Shashank Singh

Quantitative Technologist at Qube Research and Technologies (QRT)

C++, Python, C#, Bash, PostgreSQL, Microsoft SQL Server, Linux, Networking, Multithreading Oct 2023 - Present London, UK

I work on the Core tech team where I develop and maintain the central trading platform in terms of developing new functionality, maintaining/supporting the existing infrastructure as well as assisting with any business-related queries.

Software Engineer (Robotics) at Niantic, Inc.

C++ (Eigen, Bazel), Python (Numpy), GCP, iOS/Android (Video Encoding), Argo Dec 2021 - Sep 2023 London, UK

I worked in the Augmented Reality - Mapping division in London to tackle challenges with building an up-to-date 3D map of the world which users can place themselves in precisely. My role covered various tasks such doing research and benchmarking in optimizing the map-building process while minimizing the cost and resources required, as well as improving the robustness and stability of the map-to-localization results to give a better end-user experience.

Physically-Based Ray-Tracing Renderer

Vulkan, Rust (GPU Compute, (De)Serialization, Functional Programming, SIMD, Threadpools, Parsers, Simulation), GLSL, OpenEXR Oct 2019 - May 2024

I have been developing a physically-based ray-tracer in Rust from scratch. Initially it was developed for the CPU which was then also expanded for real-time GPU rendering. This includes a custom math and graphics library, an object-loading library as well as domain-specific data-structures and algorithms.

The library contains an efficient flattened implementation of a BVH tree (to be used as an acceleration structure for complex scenes) as well as cameras, multiple BSDFs, lighting types, shapes, textures and samplers. It includes an implementation of a complete Path Tracer as well as simpler Direct Lighting and Ambient Occlusion shaders.

The entire project is structured to be modular and the code is written in a highly functional manner for easier access. Despite this, the renderer is very performant and compiles down to optimized code for all types of geometric computations.

AMZ Driverless Racing

C++ (ROS, Tensorflow, PCL, OpenCV), Python (Tensorflow, OpenCV), C (Atmel AVR32) Oct 2018 - Aug 2019

1st place at both Formula Student Germany and Formula Student East (Hungary)

I was a member of AMZ Driverless, ETH's Formula Student Driverless team, for the 2018-2019 season. Being part of the Perception team, my primary role was to process and analyze all incoming information from the two cameras and two LiDARs on the car. My tasks involved the calibration of the various sensors in both the spatial and temporal domain to allow for fusion of the sensors data for combined processing.

My secondary role was the programming of various AVR32 microcontrollers on the car for interfacing with various components such as the Inertial Navigation System (INS), Low Voltage controller (LV), accumulators (AKKU), dashboard (DB), and the CAN interface tying them all together.

ETH Zürich

(Computer Science MSc.)

Sep 2018 - Aug 2021 Zurich, Switzerland

Georgia Institute of Technology

(Computer Engineering BSc. with a minor in Computer Science)

Graduated with Highest Honors Aug 2014 - Dec 2017 Atlanta, US

International School of Kuala Lumpur

(IB Diploma)

Received Book Award for Mathematics (given to one student in the whole High School as chosen by a committee from the HS Math Department) Aug 2010 - May 2014 Kuala Lumpur, Malaysia