Companies

Polymer companies spend over US$300 million annually towards formulation development. Primary ways of formulation still rely on trial and error methods which results in substandard products and delayed time-to-market.

Polymerize is incorporating relationships between material structure, property and processes to create a Machine Learning driven formulation engine into the core of their product-life-cycle platform. This reduces experimentation in formulation development and fills in R&D gaps, accelerating time-to-market for new products to 1/3 of their usual duration and at almost 1/2 the cost.

Kunal Sandeep has over 10 years of industry experience in product development and management. He consulted with KPMG and managed product implementation across banking, telecom and insurance. He was the founder of several venture backed B2B & B2C companies.

Dr Abhijit Salvekar has a PhD in Material Science from NTU, with 160 citations and 3 patents. He has spent over 10 years as a polymer scientist at the National Chemical Laboratory (Pune), BASF and AGC. His expertise is in Process-Structure-Property Relationships and DoE, and he was nominated for Schmidt Science Fellows.

Industrial facilities like power plants and refineries spend over €100B every year in maintenance. And yet, there is one industrial accident every five hours in France alone. The reason: a poor knowledge of ageing facilities!

Samp creates safer industrial facilities by providing reliable knowledge for everyone. Starting from a scan of the site, they use Machine Learning to generate a data-enriched 3D model of the facility: an intelligent Digital Twin shared by all.

They are delivering two paid PoC for energy players in France and are engaging with major players across Europe.

Laurent Bourgouin has over 15 years of experience in the energy industry, delivering key roles for both facility operators and engineering firms. In his last role, he was Technical Director for Dassault Systèmes, leading the Digital Transformation of industry heavyweights like ExxonMobil, BP and EDF.

Shivani Shah holds PhD from French Nuclear Research Institute CEA, where she worked on developing solutions for applying Machine Learning to Large Datasets, which makes her uniquely positioned to build digital twins from the massive data gathered from the industrial sites.

Using heat to separate and purify the components of large quantities of chemical mixtures is the most common and inefficient way in industry. The energy consumption of these processes such as evaporation and distillation accounts for 10 to 15 percent of the world’s annual energy use. SEPPURE created a chemically resistant nano-filter that does not use heat and separates chemicals at a molecular level. Our technology reduces the energy consumption of thermally-based chemical separations by at least 10X, and produces higher quality products.

Mohammad H. D.A. Farahani

Dr. Farahani holds a Ph.D. in Membrane Technology from the National University of Singapore, where he has developed chemically-resistant membranes and received the “Outstanding Postgraduate Research Thesis Award 2018” from the American Institute of Chemical Engineers for his contribution. He has 2 patents on membranes and more than 7 years of membrane-related experience. Dr. Farahani has published more than 30 prestigious peer-reviewed publications and one book chapter with 400+ citations.

Amir Hooshang Taheri

Dr. Taheri holds a Ph.D. in Membrane Technology from the Nanyang Technological University of Singapore. He has over a decade of membrane-related experience in both academia and industry. He has 2 patents and more than 20 publications with 600+ citations. Dr. Taheri has a business development experience working as a consultant for SNF, Headquartered in France—the number one Polyacrylamide manufacturer in the world.

ShapeNine‘s AI designs DNA structures to control industrial applications with nanoscale precision. Biosensing, chemical, electronics and pharmaceutical industries require molecular precision, but current production methods are reaching their limits, achieving minor improvements at an increased cost.

ShapeNine leverages the programmability & nanoscale precision of DNA to enable the cost-effective leap these industries need. By treating DNA as an engineering material, our deep learning software generates functional designs optimised for the specific task.

We are testing our technology with two American companies that develop biosensors for diagnostics, environmental & food safety applications.

Andrés Aldana developed DNA-based semiconductor nanowires to print pol-
lution sensors and optical barcodes during his PhD in Chemical Nanoscience. At IMEC, he created engineered magnetic nanoparticles for targeted tumour therapies. Andres holds an MSc in Bionanotechnology from KU Leuven.

Orest Mykhaskiv completed his PhD in Aerodynamic Shape Optimisation. Orest developed algorithms that improve the shapes of aerospace and automotive components. He used these methods at Volkswagen and applied 3D Deep Learning and generative design to accelerate manufacturing of the components at Autodesk Research.

SixSense is building a defect prediction platform using Artificial Intelligence and IoT Analytics. We analyze terabytes of factory floor data to predict occurrence of a defect, identify its root cause, and recommend corrective action. This will help manufacturers contain excursions that today lead to rework, scrap, warranty claims, and product recall. We envision a defect-free world that has realized the dream of Industry 4.0.

Akanksha Jagwani

Akanksha Jagwani is a Mechanical Engineer from IIT. She has worked with manufacturing giants such as Hyundai Motors and General Electric and has researched at Washington University and A*STAR. She also led digital product design and management teams at million-dollar startups, Embibe and Headout.

Avni Agrawal

Avni Agrawal is a Computer Science Engineer from NIT. She has extensive experience in Big Data Analytics and Machine learning at D. E. Shaw and Visa and cleared CFA levels. She built platforms for petabytes of transactional data and filed a trade secret for a unique analytics model.

Making batteries that work well in any situation is hard- the battery used in an EV is very different to the one used in your phone. There are thousands of possible material combinations and potential configurations to choose from and even expert battery engineers make their decisions based on trial and error.

Surge Analytics solves the battery development problem by providing SaaS simulation software powered by AI to enable rapid, cost-effective battery R&D.

Their simulations deliver cost-performance-safety optimised insights into battery designs and can reduce annual R&D costs by 80% and cycles by 90%.

Ollie Graham has a Biochemistry degree and was a CFA Charterholder from 2009-2013. He spent 15 years in financial services, culminating with being a Vice President and trader at Morgan Stanley. In 2015 he switched careers to software engineering where he developed AI/ML algorithms for health and security applications.

Dr Vishvak Kannan has a PhD from NUS in collaboration with Cambridge in Chemical Engineering with a focus on energy systems. During his PhD, he developed algorithms to integrate physical phenomena with ML and is a leading expert in this field. For his thesis, he identified scenarios in which a Sony 18650 Li-ion battery might explode!

Additive Manufacturing opens new opportunities for smart industrial productions. Unfortunately, the aeronautics and automotive industries still produce parts by relying on simple designs, as a result of a lack of tools and limited human intuition.

At TOffeeAM, we have created an automatic design software able to produce intelligent, complex and efficient designs suitable for AM. Our solutions are up to 40% more efficient and can be produced 20 times faster. Our software has already been used by GE Aviation, BHGE and F1 teams.

FRANCESCO MONTOMOLI
Francesco is an Imperial College reader and a RAEng Enterprise Fellow. He holds a PhD in Energy Engineering and studied Management of Technology at Cambridge. He is a former employee of GE and boasts collaborations with Rolls-Royce, NASA, Airbus and Criepi, becoming an expert in Uncertainty Quantification.

MARCO PIETROPAOLI
Marco is an EPSRC Doctoral Prize fellow at Imperial College where he completed his PhD in Fluid Dynamics. He holds a MSc in Mathematics and has expertise in AI software for Additive Manufacturing. He boasts a collaboration with NASA Langley and he is an MBA student at the Smartly Institute of Washington DC.

AUDREY GAYMANN
Audrey is a final year PhD candidate at Imperial College. She holds a MEng from Imperial College Aeronautics where she strengthened her expertise in robust analysis. She is a former visitor student at NASA and an Amelia Earhart Fellow, named as one of best the 32 female PhDs in the world working in Aerospace.