ODSC APAC 2021

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.

David serves as an advisor to the Data Science curriculum team at Heicoders Academy, a fast-growing tech education training provider based in Singapore. Before that, he co-founded another renowned tech education company in Singapore, Hackwagon Academy. Previously a Machine Learning Engineer at Droice Labs, a New-York based AI company in the healthcare sector, David has multiple technical consulting experiences under his belt, including a 1-year stint with Louis Vuitton in the US. He has a Master of Management Science & Engineering from Columbia University, and a Bachelor of Information Systems from Singapore Management University, where he graduated as a valedictorian. In his free time, fueled by his passion to democratise data science, David contributes articles to Medium on topics like workplace automation and machine learning techniques.

Dr Michael Brand is the Head and Founder of Otzma Analytics, a Data Science consultancy dedicated to maximising 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 PhD 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.

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.

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.

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.

Ravi Ranjan is working as Senior Data Scientist at Publicis Sapient. He is part of the Centre of Excellence and responsible for building a machine learning model at scale. He has worked on multiple engagements with clients mainly from Automobile, Banking, Retail, and Insurance industry across geographies.
In the current role, he is working on a Hyper-personalized recommendation system for the Automobile industry focused on Machine Learning, Deep learning, Realtime data processing on large scale data using MLflow and Kubeflow. He holds a bachelor’s degree in Computer Science with a proficiency course in Reinforcement Learning from IISc, Bangalore. 

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.

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.

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.

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.

Yatin is a PhD scholar in the area of Machine Learning and Artificial Intelligence, guided by Mausam and Parag Singla at Computer Science and Engineering Department, Indian Institute of Technology Delhi. Prior to joining the PhD program in 2017, he worked in the quantitative finance industry for 10 years. During the last five years of his professional stint, he was busy making high frequency trading strategies at Estee Advisors, trading primarily in stock, index and currency options. Yatin started my career in 2007 with the Equity Quantitative Analytics team at Lehman Brothers, which was eventually bought by Nomura after its bankruptcy in 2008. He did his graduation in Mathematics and Computing, a five year integrated M.Tech programme offered by Mathematics Department at IIT Delhi.

Nilav is a Manager, Data Scientist in Optum with a focus on architecting and deploying ML models at enterprise scale – on premise and cloud. He has over a decade of experience in designing and developing engineering and AI solutions in finance and healthcare industries. In his stint at Optum, he has worked on productizing deep learning models in the areas of computer vision and NLP and has filed 4 patents in these areas. He holds an M.S in Computer Science from Georgia Tech. His other passions are consulting on system & architecture design and technology training. He has trained 1k+ engineers around the globe on Python and Machine Learning. In his free time, he loves developing his chess skills.

Jonathan is an Analytics Engineer at Canva where he is building data platforms to empower product teams to unlock insights from millions of users.
He has previously worked at EY, Telstra Purple, and Mantel Group, where he has led data engineering teams, built data engineering platforms for ASX-100 customers, and developed new products and businesses. Since 2020, Jonathan has trained over 100 students through data analytics bootcamps and courses. In 2022, he founded Data Engineer Camp, a 14-week data engineering bootcamp that empowers professionals to become data engineers with the modern data stack.
He also hosts the Perth Data Engineering monthly meetup group with over 300 members.

Eram is a Lead Data Scientist at Tokopedia, which is an Indonesian e-commerce giant encompassing 1% of Indonesia’s GDP. With over 7 years of experience in Machine Learning specializing in Natural Language Processing, her work has been focused on developing real world AI at scale. Her passion for NLP has led her to become a content creator and a mentor for junior data scientists. Her motto is to give back to the NLP community by instilling self motivated learning.

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.

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.

Danny is the founder and CEO of Sydney Data Science, an Aussie tech startup. Danny is also very passionate about mentorship and runs the Data With Danny online community with over 2,500 like-minded aspiring data professionals. Outside of work, Danny enjoys audiobooks, making various types of tea & coffee, and taking care of his house plants.

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).

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.(Hons) in Statistics and M.Sc. in Business Analytics from National University of Singapore.

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.

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.

