Aditya Sriram

Associate Consultant

Stanford, California, United States1 yr 2 mos experience

Key Highlights

Expert in Quantum Computing and Machine Learning.
Experience in optimizing camera driver performance.
Strong background in Combinatorial Optimization techniques.

Stackforce AI infers this person is a Quantum Computing and Machine Learning specialist with a focus on optimization.

Contact

Skills

Core Skills

C++PythonCombinatorial OptimizationQuantum ComputingMachine Learning

Other Skills

GNU/LinuxLow LatencyREST APIsQAOASimulated AnnealingQUBOQuantum InformationTheoretical Computer ScienceQuantum MechanicsVHDLPyTorchWaveletsVariational Autoencoders (VAEs)Probabilistic Generative ModelsC (Programming Language)

Experience

Stanford university

2 roles

Teaching Assistant

Jan 2026 – Present · 2 mos · Stanford, California, United States · On-site

CS 140E: Embedded Operating Systems

Teaching Assistant

Sep 2025 – Dec 2025 · 3 mos · Stanford, California, United States · On-site

CS 149: Parallel Computing

Apple

Video Engineering Intern

Jun 2025 – Sep 2025 · 3 mos · Cupertino, California, United States · On-site

Camera driver performance optimization.

Indian institute of technology, bombay

2 roles

Department Academic Mentor

May 2023 – May 2024 · 1 yr

Teaching Assistant

Mar 2023 – Apr 2023 · 1 mo

TA for the course, MA 106: Linear Algebra.

Quadeye

System Engineering Intern

May 2023 – Jul 2023 · 2 mos · Gurugram, Haryana, India · On-site

C++GNU/LinuxPythonLow LatencyREST APIs

Qworld

Research Intern

Jul 2022 – Oct 2022 · 3 mos

Studying methods for the selection of relaxation parameters to solve constrained binary optimisation problems. Worked on extending approaches based on the eigenvalue decomposition of QUBO matrices to solve the Travelling Salesman Problem using Simulated Annealing. This involves modifying the non-zero spectra of QUBO Hamiltonians and studying its effect on convergence.

QAOACombinatorial OptimizationSimulated AnnealingQUBOQuantum Computing

Centre for quantum technologies

Visiting Scholar

May 2022 – Jul 2022 · 2 mos · Singapore

Literature survey on recent advancements in quantum learning theory including the method of Classical Shadows. Exploring the advantage of quantum machine learning in terms of query and computational complexity.

Quantum ComputingMachine LearningQuantum InformationTheoretical Computer ScienceQuantum Mechanics