About

Arslan Siddiqui is a highly skilled Software Engineer with 3.86 years of relevant experience in the field. Currently working at Microsoft, he has previously worked as a Software Development Engineer at DataCore Software, where he led the development for the new licensing model. He collaborated with cross-functional teams to facilitate a transition from a term-based model to a subscription-based model and made improvements to the REST API to enhance communication between the client and the License Server. Arslan also overhauled the license enforcement code within the client to support the new licensing model and made improvements to the UI so that the new licensing features are intuitively understood by users. Arslan has also worked as a Research Assistant at Computational Neuroengineering Lab, where he implemented Information-Theoretic Learning (ITL) framework and created the Divergence-to-Go (DtG) framework as a method for guided exploration of a state-action space. He compared the speed and thoroughness of DtG with random exploration on 2D mazes of varying complexity and ran Monte Carlo simulations for each maze, finding an average increase of 11 times in speed as compared to random exploration. Arslan is currently working on Kernel Adaptive Filtering using time series data to study the application of DtG on sequential problems like Mountain-car and Cartpole. Arslan has a Master of Science degree in Computer Science from the University of Florida and a Bachelor's degree in Computer Science from Vellore Institute of Technology. He also has a High School degree in Economics from Delhi Public School Mathura Road. Arslan's tech stack includes Software Engineering, UI, Research Science, AI, and Python. Arslan is a proactive and result-oriented individual who takes ownership of his work and strives for excellence. He has excellent communication and interpersonal skills and is highly organized and detail-oriented. Arslan is a valuable asset to any organization and is always eager to learn and take on new challenges.