ODSC EAST 2023 CONFERENCE & EXPO
AI INNOVATION
SHOWCASE
Boston Hynes Convention Center | May 11, 2023
SHOWCASE YOUR STARTUP AT THE LEADING DATA SCIENCE AND AI CONFERENCE
No industry is immune from disruption and AI has become a core strategic advantage for many businesses. As part of our efforts to grow the data science community, we are offering our support to startups in these fields to help them spread the word to VCs, conference audience and data science community.
Speak and Connect
ODSC offers a unique opportunity to pitch to investors. Selected startups get a chance to speak to ODSC West audience and pitch to some of the top companies investing in data science and AI.
WHO SHOULD JOIN ODSC AI STARTUP SHOWCASE?
ODSC offers various opportunities to showcase at our conferences depending on your startup size and funding. We provide a limited number of spaces at each event and they are generally allocated on a first-come basis to qualified startups. Join ODSC AI Startup Showcase if:
- Your startup is B2B, B2C, or any combination.
- You have a demonstrable product or service you want yo exhibit
- The core startup technology is data science or AI
- Your startup funding stage is range from pre-funding/seed to Series A
- Your startup is a legal registered entity
- You would like to connect with our community, data scientists, attending companies and investors
PAST SPEAKERS AND FOUNDERS FROM TOP AI STARTUPS
Matt Harrison
Matt Harrison has been using Python since 2000. He runs MetaSnake, a Python and Data Science consultancy and corporate training shop. In the past, he has worked across the domains of search, build management and testing, business intelligence, and storage.
He has presented and taught tutorials at conferences such as Strata, SciPy, SCALE, PyCON, and OSCON as well as local user conferences.
Danny Chiao
Danny Chiao is an engineering lead at Tecton/Feast Inc working on building a next-generation feature store. Previously, Danny was a technical lead at Google working on end to end machine learning problems within Google Workspace, helping build privacy-aware ML platforms / data pipelines and working with research and product teams to deliver large-scale ML powered enterprise functionality. Danny holds a Bachelor’s degree in Computer Science from MIT.
Building Production-Ready Recommender Systems with Feast(Talk)
Dr. Jon Krohn
Jon Krohn is Co-Founder and Chief Data Scientist at the machine learning company Nebula. He authored the book Deep Learning Illustrated, an instant #1 bestseller that was translated into seven languages. He is also the host of SuperDataScience, the data science industry’s most listened-to podcast. Jon is renowned for his compelling lectures, which he offers at leading universities and conferences, as well as via his award-winning YouTube channel. He holds a PhD from Oxford and has been publishing on machine learning in prominent academic journals since 2010.
Cal Al-Dhubaib
Cal Al-Dhubaib is a data scientist, entrepreneur, and innovator in responsible artificial intelligence, specializing in high-risk sectors such as healthcare, energy, and defense. He is the founder and CEO of Pandata, a consulting company that helps organizations to design and develop AI-driven solutions for complex business challenges. Their clients include globally recognized organizations like the Cleveland Clinic, Progressive Insurance, University Hospitals, and Parker Hannifin.
Cal frequently speaks on topics including AI ethics, change management, data literacy, and the unique challenges of implementing AI solutions in high-risk industries. His insights have been featured in numerous publications such as Forbes, Ohiox, the Marketing AI Institute, Open Data Science, and AI Business News. Cal has also received recognition among Crain’s Cleveland Notable Immigrant Leaders, Notable Entrepreneurs, and most recently, Notable Technology Executives.
AI Design in High-Risk Settings: Aligning business impact, risks, and innovation:(AI X Talk)
Dr. Jennifer Prendki
Dr. Jennifer Prendki is the founder and CEO of Alectio, the first startup focused on DataPrepOps, a portmanteau term that she coined to refer to the nascent field focused on automating the optimization of a training dataset. She and her team are on a fundamental mission to help ML teams build models with less data (leading to both the reduction of ML operations costs and CO2 emissions) and have developed technology that dynamically selects and tunes a dataset that facilitates the training process of a specific ML model.
Prior to Alectio, Jennifer was the VP of Machine Learning at Figure Eight; she also built an entire ML function from scratch at Atlassian, and led multiple Data Science projects on the Search team at Walmart Labs. She is recognized as one of the top industry experts on Data Preparation, Active Learning and ML lifecycle management, and is an accomplished speaker who enjoys addressing both technical and non-technical audiences.
