We are adding speakers and instructors daily to bring the best possible program of top data scientists and instructors.
We are adding speakers and instructors daily to bring the best possible program of top data scientists and instructors.
Toby Walsh is a leading researcher in Artificial Intelligence. He is a Laureate Fellow and Scientia Professor of Artificial Intelligence at UNSW and leads the Algorithmic Decision Theory group at Data61. He was named by the Australian newspaper as a “rock star” of Australia’s digital revolution. He has been elected a fellow of the Australian Academy of Science, a fellow of the Association for the Advancement of Artificial Intelligence, and of the European Association for Artificial Intelligence. He has won the prestigious Humboldt research award as well as the NSW Premier’s Prize for Excellence in Engineering and ICT, and the ACP Research Excellence award. He has previously held research positions in England, Scotland, France, Germany, Italy, Ireland, and Sweden. He has played a leading role at the UN and elsewhere on the campaign to ban lethal autonomous weapons (aka “killer robots”). Toby Walsh regularly appears in the media talking about the impact of AI and robotics on society. He is passionate that limits are placed on AI to ensure the public good such as with autonomous weapons.
AI and Ethics(Keynote)
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.
Applying AI to Real World Use Cases(Keynote)
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.
Dakshinamurthy V Kolluru is the Founder President & Chief Mentor of INSOFE (International School of Engineering), an organization that champions Education, Consulting, Research and Product Development in Data Science / Big Data Analytics.
His expertise lies in simplifying complex ideas and communicating them clearly and excitingly. He has worked extensively in Data Science with majority of his work pertaining to mathematical algorithms and pattern extraction. Currently, he set up “AI for Business” Lab at INSOFE whose vision is to help organizations adopt AI efficiently and systematically. He has helped set-up several Data Science COEs. Dakshinamurthy along with his highly skilled team steered INSOFE into being the globally acclaimed School of Applied Engineering it is today.
Dakshinamurthy has offered training and consulting services in US, UK, India & Middle East to fortune companies from Pharma, Insurance, retail, manufacturing and other sectors.
Before founding INSOFE, he worked with Defence Metallurgical Research Laboratories (DMRL) on some very prestigious projects, one of which was under the guidance of Dr. A P J Abdul Kalam which found much recognition and won him the Binani Gold Medal.
Adopting AI in Enterprises(Keynote)
Gunjan has been working in the industry for 3+ years and has a background in Mathematics. Currently, she is working with the Fraud Team in the Gopay (Gojek) Data Science team. She can talk about statistical models with you all day long and can’t help but notice patterns everywhere in her life. Along with her day job, she also mentors aspiring young data scientists. She currently a mentor at springboard.com for their course Data Science Career Track.
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.
Priyanshu Jain is a Data Scientist and a Machine Learning enthusiast with 6 years of experience. He graduated from IIT Delhi in 2014. He did B.Tech and M.Tech in Electrical engineering. He has worked with Barclays and Opera Solutions in the past. Currently, he is employed with Guavus Networks.
Kavita is an Analytics leader with 12 + years of core hands-on experience having an excellent track record on Presales, Partner Management, Analytics Delivery, and Team management across domains in World-Class Organizations. Currently, she is heading the Data Science function at Infinite Sum Modeling. She is a Chemical Engineer by education followed by a Masters (Eco) from IGIDR. She is a seasoned analytics professional with work experiences across companies like Fair Isaac, Experian, Accenture, Infosys, and Vodafone. Her vast experience in domains like Banking, Insurance, Telecom, Fraud, and Risk Management gives her the right kind of diversification. She has published papers in areas of Financial Econometrics and Social Media Analytics. She has been an esteemed speaker at various national seminars on Analytics. Her passion for Analytics and learning drives her to explore newer technologies and innovations in Analytics space. She is currently leading the capabilities of the firm in the areas of data science and analytics training as well as new business development in several areas that include data science, business analytics, Artificial Intelligence, Data Mining, Machine learning, blockchain, robotic process automation, econometric modeling, CGE modeling, policy/business strategy analysis, among other areas of interest to the company.
