Dr. Michael Brand is the Head and Founder of Otzma Analytics, a Data Science consultancy dedicated to maximizing clients’ value from data by providing analytics upskilling, project review, and executive mentoring. Before founding Otzma in 2018, Dr. Brand served as Chief Data Scientist at Telstra, as Senior Principal Data Scientist at Pivotal, as Chief Scientist at Verint Systems, and as CTO Group Algorithm Leader at PrimeSense (where he worked on developing the Xbox Kinect). Dr. Brand also served as Director of the Monash Centre for Data Science in his role as Associate Professor for Data Science and AI at Monash University, where he remains an adjunct. Dr. Brand holds a Ph.D. in IT from Monash University, an MSc in Applied Mathematics from the Weizmann Institute of Science, and a BSc in Engineering from Tel-Aviv University. He has made industry-defining contributions that have earned him 18 patents (more pending), garnered many prestigious industry and academic awards, and power flagship products for the companies he worked with.
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.
Machine Learning with Spark(Tutorial)
Sowmya Vajjala currently works as a researcher in Digital Technologies at National Research Council, Canada’s largest federal research and development organization. She has worked in the area of Natural Language Processing (NLP) over the past decade in various roles – as a software developer, researcher, educator, and a senior data scientist. She recently co-authored a book: “Practical Natural Language Processing: A Comprehensive Guide to Building Real World NLP Systems”, published by O’Reilly Media (June, 2020), which was also translated into Chinese. Her research interests lie in multilingual computing and the relevance of NLP beyond research both in industry practice as well as in other disciplines, through inter-disciplinary research.
Dr. Lau Cher Han is a chief data scientist and keynote speaker in data science and A.I for major companies, organisations, and government agencies across Australia, Malaysia, Taiwan and other ASEAN countries.
He has trained and advised many of the organisations including Intel, Standard Chartered, and IBM. He is also keynote speaker in data science conferences for Microsoft, Facebook and Google. As the CEO of LEAD, Dr. Lau’s current focus is on helping clients to grow their data science teams and to gain insights by combining structured and unstructured data. He helps the clients on implementing data analytics and big data strategies, and preparing for the future big data economy.
Raghav Bali is a Senior Data Scientist at Optum(United HealthGroup), one of the world’s largest health care organizations. With about a decade’s experience working across Fortune 500 organizations such as Intel and American Express, his work involves research & development of enterprise-level solutions based on Machine Learning, Deep Learning, and Natural Language Processing for real-world use-cases. Raghav has published multiple peer-reviewed papers, has authored over 7 books, and is a co-inventor of multiple patents in the areas of machine learning, deep learning, and natural language processing.
Mathangi is a renowned data science leader in India. She has 11 Patent grants and 20+ patents published in the area of intuitive customer experience, indoor positioning and user profiles. She has recently published a book – “Practical Natural Language Processing with Python” She has 17+ years of proven track record in building world-class data sciences solutions and products. She is adept in machine learning, text mining, NLP technologies & tools. She is currently heading the data organization of GoFood, Gojek. In the past, she has built data sciences teams across large organizations like Citibank, HSBC, GE, and tech startups like 247.ai, PhonePe. She advises start-ups, enterprises, and venture capitalists on Data Science strategy and roadmap. She is an active contributor on machine learning to many premier institutes in India. She is recognized as one of “The Phenomenal SHE” by Indian National Bar Association in 2019.
NLP in Ecommerce(Tutorial)
Ravi has professional experience of eight years in AI and ML at scale with expertise in building enterprise solutions and ML Engineering. He is part of the Centre of Excellence and responsible for building ML products from inception to production. He has worked on multiple engagements with clients mainly from Automobile and Retail industry across geographies.
He holds a bachelor’s degree in Computer Science with a proficiency course in Reinforcement Learning from Indian Institute of Science. He is a certified Google Cloud Architect and Kubeflow contributor.
Archana works as an AI Engineer at Continental Automotive. Her field of work is in TinyML i.e applying machine learning models to small devices with low power and memory requirements. This means that microcontrollers excite her and she loves working in this applied AI field. After work, you can usually find her volunteering at Women Who Code, where she co-leads the cloud and python track as a Leadership Fellow. Apart from that, she actively participates in TinyML and Women in Machine Learning events.
Manprit leads Data and AI offerings and engagements at Avanade. He specialises in helping enterprises in their journey to monetise their data with AI. By adopting a multi-disciplinary, highly collaborative and interactive approach to discover, define and drive rapid value realization he sets up a longer team vision and roadmap for his clients. This helps them realize the business relevance and reality of AI. He then helps build minimum loveable prototypes for them that demonstrate quantitative benefits.
Andrew has international expertise in the areas of machine learning, statistical analysis, cloud computing and AI. He is founding member of the boutique data science consulting firm Datamahi and sports industry specialists Media Rights Value.
Learn Machine Learning on AWS SageMaker(Workshop)
Hui Xiang Chua is Senior Data Scientist at Dataiku, helping enterprises with data democratization and enabling them to build their own path to AI. Dataiku is a 2x Gartner Magic Quadrant Leader for Data Science and Machine-Learning Platforms (as of 2021).