Josh Tobin, PhD
Josh Tobin is the founder and CEO of Gantry. Previously, Josh worked as a deep learning & robotics researcher at OpenAI and as a management consultant at McKinsey. He is also the creator of Full Stack Deep Learning (fullstackdeeplearning.com), the first course focused on the emerging engineering discipline of production machine learning. Josh did his PhD in Computer Science at UC Berkeley advised by Pieter Abbeel.
Jennifer Dawn Davis, PhD
Jennifer Davis, Ph.D. is a Staff Field Data Scientist at Domino Data Labs, where she empowers clients on complex data science projects. She has completed two postdocs in computational and systems biology, trained at a supercomputing center at the University of Texas, Austin, and worked on hundreds of consulting projects with companies ranging from start-ups to the Fortune 100. Jennifer has previously presented topics at conferences for Association for Computing Machinery on LSTMs and Natural Language Generation and at conferences across the US and in Italy. Jennifer was part of a panel discussion for an IEEE conference on artificial intelligence in biology and medicine. She has practical experience teaching both corporate classes and at the college level. Jennifer enjoys working with clients and helping them achieve their goals.
Large Scale Deep Learning using the High-Performance Computing Library OpenMPI and DeepSpeed(Workshop)
Alexander Ratner, PhD
Alex Ratner is the co-founder and CEO at Snorkel AI, and an Affiliate Assistant Professor of Computer Science at the University of Washington. Prior to Snorkel AI and UW, he completed his Ph.D. in CS advised by Christopher Ré at Stanford, where he started and led the Snorkel open source project, and where his research focused on applying data management and statistical learning techniques to emerging machine learning workflows such as creating and managing training data and applying this to real-world problems in medicine, knowledge base construction, and more. Previously, he earned his A.B. in Physics from Harvard University.
Solving the Last Mile Problem of Foundation Models with Data-Centric AI (AI X Talk)
Carl Gold, PhD
Carl Gold is currently the Data Science Director at OfferFit.ai, an AI-as-a-Service reinforcement learning engine that maximizes customer upsell and retention. Before coming to OfferFit, Carl was Chief Data Scientist of Zuora, the Subscription Economy leading billing platform. Based on his experiences fighting churn for SaaS companies during his time at Zuora, Carl wrote the first book dedicated to customer churn analytics and data science: “Fighting Churn With Data”. Carl has a PhD from the California Institute of Technology and first author publications in leading Machine Learning and Neuroscience journals.
Fighting Churn With Data(Workshop)
Daniel Lenton, PhD
Daniel Lenton is the creator of Ivy, which is an open-source framework with an ambitious mission to unify all other ML frameworks. Prior to starting Ivy, Daniel was a PhD student at Imperial College London, where he published research in the areas of machine learning, robotics and computer vision.
Unifying ML With One Line of Code(Tutorial)
Julien Simon
Julien is currently Chief Evangelist at Hugging Face. He’s recently spent 6 years at Amazon Web Services where he was the Global Technical Evangelist for AI & Machine Learning. Prior to joining AWS, Julien served for 10 years as CTO/VP Engineering in large-scale startups.
Leonardo De Marchi
Leonardo De Marchi holds a Master in Artificial intelligence and has worked as a Data Scientist in the sports world, with clients such as the New York Knicks. He now works in Thomson Reuters as VP of Labs, and also provides consultancy and training for small and large companies. His previous experience includes being Head of Data Science and Analytics in Bumble, the largest dating site with over 500 million users, heading the team through acquisition and an IPO.
Generative AI(Training)
Abubakar Abid, PhD
Abubakar Abid completed his PhD at Stanford in applied machine learning. During his PhD, he founded Gradio (www.gradio.dev), an open-source Python library that has been used to build over 500,000 machine learning demos. Gradio was acquired by Hugging Face, which is where Abubakar now serves as a machine learning team lead.
A Practical Tutorial on Building Machine Learning Demos with Gradio(Workshop)
Hagay Lupesko
Hagay Lupesko is the VP of Engineering at MosaicML, where he focuses on making generative AI training and inference efficient, fast, and accessible. Prior to MosaicML, Hagay held AI engineering leadership roles at Meta, AWS, and GE Healthcare. He shipped products across various domains: from 3D medical imaging, through global-scale web systems, and up to deep learning systems that power apps and services used by billions of people worldwide.