Soham Chakraborty is a Senior Data Scientist with a Statistical background. He works mostly in Manufacturing creating AI solutions using Machine Learning and Deep Learning techniques.
Hugo Bowne-Anderson is Head of Data Science Evangelism and VP of Marketing at Coiled, a company that makes it simple for organizations to scale their data science and machine learning in Python. He has extensive experience as a data scientist, educator, evangelist, content marketer, and a data strategy consultant at DataCamp, the online education platform for all things data. He also has experience teaching basic to advanced data science topics at institutions such as Yale University and Cold Spring Harbor Laboratory, conferences such as SciPy, PyCon, and ODSC and with organizations such as Data Carpentry. He has developed over 30 courses on the DataCamp platform, impacting over 500,000 learners worldwide through his own courses. He also created the weekly data industry podcast DataFramed, which he hosted and produced for 2 years. He is committed to spreading data skills, access to data science tooling, and open-source software, both for individuals and the enterprise.
Prof Carol Anne Hargreaves is a results-oriented Director of the Data Analytics Consulting Centre at the National University of Singapore (NUS) and holds a joint position as an associate professor in the Department of Statistics & Applied Probability and the Department of Mathematics. She is also the Co-Chair for the Data Science & Analytics Programme. Prof Carol has extensive experience in leading teams of analysts to solve multidisciplinary real-world data science problems. She developed and took charge of multiple innovative projects in the Pharmaceutical, Healthcare, Telecommunications, and Fast-Moving Consumer Goods (FMCG) Industry.
Her research area includes Artificial Intelligence & Machine Learning Applications in Healthcare and the Financial Industry. She is a Member of the Data Literacy Programme Committee at the National University of Singapore. Prof Carol Hargreaves is a Keynote Conference Speaker, Program Committee Member, and an Editorial Board Member for many international and local conferences.
Dr. Sri Vallabha Deevi is a Data Scientist at Tiger Analytics and lead teams in building analytics solutions – from simple statistical models to AI/Deep Learning models. His expertise is in scientific computing, machine learning & reduced-order modeling of physical systems. He is interested in teaching and talk on data science and machine learning regularly at various colleges & conferences. He finished B.Tech from IIT Madras and Ph.D. from IISc Bangalore.
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 recognized 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).
Soumya Jain is currently working as a data scientist II in MiQ. She has done her engineering in computer science from BIT Durg, and MTech from IIIT Bangalore in data Science specialization. She has been employed for the past 1.5 years. She has a keen interest in the field of data science and finding valuable information from a dataset and making great stories out of it is what drives me to learn more.
Amogh Kamat Tarcar is a Team Lead at Persistent Systems, exploring machine learning in CTO R&D team
Upasana Roy Chowdhury is a data science consultant with supply chain and manufacturing experience.
Piyush Arora is a Research Scientist with American Express AI Labs, Bangalore, India since September 2019. Before joining American Express, he was a Post-Doctoral researcher with the ADAPT Centre, Dublin, Ireland. He completed PhD in computer science in August 2018 from Dublin City University, Ireland.
His areas of interest are Information Extraction and Retrieval, Machine Learning, User Search Behavior, Natural Language Processing, Sentiment Analysis, and Deep Learning.
During his PhD, he worked in the area of Interactive Information Retrieval, towards developing novel solutions for improving the overall search experience and user learning. Mainly focused on Natural Language Processing and Machine Learning techniques and tools and their application for different tasks, domains, and languages.
He is interested in learning and exploring more on how to use technology to bring changes at the root level, especially focusing on education and human learning, how can we make better societies and ecosystem with the use of technology. He believes “Guided Technology” can play an important role in the path towards a global sustainable world.
Jianshu is Head of Federated Learning at AI Singapore where he leads the 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.
Pooja Balusani is a Data Scientist at Noodle.ai for 2 years. She has a Bachelor of Technology in Computer Science and Engineering with a Specialization in Data Science from PES University, Bangalore. She worked on Reusable Data Science Assets, Product Quality, and Asset Health AI Applications.