John leads Program Management for Microsoft Azure AI and is responsible for designing products and services that data scientists and ML experts around the world love and use. He leads a team of program managers, researchers, and designers responsible for products and services including Azure Machine Learning, Azure Cognitive Services, ML.NET, and ONNX Runtime. Prior to this role, John has led the Program Management team for Microsoft’s Developer Division, including Visual Studio, Visual Studio Code, and Azure Notebooks. He has also held positions as director of marketing for Visual Studio, as well as a program manager for Microsoft’s participation in several standards organizations, including ISO, IETF, and ECMA. Prior to joining Microsoft in 1998, John worked as a writer and editor for several computer and technology publications, including BYTE Magazine, PC/Computing, and Corporate Computing, as well as being the Chief Information Officer for Imagine Publishing.

Emma Ning is a Senior Product Manager in the AI Framework team under Microsoft Cloud + AI Group, focusing on AI model operationalization and acceleration with ONNX/ONNX Runtime for open and interoperable AI. She has more than five years of product experience in search engines taking advantage of machine learning techniques and spent more than three years exploring AI adoption among various businesses. She is passionate about bringing AI solutions to solve business problems as well as enhancing product experience.

Geeta Chauhan leads AI Partnership Engineering at Facebook AI with expertise in building resilient, anti-fragile, large-scale distributed platforms for startups and Fortune 500s. As a core member of the PyTorch team, she leads TorchServe and many partner collaborations for building a strong PyTorch ecosystem and community. She is a winner of Women in IT – Silicon Valley – CTO of the year 2019, an ACM Distinguished Speaker and thought leader on topics ranging from Ethics in AI, Deep Learning, Blockchain, IoT. She is passionate about promoting the use of AI for Good.

Ben Taylor has over 16 years of machine learning experience. After studying chemical engineering, Taylor joined Intel and Micron and worked in their photolithography, process control, and yield prediction groups. Pursuing his love for high-performance computing (HPC) and predictive modeling, Taylor joined an artificial intelligence hedge fund (AIQ) as their HPC/AI expert and built out models using a 600 GPU cluster to predict stock movements based on the news. Taylor then joined a young HR startup called HireVue. Taylor built out their data science group, filed 7 patents, and helped to launch HireVue’s AI insights product using video/audio from candidate interviews. That work allowed Taylor’s team of PhD physicists to help pioneer anti-bias mitigation strategies for AI. In 2017 Taylor co-founded Zeff.ai with David Gonzalez to pursue deep learning for image, audio, video, and text for the enterprise. Zeff was acquired by DataRobot.

Alicia Frame is the lead product manager for data science at Neo4j. She’s spent the last year translating input from customers, early adopters, and the community into the first truly enterprise product for doing data science with graphs: Neo4j’s Graph Data Science Library. She has a Ph.D. in computational biology from UNC Chapel Hill, and her background is in data science applications in healthcare and life sciences.

She’s worked in academia, government, and the private sector to leverage graph techniques for drug discovery, molecular optimization, and risk assessments — and is super excited to be making it possible for anyone to use advanced graph techniques with Neo4j.

Dr. Denis Bauer is an internationally recognised expert in artificial intelligence, who is passionate about improving health by understanding the secrets in our genome using cloud-computing technology. She is CSIRO’s Principal Research Scientist in transformational bioinformatics and adjunct associate professor at Macquarie University. She keynotes international IT, LifeScience and Medical conferences and is an AWS Data Hero, determined to bridge the gap between academe and industry. To date, she has attracted more than $31M to further health research and digital applications. Her achievements include developing open-source bioinformatics software to detect new disease genes and developing computational tools to track, monitor and diagnose emerging diseases, such as COVID-19.

Tim Baldwin is a Melbourne Laureate Professor in the School of Computing and Information Systems, The University of Melbourne, and also Director of the ARC Centre for Cognitive Computing in Medical Technologies and Vice President of the Association for Computational Linguistics. His primary research focus is on natural language processing (NLP), including social media analytics, deep learning, and computational social science.

Tim completed a BSc(CS/Maths) and BA(Linguistics/Japanese) at The University of Melbourne in 1995, and an MEng(CS) and PhD(CS) at the Tokyo Institute of Technology in 1998 and 2001, respectively. Prior to joining The University of Melbourne in 2004, he was a Senior Research Engineer at the Center for the Study of Language and Information, Stanford University (2001-2004). His research has been funded by organisations including the Australia Research Council, Google, Microsoft, Xerox, ByteDance, SEEK, NTT, and Fujitsu, and has been featured in MIT Tech Review, IEEE Spectrum, The Times, ABC News, The Age/SMH, Australian Financial Review, and The Australian. He is the author of well over 400 peer-reviewed publications across diverse topics in natural language processing and AI, with over 16,000 citations and an h-index of 60 (Google Scholar), in addition to being an IBM Fellow, ARC Future Fellow, and the recipient of a number of best paper awards at top conferences.