Unlocking the Power of Large Language Models: Why Owning Your Own Model is Critical—and Within Reach(Keynote)
Laura Ham
Laura is a ML Product Researcher at SeMI Technologies, the company behind the open-source vector search engine Weaviate. She researches new machine learning features for Weaviate and works on everything UX/DX related to Weaviate. For example, she is responsible for the GraphQL API design. She is in close contact with our open source community. Additionally, she likes to solve custom use cases with Weaviate, and introduces Weaviate to other people by means of Meetups, talks and presentations.
Malte Pietsch
Malte Pietsch is CTO & Co-Founder at deepset. His current focus is on building deepset Cloud – a SaaS platform for developers to build, deploy and operate modern NLP pipelines. He holds a M.Sc. with honors from TU Munich and conducted research at Carnegie Mellon University. Before founding deepset he worked as a data scientist for multiple startups. He is an active open-source contributor and author of the NLP framework Haystack.
Building Modern Search Pipelines with Haystack, Large Language Models and Hybrid Retrieval(Talk)
Dr. Jacqueline Nolis
Dr. Jacqueline Nolis is a data science leader with 15 years of experience in running data science teams and projects at companies ranging from Airbnb to Boeing. She is the Chief Product Officer at Saturn Cloud where she helps design products for data scientists. Jacqueline has a PhD in Industrial Engineering and her academic research focused on optimization under uncertainty. Data science is also her hobby—like making an R package that mails physical postcards of your plots.
Make Your Data Science Environment Just Right With Saturn Cloud(Demo Talk)
Jimmy Whitaker
Jimmy Whitaker is HPE’s Chief Scientist of AI & Strategy, specializing in the application of machine learning to diverse industries. With a strong background in Natural Language Processing (NLP) and Speech Recognition, Jimmy focuses on innovative solutions to enhance data-driven decision making and the application of AI at scale. He received his Masters in Computer Science at the University of Oxford, co-authored the textbook Deep Learning for NLP and Speech Recognition (Springer), and was previously Chief Scientist at Pachyderm (acquired by HPE), where he focused on applying data versioning and data-driven pipeline capabilities to ML problems.
Session Outline:
Data-Centric AI: Moving Beyond Model-Centric Approaches with Pachyderm
Abstract:
This technical talk delves into the paradigm shift from model-centric to data-centric AI, emphasizing the importance of data quality in improving machine learning outcomes. We will explore the current AI landscape and discuss the reasons behind this shift. Focusing on the Pachyderm platform for data-driven processing and versioning, attendees will learn practical steps and principles to streamline their data-centric AI efforts. This talk aims to equip practitioners with the knowledge and tools necessary to harness AI’s full potential by embracing a data-driven approach and leveraging Pachyderm’s innovative platform.
John Wasserman
John is a Data Architect at Airbyte where he enjoys helping companies move data from where it’s created to where they want it to live. Before AIrbyte he worked as a Global Solutions Architect at LiveRamp where he helped companies activate data to transform customer experiences. Besides being in the weeds about data, John is an avid bike rider and golfer.
Open Source Powers the Modern Data Stack (Demo Talk)
Shayan Mohanty
Shayan Mohanty is the CEO and Co-Founder of Watchful, a company that largely automates the process of creating labeled training data. He’s spent over a decade of leading data engineering teams at various companies including Facebook, where he served as lead for the stream processing team responsible for processing 100% of the ads metrics data for all FB products. He is also a Guest Scientist at Los Alamos National Laboratory and has given talks on topics ranging from Automata Theory to Machine Teaching.
Bias is Good: Arguments for Programmatic Labeling(Demo Talk)
Yaron Haviv
Yaron Haviv is a serial entrepreneur who has been applying his deep technological experience in AI, cloud, data and networking to leading startups and enterprises since the late 1990s. As the Co-Founder and CTO of Iguazio, Yaron drives the strategy for the company’s MLOps platform and led the shift towards the production-first approach to data science and catering to real-time AI use cases. He also initiated and built Nuclio, a leading open source serverless framework with over 4,000 Github stars and MLRun, a cutting-edge open source MLOps orchestration framework.
Prior to co-founding Iguazio in 2014, Yaron was the Vice President of Datacenter Solutions at Mellanox (now NVIDIA – NASDAQ: NVDA), where he led technology innovation, software development and solution integrations. He also served as the CTO and Vice President of R&D at Voltaire, a high-performance computing, IO and networking company which floated on the NYSE in 2007 and was later acquired by Mellanox (NASDAQ:MLNX).