Isaac Reyes, Co-Founder at StoryIQ, is a TEDx speaker and international keynote presenter in data visualization and machine learning. He was the keynote speaker at the 2019 Open Data Science Conference in Brazil and over 2018-2019, his speaking tour visited 26 cities across 5 continents. His ultimate goal is to empower every organization to derive value from data.
The Four Keys to Data Storytelling(Tutorial)
Debanjana is a Data Scientist at Walmart Labs, Global Data Value Realization. At Walmart, she has been instrumental in building numerous high-functioning bots in the compliance space dealing heavily in Natural Language Processing, Optimization, Mixture Models and Rare Time Series. Currently, her focus is on extensive Shrink Research where along with her team members she is identifying potential areas of high impact for Retail Shrink. During her 3 years of experience, Debanjana has filed 5 US patents in the field of Clustering & Anomaly Detection, Imbalance Text Classification, Travel Optimization and Stochastic Processes. In addition, she has three published papers to her credit. She presented her paper REDCLAN (Relative Density Based Clustering and Anomaly Detection) in ADCOM’18, CRESST was included at ICMLA’19 and iCASSTLE (Imbalanced Classification Algorithm for Semi Supervised Text Learning) was presented at ICMLA’18 (Orlando, FL), which was later published by IEEE. Debanjana has a master’s degree in Statistics from Indian Institute of Technology (Kanpur).
Researcher, Data Scientist, Data Science Architect, Performance specialist, Entrepreneur. Currently working as a Data Science Researcher and Director in Thales (Guavus) handling various Data Science projects. Along with actively exploring new techniques of Machine Learning via various research projects. Thus ensuring that Data Science could be effectively applied to real world scenarios and able to solve important problems.
Noriko Arai is the program director of an AI challenge, Todai Robot Project, which asks the question: Can AI get into the University of Tokyo? The project aims to visualize both the possibilities and the limitation of current AI by setting a concrete goal: a software system that can pass university entrance exams. In 2016, Todai Robot achieved the top 20 percent in the exams and passed more than 70 percent of the universities in Japan. She is also the program director of Researchmap Project to build a platform for researchers to manage their research activities. The inventor of Reading Skill Test, in 2017 Arai conducted a large-scale survey on reading skills of high and junior high school students with Japan’s Ministry of Education. The results revealed that more than half of junior high school students fail to comprehend sentences sampled from their textbooks. Arai founded the Research Institute of Science for Education to elucidate why so many students fail to read and how she can support them.
Kuldeep Singh has 11 years of professional experience in the Technology domain with DevOps specialisation. Currently, he is working to explore Data Science world with BigData, Machine learning and AI.
Ashwathi Nambiar is an experienced Software Engineer. Her interests are AI/ML/DL. Currently, she is working towards efficient embedded deployment of neural networks.
Venkata Pingali is an academic-turned entrepreneur. He works at the intersection of data, ML algorithms, and systems. He builds data products to speed up the adoption of ML in the enterprise. Scribble Data, his firm, offers a platform and managed service to production feature engineering.
Piyush is a graduate from Georgia Institute of Technology and is currently working as an NLP Engineer at vahan.ai. After passing out from IITR with a Bachelors’s in ECE, he started out his career as a 4G protocol engineer but soon got attracted towards the fast-growing ML/AI domain. Over time he switched over to this domain and, after some exploration, found his interest in working with vernacular languages.
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.
Aravind Kondamudi is a Data Science enthusiast. He has completed Dual Degree masters in BITS Pilani and currently working in Aditya Birla Group as a Data Scientist. His love for Data science started while he was working in a Microfluidics lab, he worked on modeling the flows using data science aspects rather than traditional computational modeling. Then he worked to model the metallurgical properties in multiferroic materials. Being a Manufacturing Engineer, He got a chance to work in Aditya Birla Group, a manufacturing giant. He currently works on improving the manufacturing process through Machine Learning models.
