Vedant
Srinivas

Wildlife Systems
Computer Vision
Autonomous Systems
Optimization & Modeling
Edge AI

Featured Projects

Computer Vision
2023
RADIS - Rapid Animal Detection and Identification System
Edge AI solution for real-time wildlife detection and driver warning systems
YOLOv5
Edge AI
RF Systems
Python
TensorFlow
Computer Vision
2025
Automated Thermal Wildlife Monitoring for WSDOT
Computer vision model for automated wildlife monitoring using thermal imagery
Thermal Imaging
Computer Vision
Deep Learning
Python
OpenCV
Reinforcement Learning
2025
Dynamic Portfolio Optimization with PPO
Reinforcement learning for daily asset allocation across ETFs with transaction costs.
PPO
RL
Finance
PyTorch
Python
Deep Learning
2025
Surgical Phase Detection
Multi-model approach for real-time surgical phase detection with reduced parameters
Transformers
GRU
3D CNN
PyTorch
Medical AI
Engineering
2023
Biomimicry for Truck Efficiency
Energy efficiency improvement using boxfish-inspired aerodynamic design
Autodesk CFD
Fusion 360
Aerodynamics
Fluid Mechanics
Biomimicry
Wildlife Conservation
2021
Ora - Animal Warning System
Non-habituating audiovisual warning system to mitigate roadkill through vehicle detection
Embedded Systems
3D Modeling
Arduino
Solar Power
Circuit Design
Data Science
2025
NBA Player Stats Predictor
Predictive analysis of player performance in sports betting using Singular Value Decomposition
Mathematics
Python
NBA API
Predictive Modeling
Statistics

Education

Stanford University logo

Stanford University

B.S. in Computer Science, Artificial Intelligence Track• Jun 2027 (expected)

Experience

My research and professional experience across AI systems, computer vision, and environmental monitoring

AI Software Engineer Intern

June 2025 – Sep. 2025

Salesforce AI Research

•Palo Alto, CA

Part of the Atlas AI research team, building agent-graph optimization frameworks.

Technologies
PythonGraph OptimizationMulti-agent SystemsLLMResearch
Key Achievements
  • Built a modular agent-graph optimization framework for automating multi-agent planning workflows
  • Researched symbolic graph optimization methods including evolutionary algorithms and LLM-guided descent
  • Designed and implemented graph rewrite tools for subgraph collapsing, node pruning, and operator selection
  • Analyzed optimization performance across task types via ablation studies and generalization testing

Student Researcher

Jan. 2025 – Present

Stanford Intelligent Systems Laboratory

•Stanford, CA

Worked on ground station placement optimization for satellite communication networks.

Technologies
PyomoMILPPythonAstrodynamicsOptimization
Key Achievements
  • Built MILP-based models in Pyomo to optimize satellite ground station placement across mission objectives
  • Used TLE data with the Brahe astrodynamics library to generate satellite–station visibility constraints
  • Developed Python analysis tools to evaluate data throughput and identify communication coverage gaps

Co-founder and CTO

Oct 2021 – Present

Iyarkai LLC

•Washington State

Founded Iyarkai to develop AI tools for wildlife monitoring and conservation; secured a contract with WSDOT.

Technologies
YOLOv8Computer VisionThermal ImagingPythonAI Systems
Key Achievements
  • Created a morphing pipeline to simulate thermal data from 26K+ labeled COCO-format optical images
  • Built a two-stage YOLOv8 pipeline combining synthetic trained detection and real thermal classification
  • Achieved >97% precision and recall on real-world deployments across I-90 camera traps
  • Deployed system across active WSDOT sites; expansion planned for 12 additional highway crossings
  • Presented methods and system design at ICOET & TWS Western Section Conference 2025

Applied Science Intern

June 2021 – June 2025

UC Davis Road Ecology Center

•Davis, CA

Developed RADIS: a YOLO-based edge-computing system for real-time wildlife detection and classification to detect animals on highways and warn drivers of active animal presence.

Technologies
YOLOEdge ComputingNVIDIA JetsonPythonComputer Vision
Key Achievements
  • Trained models on custom-labeled roadside datasets to detect animals in varying highway environments
  • Deployed RADIS on NVIDIA Jetson devices in Nevada with NDOT; achieved 97% detection accuracy and 99% system uptime
  • Benchmarked inference latency and power consumption to meet real-time roadside alerting requirements
  • Implemented algorithms to track animal speed and direction to identify potential collision threats
  • Presented findings at ICOET 2023

Engineering Intern

Jan. 2022 – Aug. 2022

UC Davis Veterinary School of Medicine

•Davis, CA

Worked on the California Mountain Lion project developing animal deterrent systems for wildlife conservation.

Technologies
Embedded SystemsArduinoCircuit Design3D ModelingWildlife Conservation
Key Achievements
  • Developed animal deterrent systems to protect collection animals from mountain lions without harming any species
  • Designed and implemented embedded systems using Arduino for non-lethal wildlife management
  • Created circuit designs for solar-powered deterrent systems deployed at conservation facilities
  • Utilized 3D modeling for prototyping and optimizing deterrent device housings
  • Collaborated with veterinary researchers to ensure humane and effective wildlife protection methods

Contact

I'm always open to discussing new opportunities, collaborations, or just connecting with fellow researchers and professionals in the field.

vedants8 [at] stanford [dot] edu

Connect With Me