News

• [September 2020] I published my first photo blog, Iceland day-0, at aroraakshit.me.

• [September 2020] Deepshikha Kumari and I gave a talk about How to become a Data Scientist? at IIT Bombay (placement webinars). Handout available here.

• [August 2020] Srishti Yadav and I gave a talk on Scalable Hyper-Parameter Tuning using RAPIDS on AWS at PyBay 2020. GitHub repo with presentation here.

• [August 2020] Siddha Ganju and I mentored the DisruptCNN team at GPU Hackathon 2020 (organized by Brookhaven National Laboratory).

• [August 2020] Mentored students on creating, finding and interviewing for the right opportunities in the software industry during COVID-19 via UnsaidTalks platform. More information here.

• [July 2020] I enjoy talking to students about deep learning/machine learning. Here is a blog on one of such conversations - [Deep Learning] Conversation with Akshit Arora, NVIDIA.

• [June 2020] Gave a talk on Accelerating Machine Learning with GPUs at AI Camp. GitHub repo with presentation here.

• [December 2019] Attended NeurIPS in Vancouver, BC.

• [September 2019] Joined the Solutions Architect team at NVIDIA as a Data Scientist. I work with NVIDIA’s partners to optimize and accelerate deep learning and machine learning pipelines at scale.

• [May 2019] Graduated from University of Colorado Boulder with a Master’s in Computer Science.

• [January 2019] Back at WootMath for another internship. Built a serverless Business Intelligence pipeline using Google Cloud Platform (BigQuery, Pub/Sub and StackDriver Logging) and Apache Beam.

• [November 2018] Created an artificially intelligent auto-complete extension to Mozilla’s VR project, A-painter, using SketchRNN by Google. GitHub repo here.

• [August 2018] Joined Prof. Claire Monteleoni’s Machine Learning research group.
  • Built a CNN based prediction model for classifying Indian Summer Monsoons using PyTorch.
  • Collaborated with Dr. Moumita Saha.

• [July 2018] Presented Does Deep Knowledge Tracing Model Interactions Among Skills? at 11th International Conference on Educational Data Mining Conference in Buffalo, NY. Full paper available here. Collaborated with Dr. Shirly Montero, Prof. Michael C Mozer, Dr. Sean Kelly and Dr. Brent Milne.
  • Travel fellowship award by University of Colorado Boulder.

• [June 2018] Published Learning in an interactive simulation tool against landslide risks - the role of strength and availability of experiential feedback at Journal of Natural Hazards Earth System Sciences. Full paper available here. Collaborated with Pratik Chaturvedi and Dr. Varun Dutt.

• [May 2018] Joined WootMath, Boulder, CO as an intern.
  • Trained a recurrent neural network (RNN) based stroke data classifier with ~70% accuracy using TensorFlow’s Estimator API.
  • Fine-tuned the model for mathematical categories using synthetic data.

• [May 2018] Built a real-time and scalable machine learning based toxicity monitoring tool.
  • Prototyped the model using Keras, trained the final model on Wikipedia’s detox dataset using Apache Spark, deployed on AWS Lambda to analyze tweets in real-time using Apache Storm, visualized on Kabana dashboard.
  • GitHub repo here.
  • Collaborated with Hasil Sharma, Paramjot Singh and Ajay Kedia.

• [April 2018] Won the Outstanding Poster Award (Master’s of Science category) at the Graduate Student Research Expo organized by Department of Computer Science at University of Colorado Boulder.

• [January 2018] Joined Prof. Michael Mozer’s research group.
  • Researched on tracing student’s knowledge state on online tutoring platforms, as an extension to this project.
  • Trained and evaluated RNN based deep learning models using TensorFlow for deep knowledge tracing and compared them with Bayesian knowledge tracing. Collaborated with Dr. Shirly Montero.

• [November 2017] Served as Teaching Assistant for the following undergraduate courses:
  • Fall 2017: Introduction to Computer Science
  • Spring 2018: Introduction to Data Structures
  • Fall 2018: Introduction to Computer Science
  • Spring 2019: Introduction to Social Statistics

• [May 2017] Graduated from Thapar University, Patiala, India with a Bachelor’s in Computer Engineering.

• [January 2017] Back at Applied Cognitive Science Lab. Collaborated with Akash Rao.
  • Designed first-person-shooter and search-and-rescue scenarios in augmented reality, deployed marker-less GPS based mobile application using Vuforia and Unity 3D (coded in C#).
  • Experimented with other libraries, including Kudan AR, AR Toolkit, Microsoft HoloLens, Google Tango.

• [July 2016] Presented Interactive Landslide Simulator - A tool for Landslide Risk Assessment and Communication at International Conference on Digital Human Modeling and Simulation in Orlando, FL. Paper available here. Collaborated with Pratik Chaturvedi and Dr. Varun Dutt.
  • Travel Fellowship Award by Thapar University and Indian Institute of Technology, Mandi.

• [June 2015] Joined Prof. Varun Dutt’s Applied Cognitive Science Lab at Indian Institute of Technology (IIT), Mandi, India. Created a serious game for education about landslides.
  • Studied the effect of affective feedback on awareness about landslide mitigation techniques in the Himalayan region.
  • Designed and analyzed a novel cognitive model for simulating landslides and its economic effects using Monte-Carlo simulations.
  • Built and interactive simulation tool to be used for doing what-if analysis for policy decisions and educating people living in vulnerable zones.
  • Collaborated with Pratik Chaturvedi.

• [June 2014] Attended the International Workshop on Machine Learning Algorithms and Data Analytics organized by IEEE Computer Society, Thapar University, Patiala, India. Advisor - Prof. Deepak Garg.