Ujwala Musku works as a Data Scientist at MiQ Digital, and her work involves building revenue-based advanced analytics products within the digital advertising market. She has provided analytical and campaign management advice to top retail and travel clients at MiQ. She has experience in working in areas around retail analytics, supply chain optimization, and efficiency optimizations. Ujwala graduated with a B. Tech. in Chemical Engineering from IIT Guwahati, is a keen learner and inspired to build scalable ML solutions.
Anuj Gupta is a head the Machine Learning and Data Science teams at Vahan. Prior to this, he was heading ML efforts for Intuit, Huawei Technologies, Freshworks, Chennai, and Airwoot, Delhi. He did his masters in theoretical computer science from IIIT Hyderabad and he dropped out of his Ph.D. from IIT Delhi to work with startups.
He is a regular speaker at ML conferences like Pydata, Nvidia forums, Fifth Elephant, Anthill. He has also conducted a bunch of workshops attended by machine learning practitioners. He is also the co-organizer for one of the early Deep Learning meetups in Bangalore. He is also the Editor of “Anthill-2018” – deep learning-focused conference by HasGeek.
Angela is an AI Professional specialized 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) & the 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.
Ethan Tu is a pioneer in Taiwan’s AI industry and the founder of Taiwan’s largest and most popular online bulletin board system PTT. He worked as Microsoft’s Director of Research and Development for AI in the Asia-Pacific Region for 11 years, being one of the main figures in Microsoft’s Cortana development. In 2016, he founded the Taiwan AI Labs, which is a Taipei-based and privately-funded research organization specialized in AI solutions. Since its inception, the team has shown significant results in medical AI/imaging applications, drone applications, Smart City applications, speech recognition, and face recognition, while fostering and retaining local talents.
As a data and information ethicist, Theresa uses creative, compassionate, and contemplative practices to help communities build better digital and data futures. Building consensus through gaining and maintaining a community’s trust and implementing good practice to advance socially-just data policies is embedded in her work. Her award-winning work as an educator and researcher engages with the ever-evolving relationship between people and emerging technologies when working with data and making decisions. A social informaticist with a Ph.D. in Information Science, she served as inaugural Director of the Master of Data Science & Innovation program at UTS from 2014-2018, leading the development of a uniquely transdisciplinary and human-centered curriculum that continues to prepare graduates for the demands of the data science fields. Now working as a freelance consultant, Theresa contributes to government, industry, and NGO efforts advancing socially-just data policies, building processes for gaining and maintaining a community’s trust in data/AI use. She recently joined the Standards Australia Data Sharing Committee (IT-027-06 and JTC 1/SC 32/WG 6). Theresa also contributes to international initiatives related to data sharing via the International Science Council’s Committee on Data and as a Sydney Ambassador for Stanford’s Women in Data Science Network.
Dr. Shou-de Lin is Appier’s Chief Machine Learning (ML) Scientist. He joined Appier from National Taiwan University (NTU), where he served as a full-time professor in the Department of Computer Science and Information Engineering. Prior to joining NTU, Dr. Lin was a postdoctoral research fellow at the Los Alamos National Lab. Dr. Lin specializes in areas including artificial intelligence, knowledge discovery, and natural language processing. He is an expert in solving practical challenges in machine learning applications. Dr. Lin joined Appier in February 2020 and leads the AI, research team. His focus is on the development and application of advanced machine learning technology to help customers smoothly implement AI solutions and optimize performance. Dr. Lin has collaborated with more than 50 companies and has won several awards in recognition of his work, including the 2007 Google Research Awards; the Microsoft Research Awards (which Dr. Lin won three times); and the IBM Research Awards.
During his time at NTU, Dr. Lin established the Machine Discovery and Social Network Mining Lab. He is the all-time winner of the ACM KDD Cup, for which he either led or co-led the NTU team to win 6 championships. He also led a team to win the WSDM Cup in 2016. Dr. Lin is passionate about developing young AI talent in Taiwan and has supervised more than 100 graduate students, and several of which have gone on to become university professors, founders of start-up companies, or key people at software and hardware companies.
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.
