Ramneet Singh

Ramneet Singh

Dual Degree (B.Tech- M.Tech) Student

CSE@IIT Delhi

Hello there! I am Ramneet, a student in the CSE Department at IIT Delhi, with a strong focus on Programming Languages and Machine Learning. My (desired) research interests include formal methods and neurosymbolic program synthesis. I am currently a Research Assistant in the School of Computer Science at Georgia Institute of Techology, working with Prof. Suguman Bansal on compositional algorithms for computing max-reachability policies in MDPs, which is a foundational building block in all probabilistic model checking algorithms.

Previously, I have worked as a Platform Engineer at Chorus One on the Infrastructure Team, where I built tooling for secure key management and encryption of their servers. I have completed internships at Adobe Research as a Research Intern and DataChannel Technologies as a Data Analyst Intern. I have worked with Prof. Subodh Sharma in a project on the formal verification of concurrent programs, and later on a COVID Vaccine Alerts telegram bot which reached people from 400+ districts. You can read more about me here.

Download my resumé.

Interests
  • Programming Languages
  • Artificial Intelligence
  • Program Synthesis
  • Graph Neural Networks
Education
  • Dual Degree (B.Tech-M.Tech) in Computer Science & Engineering, 2019-2024 (exp.), CGPA: 9.507

    Indian Institute of Technology Delhi, India

  • Higher Secondary Education, 2019

    Modern Vidya Niketan Sec.17, Faridabad, India

Recent News

All news »

[01/01/2024] : Excited to be a Teaching Assistant for two courses (!!) at IIT Delhi this semester – COL726 : Numerical Analysis and Scientific Computing and COL728 : Compiler Design. I learned a ton from both these courses when I took them, and I hope to learn another ton this time.

[27/12/2023] : Arrived in Atlanta to work as a Research Assistant at Georgia Tech SCS with Suguman Bansal. I have been working on my M. Tech. Project with Suguman, and will continue that work for the next four months. We will (hopefully) make probabilistic model checking faster!

[24/07/2023] : I will be a Teaching Assistant for the course COL703 : Logic in Computer Science at IIT Delhi. The course covers many foundational concepts in logic, which are always nice to revisit.

Experience

(looking for more)

 
 
 
 
 
Research Assistant (M. Tech. Project with Prof. Suguman Bansal)
Jan 2024 – Present Atlanta, USA

Max-Reachability Policies in MDPs

  • Designing a compositional algorithm to compute maximum reachability policies in MDPs, which is a foundational building block in all probabilistic model checking algorithms.
 
 
 
 
 
Platform Engineer (Part-Time)
Aug 2023 – Nov 2023 Remote

Infrastructure Team

  • Built tooling for secure key management and encryption of servers.
  • Maintained,scaled & monitored existing infrastructure, including bare metal servers,cloudmachines, & a Kubernetes cluster, to allow the organization to provide secure & reliable industry‐leading Proof‐of‐Stake validation services.
 
 
 
 
 
Research Intern
Jun 2022 – Aug 2022 Bangalore, India

Marketing Segment Flow Prediction

  • Developed a novel temporal‐graph‐based model for marketing segments.
  • Applied neural embedding techniques for temporal graphs to predict node features and edge weights, used for forecasting churn and flow of customers between segments.
  • Designed network centrality & flow‐based measures to identify high‐activity segments, providing insights about market behaviour to marketers.
 
 
 
 
 
Data Analyst Intern
Jun 2021 – Aug 2021 Gurugram, India

Data Driven Marketing Spend Optimization

  • Developed a system to give optimal spend recommendations across media channels & adsets using historical marketing data, allowing marketing teams to focus on creativity and design.
  • Implemented a revenue forecasting model to predict the revenue-budget relationship for each channel and adset, taking into account adstock transformation as well as the diminshing nature of returns. Dealt effectively with sparsity of data at the adset level.
  • Implemented a cross-channel optimiser which used revenue forecasting models at both hierarchical levels to provide optimal spend allocations. Incorporated constraints like minimum/maximum channel spend keeping in mind practical marketing strategies.

Accomplish­ments

IIT Delhi Semester Merit Award
Awarded for exceptional academic performance in Semester II, 2019-20
See certificate
Univ.AI 100 Scholarship
Received a full scholarship to take the Basics of AI & ML course, taught by Pavlos Protopapas from Harvard.
See certificate
Third Place, HCL Hack IITK
Among 12,500 teams - students, professionals and startups from 12 countries. Built and tested machine learning based solutions to real-world cybersecurity problems.
See certificate
All India Rank 146
Among 170,000 candidates who had qualified for this examination (from 1.1 Million candidates).

Get In Touch!

Feel free to contact me :)