Yaron is an active contributor to the CNCF Working Group and was one of the foundation’s first members. He sits on the Data Science Committee of the AI Infrastructure Alliance (AIIA), of which Iguazio is a founding member. He is co-authoring a book on Implementing MLOps in the Enterprise for O’Reilly. Yaron presents at major industry events worldwide and writes tech content for leading publications including TheNewStack, Hackernoon, DZone,Towards Data Science and more.
Implementing Gen AI in Practice(Track Keynote)
David Alsabery
David has over 20 years of experience in the fields of data, AI and enterprise cloud. He has led teams for EMC Dell, Hitachi and Cisco, working with some of the most innovative companies in the world in both classified and commercial environments. Today, David acts as the Western Regional Director at Iguazio, working with Enterprise customers to help them bring their data science initiatives to life. David is passionate about applying MLOps principles to real-world AI projects, on-premise, in multi-cloud environments, on a SCIF or all of the above. When he’s not working with customers on AI projects, he volunteers at the Salvation Army and Rotary International. He and his wife have twins – a boy and a girl, as well as a 94lb/43kg Labrador that eats everything.
Nick Schenone
Nick is a passionate machine learning, data science, and MLOps enthusiast with experience across multiple domains including fraud detection, natural language processing, computer vision, and data mining. Nick holds a BSc. in Cognitive Science with a specialization in ML and Neural Computation from University of California, San Diego. He is an AWS Certified Solutions Architect, and has earned certifications in Python, Pytorch, Apache Airflow, PySpark and other frameworks. Currently, Nick acts as pre-sales MLOps Engineer at Iguazio, where he specializes in helping enterprises create real-world impact with their data science initiatives, with expertise in deployments on AWS, GCP, and Azure as well as on-premise Kubernetes architecture. Nick speaks at global industry events and blogs about MLOps, data science and ML Engineering.
Demo Talk: Building and Deploying a Gen AI App in 20 Minutes
Abstract:
Generative AI has captured the imagination of many, but building your own Gen AI application is no easy feat. In this session, we’ll demonstrate how you can fine-tune a Gen AI model, build a Gen AI application, and deploy it in 20 minutes. For this exercise, we will use the following open source tools:
a. MLRun – MLOps orchestration framework
b. Langchain – used for building LLM applications
c. Milvus – open-source vector store for indexing documents
We’ll touch upon issues like accelerating the integration of AI/ML applications into existing business workflows, leveraging simple Python SDKs that transform code into a production-quality application, abstracting the many layers involved in the MLOps pipeline, building, testing, and tuning your work anywhere while integrating with other components of their business workflow.
Chase Christensen
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.
How Far Left Can You Shift? The Tension Between Data Science and ML Engineering(Talk)
Personal to Product to Platform: Reporting Your Results with Kubeflow(Demo Talk)
Souheil Inati, PhD
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.
How Far Left Can You Shift? The Tension Between Data Science and ML Engineering(Talk)
Personal to Product to Platform: Reporting Your Results with Kubeflow(Demo Talk)
Chip Kent
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.
Pete Goddard
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.
Real-time Analytics, AI&Apps with Deephaven Data Labs(Demo Talk)
Florian Jacta
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.
How to Build Stunning Data Science Web applications in Python – Taipy Tutorial(Workshop)
Bringing AI to Retail and Fast Food with Taipy’s Applications(Track Keynote)
Demo Session Title: Turning your Data/AI algorithms into full web apps in no time with Taipy
Abstract:
In the Python open-source ecosystem, many packages are available that cater to:
– the building of great algorithms
– the visualization of data
Despite this, over 85% of Data Science Pilots remain pilots and do not make it to the production
stage.
With Taipy, a new open-source Python framework, Data Scientists/Python Developers are able to
build great pilots as well as stunning production-ready applications for end-users.
Taipy provides two independent modules: Taipy GUI and Taipy Core.
In this talk, we will demonstrate how:
1. Taipy-GUI goes way beyond the capabilities of the standard graphical stack: Gradio,
Streamlit, Dash, etc.
2. Taipy Core fills a void in the standard Python back-end stack.
Martin Shell
Martin has over 30 years of experience in Data Science, AI, Decision Optimization. He worked as Consulting Project Manager, Technical Sales, Data Scientist with organizations including ILOG, IBM, Manhattan Associates, Emptoris. He has strong modeling skills in constraint programming, mathematical programming, machine learning. He is skilled in C++, Java, Python. Martin’s main objective is to help organizations identify and deploy analytics that maximize ROI. He was selected as INFORMS Franz Edelman Award finalist. He has studied M.S. in Operations Research from Massachusetts Institute of Technology.
