Nima Sadri

Machine Learning
TensorFlow, PyTorch, Scikit-learn
Training on multiple GPU and TPU
Anserini, Pyserini, Capreolus
Cleverhans, MLJar
AWS Sagemaker

Web Development
ReactJS, React Native, Expo
Node.js, Django, Django Rest Framework
Bootstrap, Material UI
Stripe API, PayPal API
Apache, Nginx, AWS Route 53
Headless Chrome, Puppeteer

Data Analysis
Pandas, NumPy, and Matplotlib,
MapReduce, Spark, Hadoop
Grafana

Architecture
PostgreSQL, AWS RDS and Aurora, S3, CloudFront
AWS Kinesis, EMR
AWS EC2, Elastic Beanstalk, Lambda
CI/CD: AWS Code Build, Code Deploy, Code Pipeline
Docker, Virtual Machines, Virtual Environments

Advanced level Math and Computer Science courses have formed most of my course load
- Machine Learning Theory and Implementation, Artificial Intelligence, Deep Learning
- Algorithms and Data Structures
- Compilers & Assemblers
- Object Oriented Programming
- Proof-Heavy Math Courses: Multi Variable Calculus, Advances Linear Algebra, Combinators
- Linear and Non-Linear Optimization
- Statistics & Probability
Other courses: Sales, Entrepreneurship; Business Negotiations; Leadership; Academic Writing; Business Writing; Game Theory (Economy)

Machine Learning, CS 299, Stanford University (2020)
Natural Language Processing with Deep Learning, CS 224N, Stanford University (2020)
Algorithms: Design and Analysis at Stanford (2018)
Operating System and System Programming, CS 162, Berkeley University (2019)
Neural Networks for Machine Learning at the University of Toronto (2019)
Functional Programming Principles in Scala at École Polytechnique Fédérale de Lausanne (2019)
CS50, fundamentals of computer science at Harvard (2018)
Bitcoin and Blockchain, Princeton University (2018)

Summer 2018 and 2019

Fully responsible for designing, implementing, and testing a scalable, efficient, real-time data analytics platform for the company, capable of analyzing TBs of data per day and reporting the results on the company's analytics dashboard
Used Spark as the data engine, AWS EMR clusters for deploying Spark to production, AWS kinesis for real time streaming of data, PostgreSQL for data storage, s3 for storing backup of the analyzed results, and Grafana as the internal dashboard
This analytics dashboard decreased the server costs by $50k a month, increased the performance, decreased downtimes, and made the analytics engine much more scalable

Fall 2019

Lead a team of 4 to build a fork of Pandas and Numpy libraries, where data structures (e.g. matrices) are stored in SSD, while preserving a RAM-like performance
Worked extensively with Numpy and Panda's python source code, modifying it to use company's patented data structure. Used in-house servers alongside Jenkins for deployment. Low level programming using C and Levyx's patented data structure (Helium).
Wrote a Whitepaper survey to showcase the benefits of using our forked Pandas Pandas version compared to the default fork – this was used to market the product to investment banks and quants.

April 2020 - Present

Avybe allows social media influencers to monetize and fans to get personal interactions with their favourite creator through one-on-one video calls
Built the initial product using ReactJS, React Native (Expo), and Django Rest Framework. Deployed to production using AWS Beanstalk. Used AWS Chime SDK, RDS, s3, and Lambda.
I hired and lead 12 engineers
I started and maintained investor relationships with ~20 VCs and angels

1. Continuous Active Learning Using Pretrained Transformers | August 2022. | Nima Sadri, Gordon V. Cormack.

2. Evaluating Dense Passage Retrieval using Transformers | Nima Sadri | August 2022.

3. MeetSum: Transforming Meeting Transcript Summarization using Transformers! | August 2021. | Nima Sadri, Bohan Zhang, Bihan Liu

Built a simple version of Amazon Go's cashierless store that automatically detects when a customer picks an item from the shelf
Used AWS Rekognition to train a ML model, Firestore as a real-time datastore, React Native for consumerfacing app, ReactJS for store owner dashboard, and Django Rest Framework for web backend

