For 2022 we had the best and brightest minds speaking at ODSC APAC. Some Speaker profiles can be found below.
For 2022 we had the best and brightest minds speaking at ODSC APAC. Some Speaker profiles can be found below.
Professor Mary-Anne Williams is the Michael J Crouch Chair in Innovation at UNSW where she collaborates with business, government and societal organisations to grow entrepreneurship and accelerate innovation in Australia. Mary-Anne has a PhD in Computer Science (University of Sydney) and Master of Laws (University of Edinburgh). She is a Fellow at Stanford University, the Australian Academy of Technological Sciences and Engineering, the Australian Computer Society and the Association for the Advancement of Artificial Intelligence (AAAI). Mary-Anne is a leading authority on AI with transdisciplinary strengths in AI for Business, Disruptive Innovation, Entrepreneurship, AI Ethics and Law. She has received multiple awards including the 2019 Australasian Distinguished Artificial Intelligence Contribution Award from the Australian Computer Society; two Google Faculty Machine Learning Awards in 2019 and 2021; and an IBM Faculty Award in 2008. She is a member of the Editorial Boards for AAAI/MIT Press; the Information Systems Journal; and the International Journal of Social Robotics. She was Chair of the International Conference on Social Robotics in 2014; Review Editor for Artificial Intelligence Journal; and served on the ACM Eugene L. Lawler Award Committee for Humanitarian Contributions within Computer Science and Informatics. Mary-Anne was Conference Chair for the 2021 Australasian Joint Conference on Artificial Intelligence and invited speaker for the Australian government at World Expo in Dubai in 2022.
Responsible Business AI(Keynote)
Luis Vargas is a Partner Technical Advisor to the CTO of Microsoft. Responsible for Microsoft’s AI at Scale initiative coordinating efforts across infrastructure, systems software, models, and products. He bootstrapped the productization of Automated ML and Reinforcement Learning in the Azure AI Platform, worked on the launch of Azure Database Services, and lead the high-availability area for SQL Server. Luis has a PhD in Computer Science from Cambridge University.
The Big Wave of AI at Scale(Keynote)
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.
As the Head of Data Science at Scouts Consulting Group, Ken spends his workdays improving the performance of athletes and teams by analyzing the data collected on them. He also dabbles in entrepreneurship and content creation, best known for his YouTube channel where he helps over 80,000 people navigate the data science landscape. More recently, Ken is focused on project-based learning through Kaggle. He hopes to share the processes that data scientists take when approaching Kaggle competitions and new datasets. He started the #66DaysOfData challenge to help people create the habit of learning and working on projects every day.
Dr. Jim Webber is Neo4j’s Chief Scientist and Visiting Professor at Newcastle University. At Neo4j, Jim leads the Systems Research Group, working on a variety of database research topics with a focus on fault-tolerance. He also co-wrote Graph Databases (1st and 2nd editions, O’Reilly) and Graph Databases for Dummies (Wiley). Prior to Neo4j, Jim worked on fault-tolerant distributed systems. First at Newcastle University startup Arjuna and then for a variety of clients for global consulting firm ThoughtWorks. Along the way Jim co-authored the books REST in Practice (O’Reilly) and Developing Enterprise Web Services – An Architect’s Guide (Prentice Hall). Jim’s blog is located at https://jimwebber.org and he tweets sometimes at @jimwebber.
Akira is a renowned data scientist in Japan who led the growth of DataRobot Japan as CEO until June 2021. His background in entrepreneurship (Shiroyagi Corporation), strategy consulting (BCG), experimental particle physicist (LHC, CERN) gives him a unique edge to develop business potential of AI and data technologies. He has worked with over a hundred companies in deploying advanced analytics and digital transformation projects. His active podcast and blog can be found through the links.
MLOps for Musicians(Talk)
Bujuanes Livermore is the Head of Research and Design in Data, Intelligence, and Design in Commercial Software Engineering (CSE) at Microsoft and she leads the Worldwide Community for Design & Experience. CSE is a global engineering organization that works directly with the largest companies and not-for-profits in the world to tackle their most significant technical challenges. Bringing human-centered design to the forefront and creating a more harmonious balance between the technical and the human drives her work. She is keenly interested in the influences and effects of digital and augmented environments, the human experience of service and product design, and challenging traditional business models and service offerings.