Elena Neroslavskaya – AI Frameworks Program Manager at Microsoft focusing on Open Source frameworks for AI. Elena is passionate about all things Cloud Native and AI and helping developers and data scientists be more efficient. She has 20+ years in IT – building large scale distributed systems, microservices, AI and cloud native applications. Elena holds Master in Computer Science majoring in AI.

Coming Soon!

Geeta Chauhan leads AI Partnership Engineering at Facebook AI with expertise in building resilient, anti-fragile, large-scale distributed platforms for startups and Fortune 500s. As a core member of the PyTorch team, she leads TorchServe and many partner collaborations for building a strong PyTorch ecosystem and community. She is a winner of Women in IT – Silicon Valley – CTO of the year 2019, an ACM Distinguished Speaker and thought leader on topics ranging from Ethics in AI, Deep Learning, Blockchain, IoT. She is passionate about promoting the use of AI for Good.

In Jacky’s twenty plus years with SAS, she has served in various roles including Pre-Sales Support, Business Development, Analytical Consulting, and Consulting Management. These roles included SAS offices in Chicago, Denver, and Melbourne. Jacky has implemented Analytic Lifecycle solutions with large banks in Brazil and Ireland, several telecoms in the US and Philippines, a Korean semiconductor manufacturer and multiple government agencies to name a few. These solutions include all stages of the ModelOps process including model performance monitoring, standardization of the life cycle processes, assistance with regulatory compliance and workflow development. Jacky holds an MBA in Economics from the University of Chicago Graduate School of Business and a Bachelors degree in Quantitative Analysis from the University of Cincinnati, resulting in a highly effective blend of mathematics and business knowledge.

Dr. Shailesh Kumar is currently the Chief Data Scientist at the Centre of Excellence in AI/ML, Reliance Jio. Prior to this he worked as a Distinguished Scientist at Ola cabs, Chief Scientist and Co-founder of Third Leap, an EdTech startup, Researcher in the Google Brain team, Sr. Scientist at Yahoo! Labs and Principal Scientist at Fair Isaac Research.

Dr. Kumar has 18 years of experience in building AI solutions in a variety of domains including Web, Retail, Finance, Remote Sensing, Fleet Management, Computer Vision, Knowledge Graph, and Conversational computing. He has published over 20 international papers and book chapters and holds more than 20 patents in AI/ML. He was recognised as one of the top 10 data scientists in India in 2015 by Analytics India Magazine. Dr. Kumar holds a Masters and PhD in AI from UT-Austin and B.Tech. in Computer Science from IIT-Varanasi.

Saurya Das is a PM in the Azure ML organization focused on the Hybrid strategy and Kubernetes.

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.

Tony is a Senior Presales Consultant in APAC. He joined the Neo4j family in January 2021. Prior to joining Neo4j, he worked at SAXOBank as a System Architect for an online trading platform. Before that, he spent 5 years at VMWare as a Senior Solution Architect designing and validating solutions on vSAN with a variety of Databases (such as Microsoft SQL Server, OracleDB, MongoDB) orchestrating on top of virtual machines or docker and Kubernetes containers. He also has been with Huawei, EMC, and Microsoft in his 17 years in technical customer facing roles in IT. Tony comes with a PhD in Control/Graph Theory and Engineering from the University of Shanghai, China. He is based in Shanghai with his wife and two sons.

Besmira Nushi is a researcher in the Adaptive Systems and Interaction group at Microsoft Research. Her interests lie at the intersection of human and machine intelligence focusing on Reliable Machine Learning and Human-AI Collaboration. In the last five years, she has made practical and scientific contributions on implementing and deploying Responsible AI tools for debugging and troubleshooting ML systems. Prior to Microsoft, Besmira completed her doctoral studies at ETH Zurich in 2016 on optimizing data collection processes for Machine Learning.

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.

