Resume

General Information

Full Name Rishabh Joshi
Contact rishabhjoshi0407 [at] gmail [dot] com
Languages Hindi (native), English (fluent), Marwari (beginner), Punjabi (beginner), Sanskrit (beginner)

Research Areas

  • My research focuses on developing algorithms for machine learning and applying my methods in order to study how machines can mimic humans in congitive tasks, especially those related to Language.
  • I am also interested in creating AI agents that can understand language and reason, therefore I have also worked on natural language processing with a focus on language generation.
  • Currently I'm focusing my efforts at Google Deepmind in improving the generation capabilities and studying alignment of large language models, including RLHF and preference optimization during post-training.

Education

  • Aug 2021
    Carnegie Mellon University – Master in Language Technologies
    • Co-advised by Prof. Alan W. Black, Prof. Yulia Tsvetkov and Prof. Alexander Rudnicky. MLT is a research program equivalent to the first two years of a PhD in LTI, CMU.
    • GPA: 3.94 / 4.33
    • PhD level Courses: Intro to ML, Algos for NLP, NN for NLP, Ethics and Propaganda in NLP, Deep RL, Multilingula NLP, Dialogue Seminar, Probabilisic Graphical Models, Question Answering
  • 2014 - 2018
    Birla Institute of Technology and Science, Pilani – Bachelor of Engg. (Hons.) in Computer Science
    • Thesis advised by Prof. Partha Talukdar at IISc Bangalore
    • Thesis: Improving Distantly Supervised Neural Relation Extraction using Side Information
    • GPA: 9.28 / 10.00

Work Experience

  • Sep 19 - Aug 21
    Senior Research Engineer at Google DeepMind
    • Advised by Profs. Yulia Tsvetkov, Alan W Black and Alexander Rudnicky
    • Proposed an interpretable approach for knowledge proliferation in academic research articles by identifying key phrases using importance attribution.
    • Performed a linguistic driven analysis on the characteristics of good negotiators and incorporated explicit strategy-sequence structure using Graph Neural Networks to improve non-collaborative dialogue systems.
    • Collaborated with team Tartan to develop a conversational system in Amazon Alexa Challenge 2019; developed mini-bots and analyzed conversational story structure, reached semi-finals.
    • Modeled the structure of dialogue by analyzing the flow of conversational topics and detecting non-coherence. Submitted proposal for Alexa Challenge 2020.
    • Studied knowledge proliferation and keyphrase extraction using interpretable neural models.
  • Jul 18 - Aug 19
    Research Software Engineer at Samsung Research India
    • Improved open domain dialogue systems using side information and contextual knowledge.
    • Constructed a low resource intent classification and speaker recognition solution using GMMs.
  • Jan - Jul 18
    Undergraduate Thesis (Advisor : Prof. Partha Talukdar)
    • Constructed a unique India-Centric Knowledge Graph based on the Never-Ending Language Learning Paradigm.
    • Improved Distantly-Supervised Relation Extraction using Side Information achieving SOTA results.
  • Summer 2017
    Summer Intern at Samsung Research India
    • Developed tools for packet generation and distributed analysis for the data link layer of 5G protocol.
  • Summer 2016
    Research Intern at IIRS, ISRO
    • Developed core API and execution engine of the DataCube for the effective storage, retrieval and analysis of large earth observation datasets using Python and ideas from distributed and parallel computing.

Teaching Experience

  • Spring & Fall 20
    Teaching Assistant for Applied Machine Learning
    • Undergraduate/Graduate-level introduction to machine learning course in an application focused way, taught by Prof. Carolyn Rose at Carnegie Mellon University.
    • I mentored groups of students working on class projects and graded homeworks.
  • Spring 2017
    Teaching Assistant for Data Structures and Algorithms
    • Undergraduate level introduction course to Data Structures and Algorithms taught by Prof. Sundar S Balasubramaniam.
    • I helmed two lab sections and was the jury fo rthe online judge with the responsibility of assisting 200+ students.

Computer skills

  • ○ Programming languages: C, C++, Python.
  • ○ Data Structures and Algorithms: Familiarity with concepts used in algorithmic competitions and machine learning research.
  • ○ Frameworks: Pytorch, Tensorflow, NumPy, SciPy, Pandas, JAX.
  • ○ Database Systems: MySQL, MongoDB.

Other Interests

  • Sports: Badminton, Squash, Volleyball, Tennis, Hiking
  • Hobbies: Traveling, Music, Movies