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 recognized as one of the top 10 data scientists in India in 2015 by Analytics India Magazine. Dr. Kumar holds a Masters and Ph.D. in AI from UT-Austin and B.Tech. in Computer Science from IIT-Varanasi.
Maria Kieferova (Marika) is a Sydney Quantum Academy fellow, a Lecturer at the University of Technology Sydney (UTS) and a member of Google Quantum AI. She has over ten years of experience working on quantum algorithms, starting from her undergraduate studies at Comenius University in Slovakia. She obtained her PhD from The Institute for Quantum Computing, University of Waterloo, and Macquarie University. Her thesis was awarded the Person medal and IQC Achievement Award. Throughout her studies, she undertook internships at Microsoft Research and Zapata Computing. At UTS, Marika is exploring the boundary between quantum and classical algorithms for machine learning. She is also affiliated with the ARC Centre of Excellence for Quantum Computation and Communication Technology and serves on the editorial board of the IOP journal Quantum Science and Technology.
Chip Kent is the chief data scientist at Deephaven Data Labs. He holds a Ph.D. from CalTech, with decades of quantitative, mathematical, and computer science experience. Chip comes from a background in quantitative private investment, using data to make investments at Walleye Capital.
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.
Building Machine Learning Apps(Tutorial)
Dipanjan (DJ) Sarkar is a data science consultant and published author, and was recognized as a Google Developer Expert in Machine Learning by Google in 2019. He currently works as a lead data science consultant at Schaffhausen Institute of Technology Academy, 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. Dipanjan has also been recognized as one of the top ten Data Scientists in India in 2020, 40 under 40 Data Scientists, 2021 and Top 50 AI Thought Leaders by Global AI Hub, Switzerland. In his spare time he loves reading, gaming, watching interesting documentaries, football. He is also a strong supporter of open-source and publishes his code and analyses from his books, articles and experience on GitHub at https://github.com/dipanjanS and LinkedIn at https://www.linkedin.com/in/dipanzan
Dr Fatemeh Vafaee is the Deputy Director of the Data Science Centre at the University of New South Wales (UNSW Sydney) and leads the ‘Health Data Science’ priority area. She launched and leads Artificial Intelligence in Biomedicine Laboratory (VafaeeLab.com) at UNSW and is the founder of OmniOmics.ai proprietary limited company (OmniOmics.ai) with the mission to develop and deploy AI technologies to enhance disease diagnosis and accelerate drug development. Dr Vafaee received her PhD in Artificial Intelligence from the School of Computer Science at the University of Illinois at Chicago, USA (2011) followed by 2 multidisciplinary postdoctoral fellowships at the University of Toronto, Canada, and the University of Sydney, Australia (2012 – 2017) on computational biomedicine. Dr Vafaee has a strong track record of multidisciplinary research leadership and industrial engagement. Her research has attracted over $10.5M across >12 research and industry-based project grants and has been published in top-tier journals in the field.
Setu is a senior technical leader, innovator and specialist in machine learning and artificial intelligence. He has led and implements machine learning products at scale for various companies.
Microsoft’s Accelerator for MLOps(Workshop)
Dr. Huong Ha is currently a Lecturer at the Artificial Intelligence Discipline, School of Computing Technologies, RMIT University, Melbourne, Australia. Her research is in the areas of Artificial Intelligence and Software Engineering, particularly trustworthy machine learning, automated machine learning, and data-driven software engineering. She regularly publishes her works in the leading international research venues in these areas including NeurIPS, ICML, AAAI, AISTATS, ICSE, and ICSME. In addition to her current role in academia, Huong has previous working experience in the industry as a data scientist and a product development engineer.
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.