During her Bachelor of Economics in Buenos Aires, Argentina, Maggie learned to see the world from the lens of mathematics and statistics. She then started teaching herself how to code out of curiosity, got a job as a Junior Software Engineer in Sydney, Australia, and went on to do a Master of Software Development to further develop her skills. She completed her Masters degree with a research project involving some cute Pepper robots at UTS’ Social Robotics Lab – which won RoboCup’s Home category in 2019. Throughout the years, Maggie has dipped her toes in various industries, from business development and digital marketing at Google to not-for-profit, banking, autonomous vehicles and more recently quantum technology. She has practical experience applying deep reinforcement learning techniques to quantum control problems and then deploying her research to production for customers to enjoy. Maggie is involved with various nonprofits that teach coding to people of all ages, with a focus on teenage girls. She suspects that if she had had that level of exposure to computer science during high school, it would have captivated her right away. That’s Maggie’s wish for future generations – but she also reminds us that it’s never too late!

Vijay has about 15+ years of experience in the data world. Vijay is currently a Senior Sales Engineer with Imply (Imply offers commercial enterprise support for open source druid). In this role, Vijay is focused on helping customers in APAC use the Imply platform (based on Apache druid). Before Imply, Vijay was with cloudera for two years helping cloudera partners position and use the cloudera platform. Before Cloudera, Vijay spent 10 years with Informatica where he was part of the team that put together connectivity for informatica cloud.

Fanghua (Joshua) Yu joined Neo4j since late 2017, and is now leading the sales engineer team for APAC region. During Joshua’s 20 years of career in IT, he has taken various roles as a developer, database designer, technical lead, consultant and solution architect. He also has extensive experience in banking and financial industry for over 11 year, with expertise in data and analytics, core banking systems, payments, application and integration architecture. Joshua has a PhD degree in Computer related subject, and now lives in Melbourne Australia.

Dr. Nathan’s accomplishments resulted in him being named as one of Australia’s Most Innovative Engineers by Engineers Australia & as one of Australia’s and the US’ Top Ten Young Scientists by Popular Science magazine, along with receiving a number of other international awards and recognitions. Dr. Nathan is the Founder | CTO at Presien – cutting edge AI vision systems, a Special Advisor for Robotics | Ventures at one of the world’s larger private construction companies, a Director of the Robotics Australia Group peak body & sit on the Advisory Board of Queensland Robotics. He is an active academic researcher in robotics as an Honorary Professor at the Ohio State University. Previously he has served multiple academic appointments at Stanford University and the University of Technology Sydney.

Dr. Nathan’s speciality is uncovering and imagining opportunities for emergent future technologies in the real world and forging viable R&D to Delivery pathways to their realisation. One of his multi-award winning portfolio projects – Blindsight by Presien (formerly Toolbox Spotter) AI computer vision for heavy industries – recently evolved into a $7m VC funded spinoff. He has over 15+ years in industry, and 10+ years in academia, initiating, shaping, driving and leading cutting-edge, research driven disruptive innovation.

Lizzie has significant experience applying her research in causal inference from observational data to real world problems. Her work has centered on the medical industry, with projects also in education, psychology and social enterprise. She received her PhD in Logic, Computation, and Methodology from Carnegie Mellon University and Master of Science in Machine Learning.

Simon has substantial experience as a software engineer across multiple platforms and industries. He applies his engineering and science studies to his specialisations in backend software development, data architecture and machine learning. He received his BEng (EEE) (Hons), GradCertSci (Physics) from Adelaide University.

Sunny is a seasoned professional data scientist, with over 15 years of relevant experience, and successful completion of significant company-onsite projects for many respected companies in South Korea and the US. Significant experience and dynamic practitioner in various domains, including NLP project lead, credit risk modeling, financial distress modeling, customer marketing prediction, and ML service provider consultation. She is passionate about creating and building AI solutions applying a variety of NLP technologies including sentiment analysis, conversational computing, topic modeling, etc. to support AI real-world usages for SME businesses. She is currently putting her efforts into her own AI start-up company – ReviewMind Inc. In 2020, her company was identified as an excellent start-up case by Korea Women in Science and Technology Support Center. Sunny and her team also won the best award in the 2021 Start-up Demo Day from the Korea Institute of Startup & Entrepreneurship Development. Sunny holds both a Masters in Data Science (Information Systems) and an MBA from the US and South Korea respectively.

