Abstract
Hi, I am Siddhant Saxena (@Sidgraph) currently an undergraduate researcher in the field of Geometric Deep Learning, advised by Dr. Tanmoy Charkaborty and Dr. Subhabrata Dutta from India.
{Category Theory, Differential Geometry, Algebraic Topology, Modern Algebra, Algebraic Combinatorics}
visit Activities for Events and Learnings
I am not applying to Ph.D. admissions this fall [2023], I will be working as an associate researcher [pre-doc] at LCS2 Lab. Currently working on Riemannian Manifold Learning, Geometric DL, and Category Theory related projects.
Recent
New Paper: DPHGNN: A Dual Perspective Hypergraph Neural Networks [KDD'24]
Working on Representation Learning on Higher Geometrical Structures [META AI Research Funded]
Working on Few-Shot Graph Incremental Learning in Graphs [META AI Research Funded]
Learning Category Theory and Functional Analysis on Riemannian Manifolds
Digital ART: "The GNN Conglomerate" - Siddhant Saxena
About me
Hi, I am Siddhant Saxena currently an undergraduate researcher in the field of Computational Intelligence from India.
Note: All the works I have done are from my solo contribution, I thank my advisors for their constant support and collaborations
Current Research Interests:
Geometric Deep Learning
Reinforcement Learning
Molecular Dynamics
Physics-inspired Deep Learning
Category Theory
Differential Algebraic Geometry
Neural Algorithmic Reasoning
Hypergraph Representation
Current Affiliations
[Affiliation] I am joining LCS2 Lab at IIT Delhi from JAN 2023 as PRE-DOC fellow, I will be working with Prof. Tanmoy Chakraborty on exciting Graph Machine Learning related problem statements.
Activities Timeline
I am regularly updating the portfolio and hence I post only recent news here, kindly visit the activities page to know what are the exciting things I do in a month-wise timeline fashion :)
Research Collaborations
Research Publications and Research Projects
[Graph Machine Learning, Hypergraph Neural Networks, Return-to-Origin]
DPHGNN: A Dual Perspective Hypergraph Neural Networks [KDD'24]
Lead contributor: Developed full architecture, performed extensive experiments, developed theoretical frameworks, and wrote the full paper.
In collaboration with Meesho
[Graph Machine Learning, Recommendation Systems, Statistics]
Biases and De-Biasing Strategies for Temporally evolving Graph RecSys
Contribution: developed temporally evolving graph recsys, establish and eliminate exposure bias in the recommendation policy.
Used Pytorch and Pytorch Geometric for Implementation
[Graph Machine Learning, Network Science]
Understanding Evolution through Spatio-Temporal Graph Generation
Contribution: Developed a robust unsupervised graph generation framework to understand the evolution of social networks.
Used Pytorch and Pytorch Geometric for Implementation
[Generative Deep Learning, Network Security, IOT]
ImmuneGAN: A self-adaptive artificial immune system for network intrusion detection.
Selected for Publication: International Conference on Cyber Security, Privacy and Networking (ICSPN2022), Thailand
Contribution: Application of GAN-based architecture in data security and implemented ImmuneGAN in PyTorch for tabular data
[Timeseries forecasting. Deep Learning, Smart City]
GRUBin: Time-series forecasting based on efficient garbage monitoring for smart city ecosystem
Submitted in International Journal of Integrated Waste Management, Science and Technology
Contribution: Implemented Time-series forecasting module to predict timestamps of garbage fill-up in PyTorch
[Deep Learning, IoT, Network Security]
DAIS: Deep Artificial Immune System for Intrusion Detection in IoT Network Ecosystem
Selected for Publication: International Journal of Bio-inspired Computing
Contribution: Development of Neural networks based on the artificial immune system and statistical analysis of network packets, implemented in PyTorch
[5] A Mixed Deep Learning and Statistical Approach for Network Anomaly Detection.
Book Chapter: Routledge Tayler and Francis Group
Contribution: Book chapter writing on Network Anomaly Detection Approaches
[6] A Review on Security and Privacy Requirements and Attacks in VANET
Paper Presentation: International Conference on Cyber Warfare, Security & Space Research (SpacSec-2021)
Contribution: Reviewed the attacks on VANETs and Privacy Requirements
I also lead an undergraduate research group, producing cutting-edge research in various areas of Computational Intelligence. We are a group of researchers looking forward to establishing a distinguished research lab in India, to encourage and support early carrier researchers in terms of mentorship, computing resources, collaboration, and resources. As the undergrad and masters students seek good collaborators and mentors, we have developed research pods to encourage interdisciplinary research in artificial intelligence and we are collaborating with well-established research labs and researchers to provide a cutting-edge research environment to our researchers.
At Genesis AI Labs we work on emerging technologies in the field of artificial intelligence, and participate and organize various events to learn and collaborate with people working in other domains, we also organize learning groups and paper discussion sessions to learn and grow together.
We believe that learning and innovation depend on the orientation of young minds, thus we are open to students from any university across the globe based on the knowledge representation by individual and not on status.