Pia Andrews is an open government and data ninja who has been driving digital, data, policy, and legislation transformation in the public sector for a decade. Pia has been in the tech sector and community for another 10 years before that and has been evangelizing “gov as a platform” right throughout. She works within the (public sector) machine to enable greater transparency, democratic engagement, citizen-centric design, and real, pragmatic actual innovation in the public sector and beyond.
Pia believes that tech culture particularly open source has a huge role to play in achieving better policy planning, outcomes, public engagement, and better public service all round. She is also trying to do her part in establishing greater public benefit from publicly funded data, software, and research. Pia was recognized in 2018 as one of the global top 20 Most Influential in Digital Government and was awarded as one of the Top 100 Most Influential Women in Australia for 2014.
Alisher Abdulkhaev is a Machine Learning Engineer working for Browzzin — AI-powered Social Fashion App. Alisher is the co-director and board member at Machine Learning Tokyo—an award-winning non-profit organization dedicated to democratizing machine learning.
Rethinking Object Detection(Tutorial)
Dat is the Head of AI at Axel Springer Ideas Engineering (https://axelspringerideas.de/), the innovation unit of Axel Springer SE which is the largest digital publishing house in Europe. He establishes and leads Axel Springer AI (https://ai.axelspringer.com/) where his goal is to make AI more accessible within Axel Springer and hence drive innovations within the group. His ultimate plan is to turn Axel Springer into an AI-first company. Dat’s interests are diverse from traditional machine learning, deep learning, AI in general to computer vision. Previously, he co-headed the data team at idealo.de where he built up the machine learning team from scratch. His team mainly focused on computer vision problems from teaching a computer to understand aesthetics to upscaling low-resolution images. He is a regular speaker and has presented at several renowned conferences. He also blogs about his work on Medium. His background is in Operations Research and Econometrics. Dat received his MSc in Economics from the Humboldt University of Berlin.
Saptarishi is Sr. Analytics Consultant, India, supporting the SAS Platform product lines. In his current role, Saptarishi works with customers to collaborate with multiple stakeholders to ideate and build product prototypes for various business demands which can become a revenue potential. He has worked with customers in Financial Services, Insurance, and Manufacturing.
Saptarishi is passionate about discussion and designing solutions in the area of Machine Learning, Deep Learning, and Data warehousing.
Akshay Bahadur’s interest in computer science sparked when he was working on a women’s safety application aimed towards the women’s welfare in India and since then he has been incessantly tackling social issues in India through technology. He is currently working alongside Google to make an Indian sign language recognition system (ISLAR) specifically aimed at running on low resource environments for developing countries. His ambition is to make valuable contributions towards the ML community and leave a message of perseverance and tenacity.
He’s one out of 8 Google Developers Expert (Machine Learning) from India along with being one of 150 members worldwide for the Intel Software Innovator program.
Rajesh Shreedhar Bhat is working as a Data Scientist at Walmart Labs, Bangalore. His work is primarily focused on building reusable machine/deep learning solutions that can be used across various business domains at Walmart. He completed his Bachelor’s degree from PESIT, Bangalore and currently pursuing his MS in CS with ML specialization from Arizona State University. He has a couple of research publications in the field of NLP and vision, which are published at top tier conferences such as CoNLL, ASONAM, etc.. and he has filed 6 US patents in Retail space leveraging AI & ML. He is a Kaggle Expert(World Rank 966/122431) with 3 silver and 2 bronze medals and has been a selected as a speaker in highly recognized conferences/meetups such as O’Reilly Strata Data & AI Conference, Spark AI Summit, California, Data Hack Summit, Kaggle days meet up – Senior Track, etc .. Apart from this, Rajesh is a mentor for Udacity Deep learning & Data Scientist Nanodegree programs for the past 3 years and has conducted ML & DL workshops in GE Healthcare, IIIT Kancheepuram and many other places.
Pranay Dugar is passionate about machine learning and deep learning. In specific, he has worked on object detection and has done projects such as text detection, facial recognition, DNA mutation detection. He is proficient in python and the tensor flow framework as well as Keras for creating and running my models. He has taken part in many hackathons, at both national and international levels, even going on to become the eventual winners in DreamWorks and Daimler. Our ‘Driver Distraction Detection’ based on Convolution neural network, was presented at the Mobile World Congress, Barcelona (2017) by Mercedes. He aims to create artificial intelligence that can observe and interact as well as any human.