Ramakanteswara is a medtech innovator/Biodesigner with primary research expertise in medical robotics, computational medical imaging, machine learning/AI and HFID (human factor and industrial design). He worked and developed medical technologies for therapy in both robotic surgery and interventional medicine as well as diagnosis using imaging, sensing and molecular methods. Ramakanteswara started medtech journey with a low-cost vein visualizer at Stanford-India Biodesign at AIIMS. As a research fellow in Robotic surgery at IRCAD and went on developing an augmented reality wearable device for sub-surface visualization. He also worked on navigation system for hip-replacement and camera-projector technology for spinal surgery. Ramakanteswara has total eight years of experience in medtech industry starting with Bosch to build medical technologies in diagnostics space as a strategy lead for R&D and innovation for their new venture in healthcare. Ramakanteswara developed multiple devices in ophthalmic imaging & diagnostics and in molecular imaging and diagnostics. He developed multiple AI algorithms for Diabetes Retinopathy and dry eye. He later moved to Boston Scientific working on interventional devices in cardiology, GI endoscopic procedures and urology. He led as specialist for clinical insights, technology and innovation. He worked in setting up computational biomechanics and Human Factors labs at Boston Scientific. Presently working with Novartis as an Innovation lead building medical technologies that can be companion devices with drugs and digital technologies for drug development. He is a trained physician with medical graduation (MBBS) from Andhra medical College and did engineering (MD equivalent) from IIT Kharagpur. He has around 10 patents applied or granted in medtech space.

Dr. Sriparna Saha is currently an Associate Professor in the Department of Computer Science and Engineering, Indian Institute of Technology Patna, India. She is the author of a book published by Springer-Verlag. She has authored or coauthored more than 290 papers. Her current research interests include deep learning, natural language processing, machine learning, information extraction, text mining, bioinformatics, and multiobjective optimization. Her h-index is 28 and the total citation count of her papers is 4938 (according to Google scholar). She is also a senior member of IEEE. Her name is included in the list of eight leading women scientists in the area of AI in India published by INDIAai which is the National AI Portal of India – a central hub for everything AI in India and beyond, a joint initiative of MeitY, NeGD, and NASSCOM, the website aims to be the trusted content powerhouse in the backdrop of India’s journey to global prominence in Artificial Intelligence. Her name is also included in the list of the top 2% of scientists of their main subfield discipline (Artificial Intelligence and Image Processing), across those that have published at least five papers ( a survey conducted by Stanford University). She is the Associate Editors of IEEE/ACM Transactions on Computational Biology and Bioinformatics, Expert Systems with Applications, PLOS ONE, and IEEE Internet Computing journal. She is the recipient of the Lt Rashi Roy Memorial Gold Medal from the Indian Statistical Institute for outstanding performance in MTech (computer science). She is the recipient of the Google India Women in Engineering Award, 2008, NASI YOUNG SCIENTIST PLATINUM JUBILEE AWARD 2016, BIRD Award 2016, IEI Young Engineers’ Award 2016, SERB WOMEN IN EXCELLENCE AWARD 2018, and SERB Early Career Research Award 2018. She is the recipient of DUO-India fellowship 2020, Humboldt Research Fellowship, Indo-U.S. Fellowship for Women in STEMM (WISTEMM) Women Overseas Fellowship program 2018 and CNRS fellowship.

Ritesh is currently working as an Associate Director – Data Science, Analytics and Digital at Novartis Pharmaceuticals US. Ritesh is a data science leader with ~ 12 years of work experience in Advanced Analytics, AI, Digital Strategy, and Product development/management across domains such as Travel, Pharma, BFSI, Retail, Automobile & FMCG. He has spent most of his career acting as an Analytics solutions consultant, a bridge between the data science, technology, and business teams, Leveraging functional expertise, ensuring free flow of information and timely delivery. He has engaged with key stakeholders in effectively integrating and synthesizing the data to build a complete, cohesive picture. His extensive consulting experience in different geographies i.e., USA, UAE, and Canada, helps him perform in a challenging environment. An IIM B alumni, he has worked with Fortune 30 companies like Lowes in USA and built the analytics team/infrastructure for companies like CarDekho and Yatra online. Very active on the Indian Analytics scene, Ritesh has been one of the speakers at multiple analytics conferences and college events. A National Geographic Moments photograph awards winner, he likes to click photographs and write short stories in his free time.