Juan Kanggrawan is the current Head of Data Analytics at Jakarta Smart City. His key role is to fully utilize data to formulate public policy and to improve the quality of public services. Juan is currently working on several city-scale strategic analytics initiatives. He is actively analyzing complex, diverse and exciting urban data on a daily basis: citizen complaint/aspiration, transportation/mobility, health (COVID-19), CCTV, Open Data, weather-flood-river bank, subsidy utilization, food commodities price elasticity, etc. He is also developing and aligning a strategic partnership framework between Jakarta Smart City with other government agencies, business enterprises, research agencies, and universities.
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.
Dr Lau is a lecturer in the School of Computing and Information Systems at the University of Melbourne. His research is in Natural Language Processing — a sub-field of Artificial Intelligence — where the goal is to develop computational models to understand human languages. A common theme of Dr Lau’s research is that it involves building computational models in an unsupervised or semi-supervised setting, i.e. a learning scenario where the supervision signal for model training is not available or scarce, and is characterised by a diverse flavour of applications, e.g. topic models, lexical semantics, text generation and misinformation detection. Some of his research in text generation and state-sponsored influence operations has been covered by popular science magazines (New Scientist) and mainstream news media (BBC and Guardian).
Thilaksha Silva has obtained a Doctor of Philosophy (PhD) in Statistics from Monash University, Australia. Thilaksha is skilled in data science for electricity distribution, statistics, time series forecasting, predictive modelling and big data analytics. She is adept at advanced data analytics with 10+ years of experience and has mastered in communicating the business value across the business and engaging audience with data science on a deeper level.
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.
Vincent has 30+ years as AI specialist with ILOG and IBM. He has mentored several Data Science teams. Vincent has designed/modeled several major AI projects for customers such as Samsung. Electronics, McDonald’s, Dassault Aviation, Carhartt, Toyota, TSMC, Disney, etc. He is skilled in Mathematical Modeling, Machine Learning, Time Series prediction. He has strong experience in Manufacturing, Retail & Logistics industries. His main objective is to “Help companies go beyond AI pilots and be successful in bringing AI to their end-users”. He received his Msc in Comp. Science & AI from Paris-Saclay University.
Ravi Ranjan is a full-stack Data Scientist working as Manager Data Science at Publicis Sapient. He holds a Bachelor’s degree in Computer Science & Engineering with a proficiency course in Reinforcement Learning from IISc Bangalore. He has professional experience of 8+ years in AI and ML at scale with expertise in building enterprise data solutions and ML Engineering. He is part of the Centre of Excellence and is responsible for building ML products from inception to production. He has worked on multiple engagements with clients mainly from the Automobile, Banking, Retail, and Insurance industries. He is a Google Certified Professional Cloud Architect, blogger, speaker, and mentor.
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.
Sudeep George is the Vice President of Engineering at iMerit, where he develops production-ready frameworks for a data-centric approach to machine learning. He has a strong background in imaging sensors, computer vision and has built and manufactured multi-sensor computational imaging platforms for several market verticals.
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.
Ray is a Customer Success Data Scientist at WhyLabs, the AI Observability company. He has a long held passion for machine learning and loves helping customers save time and money by monitoring their ML systems at scale. Ray was formerly a Senior Success Engineer at Datorama, a Salesforce Company, where he drove success for large enterprise customers with a focus on improving query performance across the company. With his spare time, Ray enjoys hiking, music, and more hiking.
Aditya Bhattacharya is an Explainable AI Researcher at KU Leuven with an overall experience of 7 years in Data Science, Machine Learning, IoT & Software Engineering. Prior to his current role, Aditya has worked in various roles in organizations like West Pharma, Microsoft & Intel to democratize AI adoption for industrial solutions. As the AI Lead at West Pharma, he had contributed to forming the AI Centre of Excellence, managing & leading a global team of 10+ members focused on building AI products. He also holds a Master’s degree from Georgia Tech in Computer Science with ML and a Bachelor’s degree from VIT University in ECE. Aditya is passionate about bringing AI closer to end- users through his various initiatives for the AI community. He has also authored a book “Applied Machine Learning Explainability Techniques”
Dr. G Shobha, Professor, Computer Science, and Engineering Department, R.V College of Engineering, Bengaluru, India has teaching experience of 28 years, her specialization includes Data mining, Machine Learning, and Image processing. She has published more than 150 papers in reputed journals/conferences. She has also executed sponsored projects worth INR 200 lakhs funded by various agencies nationally and internationally. She is a recipient of various awards such as the Career Award for young teachers 2007-08 constituted by All India Council of Technical Education, Best Researcher award from Cognizant 2017, GHC Faculty Scholar for Women in Computing in 2018, IBM Shared University Research Award in 2019, HPCC Systems community recognition award 2020.