Darshan C Ganji is an Artificial Intelligence Developer(DL Hardware and Acceleration) at SandLogic Technologies Pvt. Ltd. He works mainly on Optimizing, Deploying Deep Learning Models on low-cost Edge Devices, and Design of Hardware Accelerators and Compilers for Deep Neural Networks. He was previously working under Prof. L.M.Patnaik in the Dept of Electronics Systems Engineering, IISc. His Research work includes AI Hardware and High-Performance computing. His Passion lies in parallel computing, particularly in many-core computing and the use of accelerators in combination with multi-cores to optimize performance. And keen to explore the things on end-to-end system architecture definition, hardware-software co-design, and performance optimization for multiple generations of accelerator systems.
Deepesh Agrawal experienced Machine Learning Engineer with a demonstrated history of working in the information technology and services industry, before this I was a Solution Architect with Nvidia’s partner. I have completed projects based on ML & DL such as video classification, object detection, and text analysis. Skilled in Python (Programming Language), C++, Data Science, and Deep Learning.
Vinayaka Mayura has been working as a Quality Analyst for 8+ Years. Worked with companies like Thoughtworks, Rakuten, Flipkart. Has a specialization in testing unconventional software applications. Contributed a few bit to the community in open source projects and given talks at a few conferences.
Manjeet Dahiya is a Principal Data Scientist with Delhivery. He has earlier worked with Agilent Technologies and United Online (Juno Online). Manjeet obtained his Ph.D. in computer science from IIT Delhi and BTech in electrical engineering from IIT Kanpur.
Parthiban Srinivasan holds a dual Masters Degree- one in Science and the other in Engineering. Then, Ph.D. in Computational Chemistry from Indian Institute of Science, Bangalore. After his Ph.D., he continued research at NASA Ames Research Center (USA) and Weizmann Institute of Science (Israel). Then he worked at AstraZeneca in the area of Computer-Aided Drug Design for Tuberculosis. Later, he headed informatics business units in Jubilant Biosys and then in GvkBio before he floated the company, Parthys Reverse Informatics. Now his recent venture is VINGYANI, a data science company, with a focus on AI guided drug design and health.
Now, Parthi is also serving as Adjunct Faculty at the Indian Institute of Science Education and Research (IISER) Bhopal, teaching Artificial Intelligence.
Attended 5-day ODSC West, San Francisco, October 2019, and ODSC east, Boston, April 2020 (Virtual).
Sharmistha is currently working as a Senior Manager at Publicis Sapient where she is working on different AI, machine learning, and data governance problems. She holds a Master’s Degree in Computer Science and Engineering from Aalto University. Her Master’s thesis was done in collaboration with Nokia Research center under the supervision of Professor Joerg Ott (https://www.netlab.tkk.fi/~jo/), who is also the co-chair of SIP working group and other telecommunication research organizations and startups in Europe.
Sharmistha has in-depth expertise in productionizing and scaling AI solutions on AWS and Google Cloud. She is a certified Professional Google Cloud Architect. Prior to joining Publicis Sapient she has worked at a startup called Datami Mobile Solutions, sprung from Princeton University. Here she has filed 5 patents (https://patents.justia.com/inventor/sharmistha-chatterjee). Her work in SIP has been cited by Microsoft patent (https://patents.google.com/patent/US8682889B2/en).
She holds expertise in both research and productionizing scalable AI solutions, and skillset to bridge the gap between theory and practice. She has a proven track record of delivering complex innovative solutions to fortune 500 companies increasing revenue to $5M (in early-stage start-ups: Princeton University start-up, Ittiam Systems, SAP labs) to larger than $500M. She has worked with direct stakeholders, the world’s most renowned, award-winning research scientists in the field of telecom, media, advertising, and IOT domain. She is also a medium blogger.
