New York, NY | 1 (800) 800 8009 | bla@blab.com | nikhilravi.com | linkedin.com/in/nikhil--ravi | github.com/nikhil-ravi
Doctoral student with research experience in the design and implementation of robust and privacy-preserving optimization algorithms for complex networked dynamic systems, with a focus on fault-tolerance and differential privacy for energy systems. Advanced understanding of linear algebra, statistics, stochastic processes, optimization, and probability theory. Skilled in time-series predictive modeling, causal inference, and hypothetical testing. I am looking for quantitative research/data ML science roles in Spring 2025.
| Skills | Projects |
|---|---|
| Python (NumPy, pandas, scikit‑learn, statsmodels, plot.ly, TensorFlow, PyTorch, Langchain, HuggingFace), Ray, JavaScript, React, Next.js, Matlab, GCP, Git, Postgres, SQL, MongoDb, Neo4J. | - Chess-insights drawn from chess games of a player on Chess.com \ |
- Roosevelt Island Senior Adult Center Events App \
- LocalGPT: Private and context-aware Retrieval Augmented Generation (RAG)\
- FicRec: Personalized fanfiction recommendations using RAG\
- LeetScrape: Elevate Your Coding Game with Offline LeetCode Mastery \
- More on my projects webpage |
- Ph.D. in Electrical and Computer Engineering, Cornell University, New York, NY, August 2021 - May 2024 (expected)
- Minor in Applied Math and Computer Science
- Research: Robust Privacy-preserving algorithms for energy systems
- GPA: 3.97/4.0
- Relevant Coursework: Statistical ML, Applied Probability and Stochastic, Reinforcement Learning and Optimal Control, Distributed Optimization, Bayesian Methods in ML, Causal Learning, and Inference.
- M.S. in Electrical and Computer Engineering, Cornell University, New York, NY, August 2021 - May 2023
- M.S. in Electrical Engineering, Arizona State University - Tempe, AZ, August 2017 - August 2021
- Transferred to Cornell University with a 4.0/4.0 GPA and a Master's degree.
- Thesis: Decentralized Optimization in Adversarial Environments
- Received the 2021 Ira A. Fulton Schools of Engineering Graduate Fellowship.
- B.E. in Electrical and Electronics Engineering, PES Institute of Technology, Bangalore, India, August 2013 - May 2017
- Graduated with Distinction, First Class with a 9.9/10 GPA.
- Awarded the 2015 Indian Academy of Sciences Summer Research Fellowship.
- Data Science Intern, Kevala, Inc., San Francisco, CA (Remote), May 2022 - August 2022
- Developed a deep reinforcement learning‑based tool on GCP Vertex AI to maximize batteries and plug‑in electric vehicles’ electricity price arbitrage value via charge schedule optimization, based on electricity price, solar irradiation, and load forecasts.
- Developed a methodology to estimate carbon social prices for feeder‑level electricity generation.
- Created data visualization dashboards using Streamlit, translating complex data sets into comprehensive visual representations.
- Researched and published an internal blog on the use of racial features in ML.
- Graduate Research Assistant, Cornell University, New York, NY, August 2021 - Present
- Played a central role in the execution of Provable Anonymization of Grid Data for Cyberattack Detection, a research initiative funded by the Department of Energy, as the primary student researcher.
- Oversaw data collection, analysis, and reporting, generating critical findings that significantly advanced the project's objectives.
- Led innovative research initiatives within the project, including the development of
- Differential private (DP) clustering algorithm for consumer classification and typical load shape generation,
- DP cyber-physical attack detection methodology for SCADA systems, and
- DP approach for inferring solar PV metadata and forecasting from large-scale consumer energy usage datasets.
- Graduate Teaching Assistant, Cornell University, New York, NY, August 2021 - Present
- ECE 5260: Graph-Based Data Science for Networked Systems, Fall 2021 & Spring 2024
- ORIE 5380: Optimization Methods, Fall 2023
- CS 5356: Building Startup Systems, Spring 2023
- Research Intern, Lawrence Berkeley National Laboratory, Berkeley, CA (Remote), May 2021 – August 2021
- Developed a pipeline to ingest and clean large time‑series AMI data of an electric ISO’s consumers onto a PostgreSQL database.
- Designed algorithms to publish differentially private summary statistics about consumer energy data.
- Graduate Research Assistant, Arizona State University, Tempe, AZ, August 2017 - August 2021
- Designed the Electron Volt Exchange, a secure Hyperledger Fabric‑based distributed ledger for Transactive Energy.
- Developed gradient‑based edge‑cutting mechanisms to build Byzantine fault‑tolerant decentralized optimization algorithms.
- Designed an algorithm to infer socioeconomic preference from crowd movement dynamics data.
- Managed the SINE Lab’s compute resource cluster including VM management, networking, and administration.
- "Data Privacy for the Grid: Toward a Data Privacy Standard for Inverter-Based and Distributed Energy Resources", IEEE Power and Energy Magazine (2023).
- "Differential Privacy for Class-based Data: A Practical Gaussian Mechanism," IEEE Transactions on Information Forensics and Security (2023).
- "Differentially Private K‑means Clustering Applied to Meter Data Analysis and Synthesis." IEEE Transactions on Smart Grid (2022).
- "A secure distributed ledger for transactive energy: The Electron Volt Exchange (EVE) blockchain." Applied Energy (2021).
- "Detection and Isolation of Adversaries in Decentralized Optimization for Non-Strongly Convex Objectives." IFAC Workshop on Distributed Estimation and Control in Networked Systems (2019).
- "A Case of Distributed Optimization in Adversarial Environment." IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2019).