Glen Ford is VP of Product at iMerit — a leading AI data solutions company — where he leads the product management and design teams. Glen holds more than two decades of product development experience across the technology sector. A Graduate of Texas A&M University—Commerce, Glen began his career as a consultant where he handled full-stack web programming and architecture for clients including Time Warner and AIM Funds. Over the years, he has held senior and director-level product management roles at several companies including Demand Media, WP Engine and Humanify. Most recently, Glen spent four years at Alegion — an ML-powered data annotation platform — where he helped the company grow from eight full-time employees to more than 100 in a challenging, emerging market.
Florian Jacta is a specialist of Taipy, a low-code open-source Python package enabling any Python developers to easily develop a production-ready AI application. Package pre-sales and after-sales functions. He is data Scientist for Groupe Les Mousquetaires (Intermarche) and ATOS. He developed several Predictive Models as part of strategic AI projects. Also, Florian got his master’s degree in Applied Mathematics from INSA, Major in Data Science and Mathematical Optimization.
Prof. Jyoti Shetty, Assistant Professor, Computer Science and Engineering Department, RV College of Engineering, Bengaluru, India has 16 years teaching and 2 year industry experience. Her specialization includes Data Mining, Machine Learning and Cloud Computing. She has published research papers in reputed journals and conferences. She has also executed sponsored projects funded from various agencies nationally and internationally. She was the recipient of awards such as SAP Award of excellence from IIT Bombay for demonstrating ICT in education in 2016 and HPCC Systems Mentor Badge Award in 2021 for providing guidance and direction towards the successful completion of intern open source projects.
Pete spent more than two decades on Wall Street, growing, and running automated trading groups. In 2005, he was the founding CEO of Walleye Capital, a multi-billion-dollar quant fund that derives value at the intersection of real-time data and automated applications. In 2017, Pete and some engineers spun a proprietary data engine out of Walleye, forming an independent company called Deephaven Data Labs. Deephaven is an open-first software shop, delivering a real-time query engine, APIs, UIs, and integrations to the community via open projects designed for diverse teams. Deephaven complements streaming technologies and makes dynamic data easy and accessible.
Sushant has a bachelor’s in Materials Engineering from the Indian Institute of Technology, Kharagpur. He has extensive work experience in Reinforcement Learning, Computer Vision with AR technologies and created end-to-end pipelines and data products from conceptualisation to deployment phase for various engagements. He is currently working as a Senior Data Scientist at Publicis Sapient.
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 7+ 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 Machine Learning, Deep Learning, Computer Vision, NLP, Generative Models and Augmented Reality.
Kanika is an Enterprise Pre-Sales expert who delivers high-energy keynote presentations and runs successful POCs on “SingleStore” and values dedication, service and excellence. She has experience working with some big enterprises in various domains including Banking,Oil and Gas, Networking. She earned her M.tech from BITS Pilani and is certified professional in the database world.
Jeet is an experienced Data Science professional carrying 7+years of applied Industrial experience in Machine Learning, Deep Learning, Computer Vision & Natural Language Processing across multiple domains. He is right now working as Manager – Data Science in Analytics & Innovation (Ai) team at United Airlines, one of the major American airlines to solve Aviation analytics problems. Within his ~4 years at United he has worked on designing and architecting Computer Vision & NLP powered capabilities to save thousands of repetitive man hours & Millions of dollars in savings. In past he has worked with Tata Consultancy Services in its Analytics and insights(A&I) unit to build analytics capabilities across multiple domains. He follows various MOOCs and research communities, and his curiosity keeps pushing him to learn and explore more. A firm believer in giving back to the community and gives webinars/career coaching and 1-1 mentorship sessions on his journey to data science, the latest trends in the industry, and general advice to beginners and aspirants to help propel their journey into data science.
