Shell.ai hackathon for sustainable and affordable energy
Shell.ai Hackathon for Sustainable and Affordable Energy brings together brilliant minds passionate about digital solutions and AI, to tackle real energy challenges and help build a lower-carbon world where everyone can access and afford energy.
Shell.ai Hackathon 2023: Agricultural Waste Challenge
Meet the winners of Shell.ai Hackathon for Sustainable and Affordable Energy: Agricultural Waste Challenge
This year’s edition of Shell.ai Hackathon was nothing short of extraordinary. We hit the participation record with 5,762 registrations and 9,400 submissions, which is an astounding response to a complex challenge the participants faced this year: optimising a supply chain of agricultural waste collection. For the first time in the hackathon’s history, top finalists from different parts of the world came to pitch their solutions live on stage during the Changemakers of Tomorrow at the Shell Technology Centre in Bangalore. They meet face-to-face with Shell.AI leaders and celebrated their success together with the Shell.ai Hackathon team.
Each team presented a unique vision, creative approach to the problem, and a true passion for accelerating a future where digital solutions tackle complex problems in the energy sector. The winners of the University Edition will further explore the opportunity of an R&D project with Shell.
Team Midas
University Edition winner
Team Members:
Wei Ping Lam, PHD Student of Chemical Engineering at Rice University, Houston, Texas, USA
Wei Ping about his solution: “I reformulated a multi-faceted supply-chain optimisation problem into a single-objective one. Looking at the data I realised the transportation costs of residual biomass are much less than its under-utilisation costs, which implied the biorefineries and depots must operate at maximum capacity, with zero under-utilisation costs, further reduced by placing depots close to refineries. In the commercialisation phase, I took advantage of remote sensing data (satellite data on rainfall and agricultural production for a region). This method combined high-performance computing gave amazing results. I also used an idea of a collaboration platform where experts help scale and deploy the solution.”
Team Perception
General Edition winner
Team Members:
Parth Singhal, Senior Analyst at Goldman Sachs
Sakshi Tyagi, Senior Data Scientist at Siemens Advanta
Team Perception about their solution: “We managed to solve a complex problem with an easy solution by leveraging open-source data and cutting-edge technology. An analysis of different open-source data (from the government of India and the state of Gujarat) was our starting point. Then, we integrated it to our model to predict the biomass forecast. We also made our highly optimised and customisable clustering algorithm from scratch! For us, the solution is not only about data and the algorithm, but about creating a tangible impact.”
Team Shello There
University Edition Runner up
Team Members:
Vibin Mathiparambil Vinod, EEE student at Nanyang Technological University in Singapore
Vibin about his solution:
“I found the optimisation part of the problem statement particularly inspiring. What’s innovative about my solution is the use of a simple statistical model and external data on rainfall and altitude. My strategy for commercialising the product is creating a software or a web app where clients could upload the data and set their own parameters.”
Team Optima
General Edition runner up
Team Members:
Sagnik Das
Arun Raman
Team Optima about their solution: “We worked under the assumption of a future when biomass is produced on a larger scale than food, with individual households taking part in the biomass generation. This vision also includes irregular harvest cycles as well as biomass being traded as stock. Households sharing the volume of their own produce was key to optimising the supply chain. Our solution is customizable to different computational infrastructures, making it widely accessible.”
Team <45xTrlop!*
General Edition 2nd runner up
Team Members:
M Barak Ouro-Akondo, Data Analyst and Supply Chain Management student at HESTIM Engineering and Business School, Casablanca, Morocco
Jacintho Mpeteye, Python Developer and Industrial Engineering student at HESTIM Engineering and Business School
Japhet Ayassou, Industrial Engineer, Junior Consultant in Innovation Funding at Leyton
Team <45xTrlop!* about their solution: “ We focused on efficiency, sustainability and reliability. To overcome the limitations of our hardware, we adopted a divide-and-conquer strategy and broke down the problem into manageable pieces. What’s unique in our approach is that the batches aren’t isolated and the data feedback guarantees the constraints are satisfied at a global level. Achieving efficiency is also about doing the best with what you have – this is what we did!”
Shell.ai Hackathon 2022: EV Charging Network Challenge
Shell.ai Hackathon 2022: EV Charging Network Challenge
Meet the winners of 2022 Shell.ai Hackathon: EV Charging Network Challenge
In 2022 edition of the hackathon, Shell, together with Microsoft and Udacity, invited participants to solve EV Charging Network Challenge. The task was to optimise an electric vehicle (EV) charging network, so it remains robust to demographic changes and meets customer demand. The competition saw over 3,900 registrations. 20 shortlisted teams competed for the win. Meet the top teams behind the winning solutions!