Turning your Data/AI algorithms into full web apps in no time with Taipy (Demo Talk)
How to Build Stunning Data Science Web applications in Python – Taipy Tutorial(Workshop)
Kaushik Bokka
Kaushik Bokka is a Senior Research Engineer at Lightning AI and one of the core maintainers of the PyTorch Lightning library. He has prior experience in building production scale Machine Learning and Computer Vision systems for several products ranging from Video Analytics to Fashion AI workflows. He has also been a contributor to a few other open-source projects and aims to empower the way people and organizations build AI applications.
MEET SOME OF THE STARTUPS THAT HAVE JOINED US:
GENERATIVE AI HACKATHON
Join us on MAY 11th for the ultimate Generative AI hackathon, where you’ll have the opportunity to showcase your skills, learn from other experts in the field, and create something truly unique! Whether you’re an experienced developer or just starting out, this hackathon is the perfect opportunity to apply your skills and creativity to generative AI
Not only will you gain invaluable experience and insights, but you’ll also have the chance to win prizes and gain recognition for your work. Whether you’re looking to kick-start your career in generative AI or take your skills to the next level, our hackathon is the perfect opportunity to showcase your talent and make connections with others in the field.
STARTUPS PARTICIPATED AT ODSC EAST
Startups Sessions Include:
Human-Friendly, Production-Ready Data Science with Metaflow
What I love and hate about Dask
🤗 Transformers & 🤗 Datasets for Research and Production
AI for Healthcare: A Practical Application of AI/ML in Pediatric Behavioral Healthcare
AI Observability: How To Fix Issues With Your ML Model
An Introduction to Drift Detection
Automation for Data Professionals
Building and Deploying the World’s Largest Rock/Paper/Scissors Competitive Ladder App in X Minutes with Roboflow and Streamlit
Creating a Benchmark for a Large-Scale Image Captioning Pipeline
Data Boards: A Collaborative and Interactive Space for Data Science
Data Science in the Cloud-Native Era
Deep Dive Workshop for Apache Superset
Deep Learning Enables a New View in the Agriculture Industry
Intro to Deep Learning in R
Drift Detection in Structured and Unstructured Data
Feature Engineering on the Modern Data Stack
Full-stack Machine Learning for Data Scientists
Introduction to the PyTorch Lightning Ecosystem
MLOps: From 0-60 with Pachyderm
Noiseless Anomaly Detection with Streaming Graph A.I.
The Future of Software Development Using Machine Programming
The Origins, Purpose, and Practice of Data Observability
What I love and hate about Dask
Tower of Babel: Making Apache Spark, Apache Mahout, Kubeflow, and Kubernetes Play Nice
Unlocking the Value of Siloed Data with Multi-party ML
Vector Databases
MORE WAYS TO PARTICIPATE AT ODSC WEST
AI Founders
Build awareness and recognition and share your story of success during our AI Founders event. This event will feature short presentations from founders like you, who have done the hard work of coming up with an innovative idea, finding investors, and starting a company from scratch.
AI Expo & Demo Hall Registration
Interested in Attending And Meeting Top Startups?
Free and Paid Passes are available now.
In-person passes are sold out online, but you can still buy a pass on spot
Save 20% on Full Price
Invenstor Office Hours
Schedule: May 11th, Expo Hall
Igor Taber is the founder and General Partner of Cortical Ventures an early-stage AI-focused venture fund. Cortical Ventures was started to invent, incubate and invest in the companies leading the AI revolution. Previously, Igor was an early investor and SVP of Corporate Development at DataRobot. He raised >$500M in growth capital. Prior roles include managing director at Intel Capital and was recognized as one of the most active investors in AI.
Get expert advice and insights from Igor and other top VCs at our on-site office hours! Join us for a unique opportunity to connect with investors and gain valuable feedback on your startup or project.
*Exclusive to ODSC and Expo Hall Pass holders.
SEE WHO ATTENDS ODSC EAST
As an applied data science conference, each ODSC event attracts professionals including data scientists, managers, founders, innovators and CxOs from many companies across the industry. Request Who Attends brief to see some of the attending professionals and companies from 2022.