Tanuj Jain is a Senior Machine Learning Engineer working at Axel Springer AI (located in Berlin) since December 2019. He was previously a part of Data Science team at idealo Internet GmbH. His current interests revolve around deep learning research for speech and image processing. He completed M.Sc. in Electrical Engineering from Paderborn University in 2015 and my B.Tech from GGSIP University, New Delhi in 2010. He is very interested in leveraging the power of machine learning to empower businesses and measure the impact thus created.
Akshay is Analytics Consultant, Education at SAS India. In his current role, Akshay works with various clients of SAS in the Asia Pacific region to develop workforce in effective use of the SAS products in the area of Analytics, data management and Business data visualization. He has worked with customers in Financial Services, Insurance, Manufacturing and Telecommunication.
Internalizing Machine Learning(Workshop)
Graham Williams is Chief Scientist with the Software Innovation Institute, Australian National University. Prior to joining the ANU, he was Director of Data Science, Cloud, and AI, with Microsoft. Graham has a Ph.D. in Machine Learning and is an AI developer, researcher, practitioner, and educator as well as an Open Source Software advocate, with over 30 years in the industry. He is the author of popular books and software, ‘Data Mining with Rattle and R’, and ‘The Essentials of Data Science’. His contributions to Data Science in the region, including building capability across organizations in the industry, government, and academia, were recently recognized by the Pacific Asia Conference on Knowledge Discovery and Data Mining through its Special Achievement Award for extraordinary and ongoing contributions in research and service to the field.
Ian is a data science and engineering guru with over 2 decades of industry experience. He has a strong background in legacy SAS and Apache Spark-based analytical solutions. He has a wealth of experience designing and developing data warehouses, BI reports, business process automation, simulation systems, machine learning models, and analytical applications. His broad skills have helped numerous clients around the world in the government, financial, insurance, health care, telecom, software, and retail sectors. In 2015, he founded WiseWithData, a firm specialized in Apache Spark-based advanced analytics and legacy migration solutions, with a global reach.
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.
Graduating with a degree in Information Technology my love of working with data landed me my first job. Spanning three continents, my projects saw me architect Data Warehouses and Data Analytics platforms across banking, retail industries and startups. Currently, I am building the data platform and strategy at a construction tech B2B company called Assignar. Data, being a relatively new field is still shackled by the archaic ways of the old technology days with women still being far and few. Being a woman in this emerging area brings with it a sense of pride, but also a sense of responsibility. Empowering women to challenge the status quo and consider a career in Data is also on my agenda. I also enjoy keeping myself involved in academia by teaching in the Master of Data Science and Innovation(MDSI) program as a lecturer for Data Science Practices where I get to teach and mentor budding Data enthusiasts. One of my areas of interest is deep learning (neural networks and AI). I am fascinated with the possibilities of its application across industries and am keen to realise its potential in mainstream businesses. Hence I further aim to continue my quest for knowledge and discovery with an Industry PhD in the field of Neural Networks and Project Management.
SQL for Data Science(Tutorial)
Prasanth Pulavarthi is Principal Program Manager for the AI Frameworks team at Microsoft. His team works on making ML practitioners and engineers more efficient through optimized libraries, tools, and communities. ONNX Runtime (https://onnxruntime.ai) is an open-source engine from his team that integrates with TensorFlow, PyTorch, and other frameworks to accelerate inferencing and training on a variety of cloud and edge hardware.
Prasanth is also the Co-Founder of ONNX (https://onnx.ai), the open standard for machine learning interoperability. ONNX is now a graduate projected in Linux Foundation Artificial Intelligence. He serves on the ONNX Steering Committee and is actively involved in the ONNX community.
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)
Mehrnoosh Sameki is a senior technical program manager at Microsoft, responsible for leading the product efforts on machine learning interpretability and fairness within the Azure Machine Learning platform. She earned her PhD degree in computer science at Boston University, where she currently serves as an adjunct assistant professor and lecturer, 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.
Responsible AI with Azure Machine Learning(Demo Talk)
Genevieve Buckley is a scientist and programmer based in Melbourne Australia. She builds software tools for scientific discovery. Her interests include deep learning, automated analysis, and contributing to open source projects. She has a wealth of professional experience with image processing and analysis, spanning x-ray imaging, fluorescence microscopy, and electron beam microscopy. She is a maintainer for the dask-image project.