General edition winners
1st Prize
Pratyaya Bhattacharyya
Pratyaya is the lead data scientist of the AI solutions team at Wipro. He has eight years of experience as a consulting statistician in the domain of finance, retail, manufacturing, energy and healthcare. Pratyaya holds a Master's degree in Operations Research from Indian Statistical Institute. He is an avid reader, passionate about Bengali classics, who also enjoys chess and bridge.
2nd Prize
Rupesh Gupta and Sanket Sinha (team)
Rupesh is a Portfolio Manager at a Quantitative Systematic Hedge Fund, managing the commodity exposure of the firm. He is a machine learning enthusiast and has a keen interest in maths, physics and technology. Rupesh has won a Gold Medal in the Indian National Physics Olympiad and holds a management degree from IIM Lucknow and a B.Tech from IIT Kharagpur
Sanket is passionate about technology and its application in solving real-life problems. His present focus is machine learning, including deep learning. He has conceptualised the complete roadmap for a state-of-art artificial intelligence platform to accelerate AI adoption in enterprises, developed applied deep learning pipelines, built a team from scratch, and delivered a production-ready platform for ignio™ – The Autonomous Enterprise Software from TCS. He holds a management degree from the Indian IIM, Ahmedabad, and a B.Tech from the IIT, Kharagpur.
3rd Prize
Meson Labs
Ashish Sharma, Director Solutions at Meson Labs (left)
Ritu Sinha, Founder- of Research at Meson Labs (middle)
Dr. Çağla Odabaşı Özer – Data Scientist Director and Head – High Voltage Battery Systems - project mentor and advisor (right)
Meson Labs is a start-up dedicated to bringing new age technologies (Machine Learning and AI) to develop innovative solutions in Healthcare, Retail Education and Social Issues. Meson Labs develops purpose-built solutions using AI/ML supported by IoT and automation tools for company defined problems.
University edition winners
1st Prize
Team MOMA
Mohammad Lameh (left)
Marcello Di Martino (right)
Mohammad is a Ph.D. Candidate in Chemical Engineering at Texas A&M University. He holds a Bachelor of Engineering in Chemical Engineering from the American University of Beirut and Master of Science in Chemical Engineering from Texas A&M University at Qatar. His research is focused on developing high-level analysis methods and multiscale optimization models for guiding cost-efficient emissions reduction strategies.
Marcello is a third year PhD student in the Artie McFerrin Department of Chemical Engineering at Texas A&M University in the Multi-parametric Optimization & Control Group. His research focuses on surrogate modeling and optimization applied to integrated and interconnected process systems, such as the food-energy-water nexus. He holds M. Sc. in Chemical Engineering and B. Sc. In Industrial Engineering at RWTH Aachen University.
2nd Prize
Team J3T
Johnny Tiu (right)
Shankar Ramcharak (left)
Johnny Tiu obtained his BSc. & M.Phil. in Mechanical Engineering at the University of the West Indies (UWI). As a Research Assistant at UWI he formally outlined and developed the methodologies that undergraduate students & fellow researchers use to collect vibration data and a tool to semi-automate vibration testing. His research interests are Data Analysis, Vibration Control, and Acoustics. His hobbies include 3D printing & prototyping and musical instruments (guitar, violin, piano)
Shankar Ramharack is a final year Electrical and Computer Engineering student at the University of the West Indies (UWI) currently specialising in Energy Systems. Some of his student projects include using Bi-Directional Neural ODEs in load forecasting, assisting in developing a framework for Data-Logging in Battery Electric Vehicles, and fault location in transmission lines models using changepoint detection. His interests lie in data driven engineering and using statistical analysis to develop robust and efficient energy systems.
Start-up edition winners
1st Prize
Meson Labs
Ashish Sharma, Director Solutions at Meson Labs (left)
Ritu Sinha, Founder- of Research at Meson Labs (middle)
Dr. Çağla Odabaşı Özer – Data Scientist Director and Head – High Voltage Battery Systems – project mentor and advisor (right)
Meson Labs is a start-up dedicated to bringing new age technologies (Machine Learning and AI) to develop innovative solutions in Healthcare, Retail Education and Social Issues. Meson Labs develops purpose-built solutions using AI/ML supported by IoT and automation tools for company defined problems.
2nd Prize
Evotrack
Oytun Babacan (left), CEO and Founder of Evotrack, is a mechanical engineer and established research scientist with 10+ years of experience in sustainable energy system modelling including solar PV and energy storage systems.
