on-device ASR models and optimization techniques.
Xander Song is a Machine Learning Engineer and Developer Advocate at Arize AI and one of the creators of Phoenix, a popular notebook-first python library that leverages embeddings to uncover problematic cohorts of LLM, CV, NLP and tabular models. Before joining Arize, Song worked as a machine learning engineer at early stage AI startups. He is based in Oakland, California.
Suman Debnath is a Principal Developer Advocate (Data Engineering) at Amazon Web Services, primarily focusing on Data Engineering, Data Analysis and Machine Learning. He is passionate about large scale distributed systems and is a vivid fan of Python. His background is in storage performance and tool development, where he has developed various performance benchmarking and monitoring tools.
Habib Baluwala, a dedicated data leader with a PhD from Oxford, serves as the Domain Chapter Lead at Spark New Zealand. With over 15 years of experience in data engineering and data science, he has developed a deep understanding of how data can drive business success. Habib’s exceptional leadership and communication skills enable him to effectively engage with stakeholders, lead high-performing teams, and drive data-driven decision-making across the organization. He actively explores AI governance for responsible and ethical AI implementation. Committed to continuous learning and teamwork, his expertise is exemplified by his Chief Data Officer certification. A seasoned leader, Habib’s unique combination of technical expertise and leadership skills empowers him to deliver innovative data solutions that support business growth.
Chaine San Buenaventura
Chaine San Buenaventura is the co-founder of Voilabs, an early-stage AI startup based in Paris specializing in voice chatbots for customer service. They are exploring the transformative capabilities of AI in reshaping digital interactions and are committed to driving innovation in this space. Chaine continues to contribute her expertise to Wizy.io, where she has been serving as the Lead Machine Learning Engineer, assisting in the advancement of their AI initiatives. Passionate about the future of AI, Chaine consistently explores the intersection of deep learning and natural, context-rich digital interactions, continually pushing the boundaries of what’s possible in Human-Machine Interaction. Her years of dedicated work in developing AI solutions and active participation in research, conferences, and community dialogues underscore her commitment to AI innovation and knowledge-sharing in the expanding field.
Jason Tan is the Founder of Engage AI, a Conversation Copilot that remembers conversations across multiple channels to augment conversations in virtual and real-life. Since its release in Jan 2023, over 30,000 users worldwide have been using it to break the ice and engage with their prospects. Taking the learnings from implementing Engage AI, he also assists and shares the learnt lessons with enterprises to embrace and incorporate Generative AI and Large Language Models into their business.
Kuldeep Jiwani is Head of Data Science for HiLabs, a US Healthcare MNC. He has been driving research and innovation in the Healthcare sector using state of the art AI technologies like LLMs, Medical Ontologies, NLP, Predictive Analytics in multiple areas, Bayesian modeling, Statistical modeling, Time series forecasting, etc. Built 6 products in a year with a team of 50+ data scientists, where each product gathered multi-million dollars for the company.
Prior to this he was building machine learning applications at massive scale for the telecom sector. Discovering telecom subscribers behavioural patterns via mining and modelling billions of daily records, for various use cases like Churn prediction, Network congestion, Service experience, etc. He has been a Performance architect designing high scalable Big Data solutions over distributed systems. Then designing ultra-low latency trading solutions for the Financial trading tools industry. He has been a researcher all along, publishing papers and practically finding new ways to solve real world problems. He has also been an Entrepreneur and founding member of a startup that was successfully acquired by Oracle.
LLMs and Ontologies for Precision NERC(Tutorial)
Kevin Noel is currently Lead of Machine Learning Ads at Mapbox Japan and has more than 10 years experience in Japan. Previously, he held principal ML role at the largest Big Data, E-commerce in Japan (Rakuten), working with large scale multi-modal data (Tabular, Time series, Japanese NLP, image) through numerous machine learning projects in real time Ads/Recommendations, also provided internal training on Deep Learning and external talks on applied ML (New York, 2019, Kobe(Japan)… )… Prior to this, Kevin, with a background in applied Stochastic Modeling and Data Mining from Ecole Centrale (France), held various quantitative roles a BNP Paribas, Bank of America, and ING in Asia/Japan.
Seema Chokshi is the founder of Brainbox Solutions, guiding small and medium size firms in adopting AI to improve productivity. Seema is an established thought leader and expert with over two decades of experience in the field of Data Science. Seema learned about the power of data driven decisioning during the 2008 global financial crisis, as a part of the New York based niche credit risk management team, in the global financial services firm, American Express. Her love for inspiring the younger generation with her passion for the field, made her join Singapore Management University in 2013 as the Faculty and Founding Director of the university-wide Analytics Program. Over the years she has taught various graduate courses covering multiple aspects of Data Science. Seema has advised multiple organizations globally to set up productive Data Science teams. Seema is the author of multiple cases studies, available for purchase in the Harvard Business store, with focus on uncovering challenges that hamper trust in AI. Her research aims to uncover how Responsible AI can help companies inch closer to reaping full benefits of AI by minimising unintended consequences and instilling trust in the technology at the same time. Seema is a women’s empowerment champion, guiding and mentoring women in navigating the challenges of their unique career journeys through women empowerment sessions and meetups.
Jayachandran Ramachandran is the Senior Vice President and Head of Artificial Intelligence Labs at Course5 Intelligence. He is responsible for Applied AI research, Innovation and IP development. He is a highly experienced Analytics and Artificial Intelligence (AI) thought leader, design thinker, inventor with extensive expertise across a wide variety of industry verticals like Retail, CPG, Technology, Telecom, Financial Services, Pharma, Manufacturing, Energy, Utilities etc.
