I've programmed my own virtual self with deep learning to answer your questions about me. I created him with a deep neural network with TensorFlow, and he will try his best to answer all of your questions.
AI Chatbot
I'm Arie, an undergraduate from Indonesia currently studying EEE at Imperial College London in the UK. I've always been interested in technology, from my solar energy TED-talk in New York City, studying Machine Learning and AI at Stanford, as well as doing research on the emerging field of geometric deep learning and its applications on wireless communication networks.
I am currently a student at Imperial College London studying EEE, which has allowed me to bridge my passion for software and hardware. Moreover, to keep up with the data-driven future, I spent the summer of 2020 studying machine learning and AI at Stanford University.
I've developed and refined skills in a number of fields, both through rigorous academic studies as well as work experience and mentorship. These include proficiencies in software, hardware, data science and analytics, and management consulting.
My interests primarily lie in the area of tech. This includes a mixture of AI & Deep Learning, 5G Communication and Wireless Networks, Renewable Energies, as well as IoT. My hobbies are playing tennis, golf, swimming, and reading techy books and news.
In 2017, I delivered a TED talk in New York City about the urgency for the world to transition to a solar-dependent and renewable future. In addition to this, I built a prototype of a solar tree - a practical, designer-friendly device which charges your phone with the solar energy.
I am currently a data science intern at Xilinx, working under the CSPG department on the new line of Xilinx adaptable technology known as ACAP (Adaptive Compute Acceleration Platform) - a highly integrated, multicore compute platform that enables adaptability whilst maintaining the performance of traditional ASICs.
The emerging field of Geometric Deep Learning enables the direct use of deep learning in datasets with a non-euclidean representation, such as graphs. I am currently working on a research project to study how Graph Neural Networks can be applied to solve the classic power allocation problem in wireless communication networks.
IC Hack is the biggest annual student-run hackathon in the UK. Here, I and a friend built an off-grid radio communications system to allow long-distance messaging in remote parts of the world without internet connection, winning the 2nd place for the category of 'best hack for the community'.
As part of the Stanford data science program, I performed a detailed statistical and predictive modelling using recurrent neural networks (RNN) and gradient boosting on a large dataset of patients with Schizophrenia to study the efficacy of a new drug in treating the mental disorder.
I was a project manager at the Imperial Consulting Group (ICG), where I led a team of 7 students in a Santander Bank project to research the growing competition between highstreet banks and emerging FinTech companies; in particular to determine its niche amongst the younger generation.