Ethel Karskens is the founder and president of Civita, a not-for-profit that “releases the power of data to everyone”. She has worked in the corporate, the tech, and the not-for-profit worlds as a data analyst. Today, she helps restore better data sovereignty to Indigenous communities through her work with Blak Impact and she spreads data equity with Civita.
Ashish is a comprehensive, time-critical, result oriented, ‘all-hands’ expert with over 17+ years of global experience in driving sustainable, scalable business performance and revenue growth. He has played multiple key roles in Solution development & delivery, competency building, manage P&L and Business Development for current key pursuits for BFSI, Retail, Energy & Telecom sector. He has invested humongous time working on layers of Data Engineering, Data Science and Decision Science, where he managed several cutting-edge technologies on AI-IOT & Data Science, Analytical Solution building and data driven architecture for Visualization tools. He is a seasoned analytics professional with work experiences across companies like GE, Deloitte & Touche’ , Hewlett Packard, Adobe Systems, American Express, Mu-Sigma and currently working with NEC Corporation India as Head of Analytics & AI .
With his extensive international experience, wherein living and working in several parts of United States, Europe & APAC – able to quickly adapt to diverse business methodologies, easily work across multicultural boundaries and effectively manage teams of various culture, geography and time zones.
He holds Bachelor’s degree in Information Technology, Masters in Marketing and Finance, also is a Certified Scrum Master & Project Management Professional, an Org-wide mentor & train the trainer for Project Management Programs in his skill sets.
Simon Asplen-Taylor is a Chief Data Officer at Rank Group, Tesco, Cushman & Wakefield. He is a specialist in transforming business through the use of data, analytics and artificial intelligence. Data IQ list him as one of the 100 most influential people in data 2020. Simon is an Executive Speaker, Fellow of the Royal Statistical Society (FRSS), Fellow of the British Computer Society (FBCS).
How to Maximize Business Value from Data Science(Track Keynote)
Rachel House is a Senior Data Scientist on S&P Global’s Artificial Intelligence Engineering team. Prior to her tenure at S&P, Rachel served as a software developer in the ad tech industry and as a proposal writer in defense contracting. She has leveraged her dual background in technology and communication to build a portfolio of experience in the design and development of robust, elegant systems as well as the ability to pitch those creations to varied audiences.
Torgil Hellman is the Chief Architect at WhereScape and has a deep knowledge and solid experience of e-commerce solutions. He has a rare understanding of both the technology and the business processes involved which makes him excellent as interface between senior operatives and system developers. He has over 10 years experience of developing e-commerce solutions and content managing applications in international environment.
Dr. Ankur Narang has 26 years of experience in Senior Technology Leadership positions across MNCs including IBM Research India and Sun Research Labs (Oracle), CA, USA. He was one amongst Top-10 Data Scientists in India in 2017 (Analytics India Mag) in recognition of solid scientific and industry contributions to the field of Data Science and Artificial Intelligence.
Dr.Ankur Narang heads the AI division at Hike as Vice President – AI and Data Technologies, where he leads state-of-the-art research and development projects on NLP, Chatbots, Computer Vision, Speech Recognition and related AI/ML areas. He holds B.Tech. & Ph.D. from IIT Delhi in CS&E and has 45+ publications in top international Computer Science & Machine Learning conferences and journals, along with 15 granted US patents and 25 pending. He has held multiple Industrial Track and Workshop Chair positions, and has given invited talks in multiple international conferences. As Co-founder of Sigmoidstar, he drives various training initiatives and consulting projects in AI and latest technologies including Blockchain as applied to various domains such as Ecommerce, Healthcare, Advertising, Education and others.
Bryan is a Senior Solutions Architect at WhereScape. He has been building Data Warehouses since the 90’s. He has been an Oracle DBA for over 20 years. Bryan started his career at NASA maintaining launch trajectories programs and has worked at large Financial Services companies, government agencies through startups.