Emre Eran (middle), Cloud Architect at Evotrack, is a senior software engineer with 12+ years of experience in designing and developing highly technical software solutions including for sustainable energy services.
Derin Babacan (right), Research Scientist at Evotrack, is a senior data scientist and machine learning engineer with 20 years of experience in high-tech software product development in Silicon Valley companies.
The electric vehicle infrastructure is rapidly growing, and market dynamics are becoming complex. In this fast-changing landscape making smart investment and operation decisions will depend on automated expert data intelligence. Evotrack develops proprietary software using specialized learning-based algorithms to identify factors affecting the evolution of the charging demand and deliver correct deployment and operation strategies for charging supply.
Shell.ai Hackathon 2021: AI Solar Power Prediction Challenge
Shell.ai Hackathon 2021: AI Solar Power Prediction Challenge
Meet the winners of 2021 Shell.ai Hackathon: AI Solar Power Prediction Challenge
Shell.ai hackathon’s ambition is to create AI-based solutions to make energy more sustainable and affordable. In this edition, we asked the participants to predict the percentage of total cloud coverage and Global Horizontal Irradiance (GHI) over a solar farm to better forecast its power production.
The winners rose to the challenge and developed solutions that were accurate, innovative and scalable.
Meet the bright minds behind the winning solutions and read about their experience of the hackathon. Congratulations to the winners!
General edition winners
1st Prize
Dr. Sukanta Basu
Associate Professor
Delft University of Technology
I’ve been doing renewable energy related research for last almost 20 years. I’ve also had experience with machine learning going back to 1999, but for the last two years I’ve spent a lot of time understanding the new deep learning tools that could really help my research. This hackathon was a challenging one, full of excitement (and some frustration) – I had my ups and downs working on the solution. But if you know the domain reasonably well, I think machine learning can do miracles for you. I guess all these years spent studying atmospheric physics actually paid off.
2nd Prize
esk.AI
Ricardo Lara, PhD candidate in petroleum engineering at The University of Texas at Austin (left)
Roderick Perez, physical engineer, Data Science student at University of Vienna (right)
Ricardo: This hackathon has been a great networking experience. Me and Roderick never met in person. We connected in social media and decided to form a team. It was stimulating to discuss our ideas and get feedback from Shell and NVIDIA mentors, get inspired by these conversations and put new ideas into action.
Roderick: Both of us have background in oil-and-gas engineering and we are both passionate about access to energy. For me, it was an opportunity to step into the world of renewable energy and prove to myself I can be a part of a solution to the world’s current climate challenges.
3rd Prize
peaceHai
Akshat Gupta, data scientist (left)
Sumit Yadav, data scientist (right)
Sumit: We’ve been working together in similar competitions for the past two years and got very intrigued by this challenge, as we realise forecasting energy production in solar farms and its impact on supply and demand is a valid problem in the energy space.
We are motivated by a vision of making a real change, so we are thinking about publishing a paper and releasing our source code so the whole community can benefit from our solution.
Akshat: We loved the competitive nature of this hackathon. Monitoring the leaderboard and continuously improving the accuracy of our algorithm to get ahead of other teams kept us going. But it was about more than good scores. We paid extra attention to our model being scalable and deployable, so real people can use the technology to make their lives better.
Special start-up edition winners
Meson Labs
Ashish Sharma, data scientist at Meson Labs (left)
Ritu Sinha, Founder- Director and Head of Research at Meson Labs (right)
Ashish: At Meson Labs we work mostly on AI machine learning solutions for three sectors: education, healthcare, and climate technology. We look at applications of technology that make a sustainable impact, so the hackathon sparked our interest immediately.
Personally, I got interested in renewable energies, as my father who had worked lifelong designing and commissioning steel plants, coal powered blast furnaces, moved into solar power and renewables. It’s exciting to be able to use the skillset and talent we have at Meson-Labs to create something that can have a long-term positive impact on the climate. We built our models with deployment and scalability in mind.
Akira.Insights
Akhil George, data scientist (right) and full team (left)
Akhil: Akira.Insights is a small start-up that provides data science and artificial intelligence solutions. When we saw the hackathon’s problem statement, we decided to challenge ourselves and see if we can crack it and how far we will go.
We invested a lot of time and effort in our solution and at the end of the day it was extremely rewarding, as we believe that our products can directly help companies and society. I have experienced the intermittency of solar power first-hand, as my home is fully solar-powered. It’s a great feeling to work on something that touches you in such a direct way.
Access to NVIDIA’s GPU cluster was a game changer for us. The computing power made it fast and easy to try out different solutions. Personally and professionally, I feel this hackathon pushed me to the next level.
