Rakshit Agrawal

I am an Applied Scientist at Camio. I completed my PhD in Computer Science from the University of California, Santa Cruz. I work towards research in Machine Learning, Artificial Intelligence, and Computer Vision. My PhD dissertation is on Generalized Learning Models for Structured Data. My additional research projects span across Crowdsourcing, HCI, ICTD and Data Science for Social Good.

I am also interested in the domain of Machine Learning and Society and often work on related projects and content. I developed and conducted the graduate course on Applied Machine Learning for Social Good at UC Santa Cruz in Spring 2019. [Link]

  • Curriculum vitae
  • Resume

Publications

Generalized Learning Models for Structured Data

Rakshit Agrawal
UC Santa Cruz [Link]
2019

Learning Edge Properties in Graphs from Path Aggregations

Rakshit Agrawal, Luca de Alfaro
Proceedings of the 2019 World Wide Web Conference (WWW'19) [Link]
2019

Attention in Recurrent Neural Networks for Ransomware Detection

Rakshit Agrawal, Jack Stokes, Karthik Selvaraj, Mady Marinescu
2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '19)
2019

ScriptNet: Neural Static Analysis for Malicious JavaScript Detection

Jack W. Stokes, Rakshit Agrawal, Geoff McDonald, Matthew Hausknecht
arXiv Pre-print at https://arxiv.org/abs/1904.01126 [Link]
2019

A New Family of Neural Networks Provably Resistant to Adversarial Attacks

Rakshit Agrawal, Luca de Alfaro, David Helmbold
arXiv Pre-print at https://arxiv.org/abs/1902.01208 [Link]
2019

Identifying Fake News from Twitter Sharing Data: A Large-Scale Study

Rakshit Agrawal, Luca de Alfaro, Gabriele Ballarin, Stefano Moret, Massimo Di Pierro, Eugenio Tacchini, Marco L. Della Vedova
arXiv Pre-print at https://arxiv.org/abs/1902.07207 [Link]
2019

Robust Neural Malware Detection Models for Emulation Sequence Learning

Rakshit Agrawal, Jack W. Stokes, Mady Marinescu, Karthik Selvaraj
2018 IEEE Military Communications Conference (MILCOM) [Link]
2018

Neural Classification of Malicious Scripts: A study with JavaScript and VBScript

Jack W. Stokes, Rakshit Agrawal, Geoff McDonald
arXiv Pre-print at https://arxiv.org/abs/1805.05603 [Link]
2018

Neural Sequential Malware Detection with Parameters

Rakshit Agrawal, Jack W. Stokes, Mady Marinescu, Karthik Selvaraj
2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '18) [Link]
2018

Reputation Systems for News on Twitter: A Large-Scale Study

Luca de Alfaro, Massimo Di Pierro, Rakshit Agrawal, Eugenio Tacchini, Gabriele Ballarin, Marco L. Della Vedova, Stefano Moret
arXiv Pre-print at https://arxiv.org/abs/1802.08066 [Link]
2018

Learning User Intent from Action Sequences on Interactive Systems

Rakshit Agrawal, Anwar Habeeb, Chih-Hsin Hsueh
AAAI Workshop on AI and Marketing Science (AAAI AIMS 2018) [Link]
2018

Learning From Graph Neighborhoods Using LSTMs

Rakshit Agrawal, Luca de Alfaro, Vassilis Polychronopoulos
AAAI Workshop on Crowdsourcing, Deep Learning and Artificial Intelligence Agents [Link]
2017

Predicting the quality of user contributions via LSTMs

Rakshit Agrawal, Luca de Alfaro
Proceedings of the 12th International Symposium on Open Collaboration (OpenSym'16) [Link]
2016

QuickResponseHost: Enabling crowdsourced disaster response stations

Rakshit Agrawal, Aaron Springer, Emily Lovell
2015 IEEE Global Humanitarian Technology Conference (GHTC 2015) [Link]
2015

Collaborative systems with applications for social good

Rakshit Agrawal
Companion to the Proceedings of the 11th International Symposium on Open Collaboration (OpenSym'15) [Link]
2015

KrishiEkta: integrated knowledge and information distribution system for Indian agriculture

Rakshit Agrawal, Mridu Atray, S Krishna Sundari
Proceedings of the 4th Annual Symposium on Computing for Development (ACM DEV 2013) [Link]
2013

Exploring suitable interfaces for agriculture based smartphone apps in India

Rakshit Agrawal, Mridu Atray, S Krishna Sundari
Proceedings of the 11th Asia Pacific Conference on Computer Human Interaction (APCHI 2013) [Link]
2013

Sensor network architecture for soil and weather data extraction and database generation

Rakshit Agrawal, Mridu Atray, S Krishna Sundari
Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems (ACM SenSys 2012) [Link]
2012

Concept to design a hand-held crop management device (CMD) for farmers

Rakshit Agrawal, Mridu Atray, S Krishna Sundari
Proceedings of the 2nd ACM Symposium on Computing for Development (ACM DEV 2012) [Link]
2012

Experience

Camio

San Mateo, Califronia
Applied Scientist

Artificial Intelligence and Computer Vision [Link]

Sept 2019 - Present

University of California, Santa Cruz

Santa Cruz, Califronia
Graduate Student Instructor

Developing and teaching graduate course on Applied Machine Learning for Social Good [Link]

April 2019 - June 2019

University of California, Santa Cruz

Santa Cruz, Califronia
Graduate Student Researcher, Teaching Assistant

Research in Machine Learning, Reputation Systems and Crowdsourcing. Assisted for courses: Web Applications, Software Engineering, Algorithms and Abstract Data Types, Mobile Applications, Introduction to Computer Science

Sept 2014 - June 2019

Nvidia

Santa Clara, California
Deep Learning Architecture Intern

Worked on resilient neural network architectures for autonomous vehicles.

Nov 2018 - Mar 2019

Microsoft Research

Redmond, Washington
Research Intern

Worked on developing algorithms and models for Machine Learning in Computer Security. Developed Malware Detection models using Deep Neural Networks.

June 2017 - Sept 2017, Nov 2017 - Jan 2018, June 2018 - Sept 2018

eBay inc. (StubHub)

San Francisco, Califronia
PhD Intern

Worked on Machine Learning, Data Science and Natural Language processing for Big Data Analytics and Search systems. Developed conversion prediction system and text summarization pipelines.

June 2016 - Sept 2016, Jan 2017 - May 2017

Education

University of California, Santa Cruz

Santa Cruz, Califronia
Doctor of Philosophy
Computer Science (Machine Learning, Graphs, and Reputation Systems)

Research Advisor: Prof. Luca de Alfaro

GPA 3.7/4.0

Sept 2014 - Present

Jaypee Institute of Information Technology, Noida

Noida, U.P., India
Bachelor of Technology
Information Technology

July 2008 - May 2012

Skills

  • Data Science
    Python, Tensorflow, Keras, PyTorch, Spark, Hive, Pandas, NLTK
  • Programming
    Python, Javascript, Java, Node.js, C/C++, Android
  • Full Stack
    Django, Web2py, Flask, Node.js, Vue.js, Cordova
  • Miscellaneous
    Raspberry Pi, Photoshop, Illustrator