She has both public and private experiences solving problems using data, namely over six years in the public service and two years in the media industry. She was also previously an instructor with General Assembly.
In 2017, she was accepted to the Data Science for Social Good Fellowship and was mentored by Rayid Ghani, Chief Scientist of the Obama for America campaign in 2012. For bringing data science into a high school’s curriculum, Hui Xiang was a recipient of the KDD Impact Program award by SIGKDD, the Association for Computing Machinery’s special interest group on knowledge discovery and data mining. She also runs a data science blog called Data Double Confirm that was recognised as 2018/2019 Top 100 Data Science Resources on MastersInDataScience.com.
Hui Xiang holds a B.Sc.(Sons) in Statistics and M.Sc. in Business Analytics from National University of Singapore.
Seng-Beng Ho is currently Senior Scientist & Deputy Director, Department of Social & Cognitive Computing, Institute of High Performance Computing, Agency of Science, Technology & Research, Singapore. He obtained his Ph.D. in Cognitive Science (AI, Neuroscience, Psychology, & Linguistics) and M.Sc. in Computer Science from the University of Wisconsin, Madison, U.S.A. He has a B.E. in Electronic Engineering from the University of Western Australia. He is the author of a monograph published in June 2016 by Springer International entitled “Principles of Noology: Toward a Theory and Science of Intelligence”. In the book, he presents a principled and fundamental theoretical framework that is critical for building truly general AI systems. Prior to the current position, for 11 years he was President of E-Book Systems Pte Ltd, an e-book Technology company he founded with offices in the Silicon Valley, Beijing, Tokyo, Germany, and Singapore. The company developed and marketed a patented, novel 3D page-flipping technology platform for e-book. Prior to that, he lectured and conducted research on AI and Cognitive Science at the Department of Information Systems and Computer Science, National University of Singapore. He holds 36 U.S. and world-wide patents related to e-book technology and has published more than 30 papers in the field of AI since returning from industry.
Chaine San Buenaventura is a Lead Machine Learning Engineer at WizyVision. Her team, awarded as 2021 Startup of the Year in France by EUROCLOUD France, focuses on the adoption of computer vision models across Google Cloud Platform products and services for use cases relating to frontline workers. She received her master’s degree from the University of the Philippines Diliman in June 2018. Her graduate research was on Smartphone-Based Human Activity Recognition (HAR) for Ambient Assisted Living (AAL). Charlene is currently specializing in Deep Learning applied to Computer Vision and Natural Language Processing. She has numerous publications and has many years of experience in deep learning research, development and engineering.
Ian Hansel is a Director of Verge Labs, a company empowering businesses through Machine Learning and Artificial Intelligence. Verge Labs bridges the gap between business and cutting-edge research applications. Ian has lead data teams in corporates and believes in taking away the complexity of machine learning to show people how to use amazing technology on their own.
Network Analysis App in Python(Workshop)
Pavithra is a software engineer and technical writer with over a year of experience in FOSS. She enjoys working at the intersection of technology and education, especially on outreach.
Data Science and Machine Learning At Scale(Half-Day Training)
Mausam is the founding head of School of Artificial Intelligence, along with being a Professor of Computer Science at IIT Delhi. He is also an affiliate professor at University of Washington, Seattle. With a twenty year research experience in artificial intelligence, he has, over time, contributed to many research areas such as large scale information extraction over the Web, AI approaches for optimizing crowdsourced workflows, and probabilistic planning algorithms. More recently, his research is exploring neuro-symbolic machine learning, computer vision for radiology, NLP for robotics, multilingual NLP, and several threads in intelligent information systems that include information extraction, knowledge base completion, question answering, summarization and dialogue systems. He has over 100 archival papers to his credit, along with a book, and two best paper awards. Mausam was awarded the AAAI Senior Member status in 2015 for his long-term participation in AAAI and distinction in the field of artificial intelligence. He has had the privilege of being a program chair for two top conferences, AAAI 2021, and ICAPS 2017. He was ranked the 65th most influential AI scholar and 71st most influential NLP scholar for the last decade by ArnetMiner. He received his PhD from University of Washington in 2007 and a B.Tech. from IIT Delhi in 2001.
Yiliang is VP, Head of Data Science with Openspace Ventures, where he is helping OSV’s portfolio companies to be more successful in machine learning and data science operation. He is also teaching applied machine learning courses in NUS and SMU as adjunct faculty. Yiliang has 10+ years of experience in managing and developing end-to-end machine learning projects from ideation to production. He has broad knowledge in predictive modelling, machine learning, natural language processing (NLP) and computer vision (CV). He has solid background in fundamentals of computer science, rich hands-on experience in complete software product development, solid software engineering capabilities and deep understanding of big data system, architecture and optimization. He has extensive experience in driving effective digital transformation using AI/machine learning to derive business insights and make intelligent decisions with quantifiable business impact. Prior to joining OSV, Yiliang was J/APAC Machine Learning Practice Lead with Google Cloud, where he led the ML practice group, oversaw machine learning pipelines and managed training/enablement programs/initiatives in the region. He worked with multinational industry leaders including Fast Retailing, Netmarble, AirAsia, AU Optronics and UOB on various machine learning projects. Yiliang also had extensive experience working in Singapore government as data scientist and tech lead, helping government agencies to solve machine learning and data related problems. Working as a senior data scientist and tech lead at Shopee, Yiliang gained practical understanding of how B2C/C2C ecommerce works in south-east Asia, the related challenges and how data and machine learning can be used to tackle these problems. Yiliang has a Ph.D. in Computer Science from NUS and a B.Eng degree in Computer Engineering from NTU with 1st Class Honours.