Nitin Ranjan Sharma has joined Novartis’s Hyderabad office on Feb 2021 as Manager. Nitin has a Data Science consulting experience with wide array of knowledge in Retail and Finance domain with 8+ years of industry experience and was involved in product development improving efficiencies and monetary output of the firms He has the technical skillsets ranging in Statistics, Machine Learning and Deep Learning (NLP and Computer Vision space) Prior to joining Novartis, Nitin worked with Publicis Sapient, EY and TGS. He has completed his B.Tech from MCKV Institute of Engineering (WBUT)

Soutir Chakraborty has joined Novartis’s Hyderabad office in August 2016 as an Analyst and got promoted to Senior Analyst in September 2018 and Manager in 2020. He is an experienced professional offering 5 years of in Deep Learning, NLP, Marketing Mixed Models, Optimization Scenario runs, Predictive Analytics, Test Control Design and Campaign Evaluation Methodology. Soutir is currently providing his expertise on Deep Learning and NLP. In past, he managed the entire process Marketing Mix Model and Optimization Scenarios for US GenMeds. He also played a pivotal role in Digital Medicines while working on Test Control Designs and Campaign Evaluation Methodology. Soutir holds a Masters degree from Indian Statistical Institute, Kolkata . Soutir holds a Bachelors degree from West Bengal University of Technology, West Bengal.

Sauradeep Debnath has joined Novartis’s Hyderabad office in Feb 2020 as an Analyst. He has 4 years of experience in NLP, Computer Vision, Image Processing, and other fields of Data Science/analytics. Sauradeep played a crucial role in RAinBOW Clustering project for Japan Hematology–a project which won on the Highest Award for Novartis Global Oncology (BOLD4CURE 2021). He worked in Phase 1 of Deep Learning Implementation of the MATCH Project Sauradeep has worked extensively on the Veeva Survey Analysis for Inclisiran – and worked with Topic Modelling & Keyphrase Extraction there, apart from building the Text Cleaning Pipeline. Prior to joining Novartis , he worked with Oracle. Sauradeep is currently pursuing M.Tech. in Data Science from IIT Hyderabad. He holds a Bachelors degree (in ECE) from NIT Jaipur.

Angela is an AI Professional specialised in Ethics, Explainability, Diversity & Inclusion in AI and recipient of Top 10 Analytics Leaders 2020 From Institute of Analytics Professional Australia and also sits on the Founding Editorial Board of Springer’s new & timely AI and Ethics Journal.
Angela has been working with Insurance Australia Group, Macquarie Group, Microsoft and Salesforce to provide AI outreach programs for high schools and also Technology Literacy programs for USYD, UNSW, UTS and Macquarie University Business female students for 100 Girls 100 Futures Workshop.
In 2018, Angela and her team won the Data Science & AI National Industry Innovation Awards for “Best Industry Application of AI for AI & Data driven Underwriting Engine” through a collaborative ANZ Wealth (Zurich Insurance) & University of Technology of Sydney project. Angela works with STEM class in high school, Women in Business in major universities in Sydney and Women in technology at Macquarie Group to promote Diversity and Inclusion in technology and Ethics, Fairness and Responsibility in AI.

Alex has 17+ years’ experience developed across a number of industries and domains, including Federal and State government, Insurance, Asset Management, Banking (Investment and Retail), Consulting and Academia. He has expertise in leveraging Data Science/AI to deliver impact and change, by developing and managing high-performance teams, and via strategic advisory and technical expertise. Alex has recently been recognised as one of the Top 10 Analytics Leaders in Australia by IAPA (Institute of Analytics Professionals of Australia).

You can follow Alex on Twitter (@DrAlexAntic) or his blog (https://impartiallyderivative.com).

In two decades in the data management industry, Paige Roberts has worked as an engineer, a trainer, a support technician, a technical writer, a marketer, a product manager, and a consultant.
She has built data engineering pipelines and architectures, documented and tested large scale open source analytics implementations, spun up Hadoop clusters from bare metal, picked the brains of some of the stars in the data analytics and engineering industry, championed data quality when that was supposedly passé, worked with a lot of companies in a lot of different industries, and questioned a lot of people’s assumptions.
Now, she promotes understanding of Vertica, MPP data processing, open source, high scale data engineering, and how the analytics revolution is changing the world.

