Thameem Abbas I. Email & Phone Number

Raleigh, Nc, Us

Performance and Scale - ML

Boston, Massachusetts, Us

CS 5520 - Mobile Application Development - Under Professor. Dr. Daniel Feinberg

Boston, Massachusetts, Us

CS 3700 - Under Professor Dr. Alden Jackson

Boston, Massachusetts, Us

CS 6650 - Building Scalable Distributed Systems under Professor - Dr. Saripalli Prasad

Boston, Massachusetts, Us

Fundamentals of Cloud Computing

Boston, Massachusetts, Us

Networks and Distributed Systems (3700)

San Jose, Ca, Us

◦ Conducted research on innovative architectures for deep recurrent multi-modal neural networks using mixed precision training to fit saidnetworks on memory constrained GPUs and utilize Tensor Cores◦ Engineered a highly scalable, multi-cloud capable and efficient SaaS platform delivering exceptional throughput per clientand achieved sub-200 ms end-to-end latency, empowering businesses to leverage near real-time applications and providing a competitiveedge. Employed a variety of cloud-native ideas including containerization, microservices, load-balancing, WAFs, and, middlewares◦ Implemented and automated deployment management policies reducing deployment transition times◦ Championed a streaming-model back-end architecture, achieving drastic throughput increases.◦ Enhanced network security practices, automated SAST & DAST security testing, and trained development and deployment teams◦ Built least permissive privacy-first protocols ensuring only secured access to Personal Identifying Information(PII)◦ Built logging and validation systems to improve visibility of metrics, ensure compliance with the data protection laws, and speed up

San Jose, Ca, Us

◦ Optimized computer vision models to match or surpass SOTA benchmarks while achieving many fold reduction in memory and computerequirements before quantization by implementing a range of compression techniques including pruning, and knowledge distillation◦ Designed and trained model architectures optimized for various target hardware platforms(hardware-model co-design), ranging fromGPUs to DSPs improving performance over base architectures◦ Developed custom parsers and converters between multiple ML training and inference frameworks including Darknet, Tensorflow,PyTorch, ONNX, nGraph(Intel), and TensorRT enabling the use of novel model architectures including Enet.◦ Leveraged parallel multi-stream inference to boost performance on TensorRT and optimized CPU performance by leveraging asynchronous scheduling◦ Built the SDK to operate across Windows, and Linux, platforms running inference on CPU(x86, AVX), GPU(CUDA), and dedicated edgeinference accelerators - ARM NN and Qualcomm SNPE. Recurrent blocks of code were developed in C++ with Python wrappers◦ Established automated build and test pipelines on Bitbucket to ensure stable development and improve developer throughput

Hosur, Tamilnadu, In

My learning responsibilities included learning safety mechanisms followed by the industry, and developing a solution using Augmented reality and Deep Learning to allow for real-time monitoring of the status of machines and internal components for preventive maintenance. I was also deeply involved in creating another proof of concept using Deep Learning to allow for the automated testing of gas-filled parts, thereby reducing possible human error.Tech Stack:Tensorflow, OpenCV, Python, Android Application, Industrial IOT, MQTT, LabelImgThe opportunity to perform the complete machine learning dataset and model development and the subsequent fine-tuning gave me the opportunity to understand the nuanced effects each process in the chain can have on the performance of the final model.

Bangalore, Karnataka, In

I was involved in : - Multiple domains and roles including but not limited to porting code from MATLAB to c++, accelerating said algorithms using OpenCV and leveraging parallelism, identifying functional criteria and constraints for said algorithms, and identification of suitable hardware for the application of the same. - Developing a proof of concept using Machine Learning and Deep Learning, in specific, to solve the problem of identifying human error and verifying compliance of set criteria.Tech Stack:a. Tensorflowb. Pythonc. OpenCVd. LabelImg

Master Of Science - Ms, Computer Science

Bachelor Of Engineering - Be, Electrical And Electronics Engineering (Sw)

High School Diploma