Prerna leads Business Development for Data Science at HP India. Prior to joining HP, she worked in IT industry for almost 9 years and has multi-disciplinary experience cutting across business development and data science & analytics. She has an MBA from SPJIMR, Mumbai and BTech in Computer Science.
Urvesh, currently Head of Data Science at Portcast.io (real time predictive visibility and demand forecasting to optimize supply-chain), has more than 8 years of hands-on and 4 years of leadership experience overall across Machine Learning, Software product development, management, and cross-functional collaboration. Urvesh started his career as a software engineer at Cisco, writing and fixing protocols for firewalls and exploring use of machine learning in malware classification. He later joined noodle.ai as a Data Scientist and worked on numerous ML projects involving government, manufacturing industry, and airlines. He has spent some time mentoring Data Science Students at SpringBoard and is currently a fellow at On Deck Data Science (ODDS).
Ghassen, currently data scientist at Portcast.io (real time predictive visibility and demand forecasting to optimize supply-chain), has close to four years of experience and extensive expertise in leading full-spectrum descriptive and predictive analyses towards supporting high-level decision-making.
Rohan Maheshwari is a student at RV College of Engineering in Bengaluru, India with a keen interest in Deep Learning, Natural Language Processing, Graph modelling and Machine Learning as well as their applications in finance and sentiment analysis. He has worked under the Samsung PRISM program to create a code-mixed multi-intent classification system. He has also worked with SCII to create an invoice extraction system. He is actively working with the LexisNexis® Risk Solutions HPCC Systems® team and the RV College of Engineering Centre of Excellence on Cognitive Intelligent Systems for Sustainable Solutions to investigate block data stored on the blockchain to gain insight and build relationships between transactions that can shed light on potential criminal transactions . Rohan is pursuing a Bachelor of Computer Science and Engineering at RV College of Engineering.
Passionate about solving human problems, Chanran’s main interests are computer vision and natural language processing while using machine learning and deep learning. He’s written a book on transfer learning and he often gives lectures on it. Today, Chanran is running Pseudo Labs, a machine learning community he founded in 2020. Pseudo Labs is all about sharing knowledge on machine learning and deep learning studies for free, offering Kaggle meetups, code sharing and other events in the Republic of Korea.
When Chanran isn’t running hackathons for Pseudo Labs, you’ll find him watching Premier League soccer matches or honing his food photography (pop over to his Instagram to see some mouth-watering shots).
Zaccheus has strong experience in development of time series machine learning models which power workforce scheduling systems. He is skilled in data science workflow and solution delivery by developing end-user applications. Zaccheus has designed/modeled AI projects and has big interest in Python’s ubiquity in diverse settings to explore fields like computer vision, NLP and bioinformatics. His main objective is discovering untapped potential across wide disciplines as big data becomes increasingly appreciated and available. He received his BSc. (Hons) in Computer Science from Sunway University. His Bachelor Thesis was on “Application of Blockchain to Trust Models for Secure Cognitive Radio Networks”.
Ruchi Bhatia is a Computer Engineering graduate from India and is currently pursuing her Master’s degree at Carnegie Mellon University. She is the youngest 3x Kaggle Grandmaster in the Notebooks, Datasets, and Discussion category, the Leader of Data Science at OpenMined, and one of the 21 Data Science Global Ambassadors at Z by HP. Her passion lies in utilizing data-driven techniques in conjunction with a sound knowledge of business processes to drive meaningful insights and impact.
Paras Varshney is a Data Scientist at LogicAI and an Ex-Data Scientist from IISc. Bangalore. He has been working on building competitive machine learning pipelines and automating the competitive ecosystem for the “Kaggle Days x Z by HP Global Data Science Championship”. He also developed the systems to manage the high throughput data ingestion pipelines for smart cities’ big data. Recognized within the top 1% of Kaggle worldwide, Paras likes to share his passion for data science by helping junior coders develop programming skills through an online classroom. He also loves writing, and his works can be found in top digital publications such as Towards Data Science.
