Meet your next
Research collaborator.
I’m a problem solver
with
technical
skills
to
boot.
I love making
(and breaking) things
(and breaking) things
I’ve worked in 2D, 3D…and 4D?
and managed some
free time.
free time.
I’m open to interdisciplinary explorations
and I’d like to
collaborate with you.
Selected Experience
-
School of Data Science, University of Virginia
August 2025 to present
- Transferred to UVA with Prof. Yong-Yeol Ahn to continue PhD research in network science and machine learning.
- Continuing work on geometric deep learning approaches to community detection and graph representation learning.
- Exploring hyperbolic embeddings and their applications to sciesntific knowledge networks.
-
Capital One, Data Science Intern
June 2025 to August 2025
- Built the bank's first enterprise approach for data-shift risk in loss-forecasting, selecting Bayesian Online Changepoint Detection (BOCPD) and implementing a production-ready Python workflow.
- Validated the approach on synthetic stress suites and historical portfolios, surfacing macro-regime shifts and portfolio-mix changes earlier and with fewer false alarms than existing drift tests.
- Drove adoption by aligning with Model Risk and business stakeholders, shipping runbook and training materials, and demoing to senior executives for rollout across 150+ developers enterprise-wide.
-
Department of Physics, University of Barcelona
December 2024 to June 2025
- Collaborated with Profs. Marián Boguñá and Mariangeles Serrano on applying hyperbolic graph embedding techniques (Mercator) to large-scale journal citation networks.
- Extracted and processed massive datasets from OpenAlex to model the flow and gatekeeping of ideas between journals in the scientific publication ecosystem.
- Analyzed author trajectories through hyperbolic embedding space to uncover patterns of interdisciplinary movement, community boundaries, and structural barriers to idea diffusion.
-
Centre for Complex Networks and Systems Research (CNetS)
August 2022 to August 2025
- Developed a novel clustering algorithm with Prof. Yong-Yeol Ahn and Prof. Sadamori Kojaku that outperforms K-Means without needing prior information of the number of clusters.
- As part of the Science Genome project, quantified the extent of reliance of firms on basic sciences in their R&D efforts using deep learning methods with Prof. Stasa Milojevic.
- Mined and compiled semi-structured big data from Microsoft Academic Graph and Web of Science for analyzing patent-citation patterns.
-
Marc Bloch Center, CNRS Berlin
July 2021 to May 2022
- Worked with Prof. Camille Roth and Dr. Telmo Menezes to improve symbolic regression algorithms by developing novel evolutionary programming techniques.
- Optimized the algorithm to describe and predict the evolution of socio-semantic networks 120% faster.
- Converted the social network analysis into an open-source library for broader research use.
-
IISER Pune Research Groups
May 2019 to July 2021
- Developed a novel analytical framework with Prof. M.S. Santhanam, harnessing biased random walkers to study extreme events on the edges of complex networks.
- Worked on social network analysis of Gossip & Credibility networks to understand misinformation spreading, proposing a novel social influence model involving source credibility.
- Modeled human grid cells as a Continuous Attractor Neural Network with Prof. Collins Assisi, quantifying the role of Spike-Timing-Dependent Plasticity in spatial mapping.
Schools
University of Virginia
PhD in Data Science, GPA: 3.86/4.0
August 2025 - present
Transferred with Prof. Yong-Yeol Ahn to continue research in network science and machine learning at the School of Data Science.
Relevant Courses: Deep Learning, Natural Language Processing, Advanced Graph Neural Networks, Artificial Intelligence
Indiana University Bloomington
PhD Student in Complex Networks and Systems
August 2022 - August 2025
Research Assistant at Science Genome Project and CNetS. Transferred to University of Virginia.
Relevant Courses: Network Science, Complex Systems, Elements of Artificial Intelligence, Applied Algorithms
Indian Institute of Science Education and Research Pune
Master of Data Science, GPA: 9.1/10
May 2021 - May 2022
Best Interdisciplinary Thesis Awardee. Thesis: Symbolic Regression of Dynamic Socio Semantic Networks with Prof. Camille Roth and Dr. Telmo Menezes at Berlin's Marc Bloch Centre.
Bachelor of Physics, GPA: 8.8/10
August 2017 - May 2021
Relevant Coursework: Nonlinear Dynamics, Probability and Statistics, Computational Physics, Data Science, Graph Theory, Algorithms, Economics & Public Policy
Recent work and experiments
Alt-means
2023A clustering algorithm that goes toe-to-toe with K-Means, sans the K. The conception of the algorithm and prototype code is the brainchild of Prod. Sadamori Kojaku. We are currently working with Prof. Yong-Yeol Ahn to publish the results. You can use it for your needs by installing the python library from Github
Synth
Synth
2022Synthetic is a machine learning tool that can be used to discover mechanisms for complex networks. This tool automates scientific method - it creates hypothesis, tests them against data and refines them. It's previous version was developed by Dr. Telmo Menezes and Prof. Camille Roth before I started using genetic programming techniques with them on this. Check it out on Github
Buttcoin
Buttcoin
2021This was a crypto-starter pack to educate people about the basic components that make up a cryptocurrency. It came out of our love/hate relationship with Bitcoin and Dogecoin and you can check it out on Github
Prevention > Cure
2019Designed a Django application to preemptively schedule maintenance for systems and subsystems for Goa Shipyard Ltd.
Programmed an LSTM network to predict the probability of failure, by monitoring sensor values trends like current,
temperature and pressure with 78% accuracy on historical failures.
Drafted algorithm to reduce downtime by 68% by load-balancing assembly lines and maintenance scheduling.