Sonal joined American Express in 2011 and has held multiple responsibilities across decision science teams over the past 12 years. She is currently Vice President for customer marketing models for consumer business at American Express. She has been instrumental in redefining personalization and digital marketing in the era of Big Data to drive revenue while also enhancing the customer experience. Under her leadership, the team has driven multiple machine learning and data science innovations across self-learning models and boosting to drive incremental revenue for the business. Sonal has a strong track record of driving results for unstructured projects working across large global team of data scientists and business partners. She is also passionate about grooming talent and creating a strong pipeline of next gen leaders. She was the recipient of the president award in 2019 for her outstanding contributions and leadership. She lives in Gurgaon with her husband and two young girls.
Rohit Sroch is a Sr. AI Scientist at Artificial Intelligence Labs at Course5 Intelligence, with over 5 years of experience in the Natural Language Processing and Speech domains. He plays a pivotal role in conceptualizing and developing AI systems for the Course5 Products division. Simultaneously, he maintains an active involvement in his research endeavors, leading to the publication of several research papers in recent years. Also, his fervent interest in the constantly evolving landscape of AI drives him to engage in continuous research and stay abreast of the latest technologies.
Mahesh Krishnan is the CTO for Fujitsu in Oceania. One of the key technology area he focuses on these days is AI. He has been in leadership roles within the Tech industry for a number of years, is a frequent speaker at conferences, and has written a couple of technology books. He also used to be a Microsoft MVP for a number of years.
Karin Verspoor, PhD
Professor Karin Verspoor is Dean of the School of Computing Technologies at RMIT University. She was previously a Professor in the School of Computing and Information Systems and Deputy Director of the Health and Biomedical Informatics Centre at the University of Melbourne.
Trained as a computational linguist, Karin’s research primarily focuses on extracting information from clinical texts and the biomedical literature using machine learning methods to enable biological discovery and clinical decision support. Karin held previous posts as the Scientific Director of Health and Life Sciences at NICTA Victoria Research Laboratory, at the University of Colorado School of Medicine, and Los Alamos National Laboratory. She also spent 5 years in start-ups during the US Tech bubble, where she helped design an early artificial intelligence system.
Jayeeta is a Senior Data Scientist with several years of industry experience in Natural Language Processing (NLP), Statistical Modeling, Product Analytics and implementing ML solutions for specialized use cases in B2C as well as B2B domains. Currently, Jayeeta works at Fitch Ratings, a global leader in financial information services. She is an avid LP researcher and gets to explore a lot of state-of-the-art open-source models to build impactful products and firmly believes that data, of all forms, is the best storyteller. Jayeeta also led multiple NLP workshops in association with Women Who Code, and GitNation among others. Jayeeta has also been invited to speak at International Conference on Machine Learning (IML 2022), ODSC East, MLConf EU, WomenTech Global Conference, Data Science Salon, The Al Summit, and Data Summit Connect, to name a few. Jayeeta is also an ambassador for Women in Data Science, at Stanford University, and a Data Science Mentor at Girl Up, United Nations Foundation, and WomenTech Network where she aims to inspire more women to take up STEM. Jayeeta has been nominated for the WomenTech Global Awards 2020 and has been spotlighted in the List of Top 100 Women Who Break the Bias 2022. More information here – https://linktr.ee/JayeetaP
Emil Pastor is part of the Pre-Sales and Field Engineering team at Neo4j. Over the last ten years, Emil has been a data and AI professional enabling organisations across the globe in various industries through strategy, architecture, use case delivery, and capability building to support stakeholders and client data professionals in leveraging their data assets. Before Neo4j, Emil worked for Microsoft, Mckinsey & Company (QuantumBlack), Ernst & Young, and Teradata in a similar capacity of helping customers realise the value of digital transformation through data and AI. He has a Master’s degree in Data Science and a Bachelor’s degree in Electronics engineering.
Demo Talk Title: Building Responsible AI Apps with Neo4j Knowledge Graphs and Google Generative AI
We’ve reached an inflexion point in both the AI industry and society, and the APAC region is at the epicentre of this change. To ensure you’re at the forefront of this change, ODSC APAC is gathering leading experts from across the globe to share their knowledge through 100+ hours of hands-on training sessions, workshops, talks and more.
Join us for a deep dive into the latest data science and AI trends, tools and techniques: from LLMs to data analytics and from machine learning to responsible AI.
Peter Kilroy is a Data Science Principal Consultant at Fujistu in Australia. He specialises in delivering innovative AI and Machine Learning, end-to-end Advanced Analytics, Business Intelligence and AI capabilities to the enterprise. He comes with a strong mathematical background and over 25 years of experience in this field.
Bidyut Sarkar, a distinguished professional with a silver badge distinction in IBM for Life Science solutions and an expert in Industrial manufacturing, has made remarkable contributions to addressing global challenges through AI and Analytics-driven solutions.
Also, see the AI-related articles published at Dzone
His 20-year tenure at IBM shines with outstanding achievements, earning him prestigious awards as a leader in the solutioning function, including the ‘Client and Partner Success Award – 2023’ and ‘Growth Award -2023.’ Notably, his expertise has significantly impacted large pharmaceutical companies in the US, where he played a pivotal role in combatting counterfeit drugs, AI/ML-powered predictive demand, and automated replenishment capabilities. Leveraging AI-driven technologies, Bidyut’s solutions have enhanced cybersecurity, ensuring the authenticity and safety of medications worldwide. His career spans multiple countries, including the USA, Netherlands, Saudi Arabia, Brazil, and Australia, granting him a unique perspective on the challenges faced by global organizations. With an illustrious career spanning international borders and an exceptional understanding of Advanced Manufacturing & Supply chain transformation, Bidyut Sarkar continues to drive AI-driven solutions to tackle critical global challenges in the life sciences domain.