MLOps: From Model to Production(Workshop)
Kishore is a hands-on leader with deep interest in leveraging Technology, Data & Machine Learning to identify, communicate & solve Business problems – essentially, Applied Data Science.
He has worked across Healthcare, Retail, eCommerce, Financial Services. Established, grew applied data science teams for more than a decade since his MBA in IT & Operations from IIM Calcutta.
In this process, he has filed 11 patents at the intersection of Machine Learning, Healthcare, and Operations & has written 4 books on ML & Deep Learning.
Debanjana is a Senior Data Scientist at Walmart Labs with 4+ years of experience in tech. At Walmart, she has been instrumental in developing ML-driven solutions in the compliance space dealing heavily in Natural Language Processing, Mixture Models and Rare Time Series. Currently, her focus is on building an AI to enable automated shelf curation for creative content on Walmart.com. She has filed 5 US patents in the field of Clustering & Anomaly Detection, Imbalance Text Classification and Stochastic Processes. In addition, she has three published papers to her credit. Debanjana has a master’s degree in Statistics from Indian Institute of Technology (Kanpur).
Finding Rare Events in Text(Workshop)
Danny is the Founder and CEO of Sydney Data Science and has over 10 years of experience in the data industry. He has held almost every role in the data ecosystem from data entry to campaign analyst, data scientist, data engineer and machine learning engineer. His core expertise is in data analytics, supervised ML algorithms, data architecture and designing digital data systems for retail, banking and financial markets. Danny’s passion is to guide businesses and individuals on their data & machine learning journey. He currently runs the Data With Danny community with over 8,000 aspiring data professionals and is working on his vision of creating a scalable virtual data apprenticeship program to empower others to kickstart their career in data.
SQL Masterclass for Data Scientists(Half-Day Training)
Sunil is a senior analytics consultant, Education at SAS India. He is a SAS certified data scientist and in his current role, Sunil works with various clients of SAS in the Asia Pacific region to develop workforce in effective use of the SAS products in machine learning, artificial intelligence, data management and Business data visualization. He is also engaged in Industry specific solution mentoring in Financial Services, Insurance, Manufacturing, and Telecommunication.
Yeshwanth Reddy is a data scientist with prior teaching experience in INSOFE. He has completed his M.Tech and B.Tech from IIT Madras.
Vaishali is a lead data scientist at Indium Software, a leading digital engineering company. She has 7 years of experience in predictive modeling and data analysis. She designs and develops enterprise-grade solutions based on Machine Learning, Deep Learning, and Natural Language Processing for real-world use cases. As a technology evangelist, Vaishali also coaches aspiring professionals on data science and machine learning at Simplilearn, the world’s leading training boot camp. Vaishali holds a professional postgraduate degree in Artificial Intelligence and Machine Learning. She loves cracking Machine Learning Hackathons and has been a winner in many such events.
Supervised Machine Learning using Python(Half-Day Training)
Jonathan is on a mission to help businesses generate value through data. As a Senior Data Engineer at Cuusoo (Mantel Group), he empowers organisations with the technology, skills and processes to unleash insights from big data. Outside of his nine-to-five, Jonathan trains and upskills the next generation of data professionals as the Instructor of the Data and Analytics Bootcamp at The University of Western Australia.
The field of artificial intelligence (AI) has seen several proposals for modeling intelligent computation. Two of the most popular ones are (1) neural – which is inspired by the structure of our brain and consists of millions of nodes resembling neurons connected in a network, and (2) symbolic – which uses the formalism of logic to make inferences from known facts. While deep neural models have revolutionized the field of AI in modern times, an emerging body of work combines neural models with symbolic computation to achieve the best of both worlds. In this introductory tutorial, we briefly present some of this literature in the context of (1) augmenting neural models by incorporating additional symbolic knowledge, (2) designing neural models for solving symbolic reasoning problems, and, (3) neuro-symbolic architectures for solving perceptual-reasoning tasks.
Opportunities to form working relationships with some of the world’s top data scientists for follow-up questions and advice.
Access to 40+ training sessions and 70+ workshops.
Hands-on experience with the latest frameworks and breakthroughs in data science.
Affordable training–equivalent training at other conferences costs much more.
Professionally prepared learning materials, custom- tailored to each course.
Opportunities to connect with other ambitious, like-minded data scientists.