Adam Gibson is the founder of Skymind.io and is a deep­ learning specialist based in San Francisco assisting Fortune 500 companies, hedge funds, PR firms and startup accelerators with their machine learning projects. Adam has a strong track record helping companies handle and interpret big real­-time data. Adam has been a computer nerd since he was 13 and actively contributes to the open­ source community.

Jianshu is Head of Federated Learning at AI Singapore where he leads team to develop a platform to support Federated Learning, a new paradigm of privacy-preserving Machine Learning. As a national initiative, AISG brings together the strength of AI research bodies in Singapore’s Autonomous Universities and research institutes, together with the vibrant ecosystem of AI start-ups and companies developing AI products, to perform use- inspired research, create innovative AI solutions, and develop the talent to power Singapore’s AI efforts.
Jianshu has many years of AI/Data Science research and consulting experience. In recent years, he has spent most of his time in putting AI/ML into real-world usage and promoting ethical aspects of AI/ML, e.g. explainability, fairness, robustness, and privacy- preserving AI/ML models. Before joining AISG, he was the Head of Insights and Modelling of a leading global reinsurer where he led his team to deliver a number of significant data science projects for their key clients in the Asia Pacific region..
Jianshu obtained his Ph.D in Computer Science from Nanyang Technological University (NTU), Singapore in 2008.

Rowel Atienza is a Professor and Scientist at the Electrical and Electronics Engineering Institute of the University of the Philippines, Diliman. He holds the Dado and Maria Banatao Institute Professorial Chair in Artificial Intelligence. He received his MEng from the National University of Singapore for his work on an AI-enhanced four-legged robot. He finished his Ph.D. at The Australian National University for his contribution on the field of active gaze tracking for human-robot interaction. Dr. Atienza is the author of Advanced Deep Learning with TensorFlow 2 and Keras. His current research work focuses on robotics, computer vision and AI.

Min Yan is a Quantitative Researcher at Credit Suisse, where she utilises cutting-edge machine learning and statistical models to optimise automated trading strategies. Before that, she worked in various Artificial Intelligence startups such as SWAT Mobility and KeyReply, on geospatial optimisation problems and multilingual Natural Language Processing models for context-aware chatbots. She was also part of Yahoo’s Search and Advertisement Platforms team in Silicon Valley, where she built distributed algorithms trained with deep neural networks on Tensorflow and Spark.

During her graduate studies at Carnegie Mellon University, Min Yan’s research was focused on developing AI-driven innovative sensing systems under the Human-Computer Interaction Institute. She has authored papers on extending the capabilities of wearable sensors and computer vision systems for health sensing, and using clustering algorithms to provide semi-automated feedback on programming assignments. Currently, Min Yan also leads the team of Data Science Instructors at Heicoders Academy, a renowned technology education institution based in Singapore. She has a deep passion for education and seeks to make AI education accessible to the layperson.

Debashish is ex-Deloitte Consulting Managing Director and has more than two decades of experience in A variety of emerging technologies of IR4.0 specifically in data science and artificial intelligence. Currently he heads Innovation and Strategy at GDD India, aimed to provide thought leadership, enable and execute some of the marquee, transformative and strategic initiatives of Novartis. Instrumental in establishing the corporate innovation accelerator – Biome in India for Novartis – which aim is to provide collaboration opportunities with the start-up ecosystem. Deba has extensive work experience in many geographies including, USA, South Korea, Australia, UK, Germany, Denmark and India. He is a voracious reader, traveler and speaker. His publications and thought ware, has been recognized by many industry and academic conferences across India, Japan and USA. Deba has received many industry accolades e.g. Golden Leadership award in 2016 from Amity University. Analytics India Magazine has named him as one of the top 10 analytics and data science leader in India. He is also serving as a Board of Advisor for TropoGo- a first of its kind – Drone Marketplace start-up. Deba serves as an Industry Advisor for Indian School of Business (ISB).

Aditya Kanade is an Associate Professor at the Department of Computer Science and Automation of the Indian Institute of Science. He completed his PhD at IIT Bombay and post-doc at the University of Pennsylvania. His research interests span machine learning, software engineering and automated reasoning. He has received an ACM best paper award, a teaching excellence award, and faculty awards from IBM, Microsoft Research India and the Mozilla Foundation. He has been a Visiting Researcher at General Motors Research, Microsoft Research and most recently, at Google Brain. He is particularly excited about the prospect of developing machine learning techniques to automate software engineering, and designing trustworthy and deployable machine learning systems.