Parinita Rahi is a Principal PM lead in Azure AI Platform organization at Microsoft. She works on various AI frameworks (PyTorch, ORT Training and ONNX Converters), in addition to driving GitHub CoPilot quality initiatives. She has 10+ years of Product Management experience, previously in the Online Advertising domain. She has driven various ML based solutions and products with a strong focus on solving customer problems.
Jambay Kinley is a Software Engineer in Azure AI Platform organization at Microsoft. He is a member of a team that works on various Pytorch related initiatives for the AI Frameworks team. Prior to joining Microsoft, he was involved in Machine Learning research in a Natural Language Processing lab at Cornell Tech.
Angelica Lo Duca is a researcher at the Institute of Informatics and Telematics of the National Research Council, Italy. She is also an external professor of Data Journalism at the University of Pisa. Her research interests include Data Science, Data Journalism, and Web Applications. She used to work on Network Security, Semantic Web, Linked Data, and Blockchain. She has published more than 40 scientific papers at national and international conferences and journals. She has participated in different national and international projects, and events. She has been a member of the Program Committee at different conferences. She is also the author of the book Comet for Data Science, published by Packt Ltd.
Astha Mehta is a Machine Learning Engineer at Condé Nast, where she works on building large-scale audience segmentation, recommendation, and personalization platforms. She currently leads the effort to redesign a content recommendation framework for newsletter personalization. Astha comes with vast experience in data science with over 4 years spent on research and development of media measurement assets. She is enthusiastic about designing simple, scalable systems that enable the company to grow its machine learning capabilities.
Hariprasath Thiagarajan leads the ML Product development and MLOps for various business verticals such as recommendations and subscriptions within Condé Nast across the global market, catering to different business use cases. Hariprasath has experience building software products for over 10+ years on different domains using Java, Scala, and Python. His involvement with Condé Nast allowed him to build most of the products from the ground up. Hari, and his team, specialize in scaling the process and architecture of these products so that the time-to-market for new brands is relatively lesser.
Jesús is Senior Director of Sales Engineering EMEA at neo4j. He holds a Ph.D. in Computer Science ( AI / Knowledge Representation ) from the Technical University of Madrid. His academic and profesional career has been permanently connected to Graphs. He did his Ph.D. research on relational-to-graph schema mappings with the Ontology Engineering Group between 2001 and 2007. After that, he moved to London to join Ontology.com and lead the design and construction of graph-based solutions for Tier 1 telcos around the world using the RDF stack. For the last 4 years he’s moved to the LPG camp, leading Neo4j’s efforts in the Telco and Media industry. Given his expertise on both sides of the graph spectrum (RDF and LPG), Jesús has been publicly speaking/blogging/coding about how the two approaches can coexist and complement each other.
Knowledge Graph Demo (Demo Talk)
Emil Pastor is a Solution Architect at Neo4j based in Sydney. He has been a data and AI professional enabling organisations in various industries through strategy, architecture, use case delivery, and capability building to support stakeholders and client data professionals in leveraging their data assets. Prior to working at Neo4j, he worked as an Architect and Consultant for organisations like Microsoft, McKinsey & Company (QuantumBlack), EY and Teradata.
Chase is a solutions architect at Arrikto with a passion for connecting people to technical solutions that can prevent them from wasting precious time and mental energy- solving the same problems over and over. Chase is a certified Kubernetes Administrator, Developer, and Security Specialist who works to help clients reduce MLOps friction and toil while ensuring the “non-negotiables” are enforced to provide the best return on their production models.
Souheil is the Head of Field Data Science at Arrikto where he helps build machine learning solutions for clients. Previously, Souheil worked at Freddie Mac and Capital One where he built models and machine learning platforms. Prior to becoming a data scientist, he spent 15 years in academia working on MRI and Brain Imaging. Souheil holds a BS and PhD in Physics from Yale and MIT respectively.