Trained large Deep Learning Natural Language Processing Information Retrival models (e.g. monoBERT) using the Capreolus open source library
Benchmarked and reproduced research results in NLP Information Retrieval using Anserini and Pyserini libraries

Wrote an interpreter for LISP
Implemented a compiler for a simplified C-like language

Implemented a large portion of C++ standard library from scratch
Designed and implemented memory-optimized data structures in C
Implemented a variety of algorithms and data structures with optimized time complexity using python and C

Implemented classical ML algorithms (Linear Regression, Logistic Regression, Ridge Regression, SVMs, Decision Trees) from scratch
Implemented fundamental deep neural networks models (CNN, RNN, VAE, GAN, Transformers) using TensorFlow and PyTorch
Implemented reinforcement algorithms (e.g. ADP), decision trees, Baysian Networks, and HMMs in Python using NumPy

Built a book reading mobile app using django-rest-framework as backend and React Native as front-end; deployed using Beanstalk and Amplify

Euclid Contest: Certificate of Distinction (2018)
Fermat Contest: Certificate of Distinction (2017)
Canadian Senior Math Contest: Certificate of Distinction (2016)
Cayley Contest: Certificate of Distinction (2016)

Thiel Fellowship Candidate (2021)
Sir Isaac Newton Exam: Certificate of Distinction (2017 and 2018, University of Waterloo)

Over $30,000 in scholarships

You can ask me to provide references by emailing me: nimasadri11 [at] gmail [dot] com

I have recieved some kind recomendations on LinkedIn (which I will place here for convinience). To validate their integrity, see the “Recommendation” section of my LinkedIn page

Reza Sadri (PhD, Computer Science, UCLA)
Disclosure: Reza is my uncle (and mentor)
I was hesitent to write a recommendation for a relative, but after a series of outstanding achievements by Nima, I thought to myself that it was just wrong not to recognize him. In a nutshell, Nima is the ulitmate "get it done" person. A few times he has told me that he was to embark on something really big and I have seen him how he gets it done against many odds. I believe this is rooted in a collection of characteristics: very knowledgable and always eager to learn; a great and attentive listener and the ulitmate doer.

Shahin Rahbariasl (Master's, Computer Science, University of Waterloo)
I worked with Nima closely during his co-op at Blockthrough. He's a talented programmer and also a very quick learner who can get the grasp of any technology needed to get the tasks done. He was always open to suggestions and also he actively came up with different solutions for various challenges. Overall, I enjoyed working with him and I think whatever team he joins, he can bring a lot of value.

Siddharth Choudhuri (PhD, Computer Science, UC Irvine)
Nima was our intern at Levyx. In a short span of his internship, Nima was able to ramp up on our Python dictionary wrapper, understand our key-value integration, and run performance reports. Nima is sharp and tries to understand the business side of things too. Nima will make a great hire!

Jim Yu (Senior Software Engineer)
It's a pleasure to work with Nima. He has great initiatives and abilities to tackle complex problems by both following instructions/suggestions and independent thinking. He is also humble, hard-working and a quick learner.

Simon Liu (Software Engineer, Coursera)
Nima has an extraordinary ability to grasp theory and apply it in practice, to complex software systems. He has been a pleasure to work with since he is amicable and strives to ensure flow of communication and understanding among team members. I am confident that Nima will quickly bring value to any project he contributes to.

Richard Luo (Senior Software Engineer)
From the time Nima co-oped at Blockthrough, he was quickly able to show the ability to problem solve both in groups and independently. He always asks questions if something is confusing him and he has shown diligence on the projects he has worked on from start to finish.

Arash Nabili (Master's, Computer Science, UC Irvine)
Nima is smart and very talented. He is a quick learner, and brings new ideas to the table. He is passionate about his work and isn't afraid of tackling new challenges. It was a pleasure working with Nima at Levyx!