Summary
I am an experienced data and ML engineer with a strong enterprise-level
and academic background. My programming skills include
Python, SQL, PSQL (Postgres SQL), R, C++, etc.
I also have a solid statistics and research background with five
publications with 24 citations to date.
During my strudies I have also have received several awards and scholarships.
Experience
- Designed an ETL pipeline including a Command Line Interface (CLI), data preprocessing, alpha lag decay process,
and exporting the results predicting future sales attribution.
- Automated the data workflows and batch processes and minimized human touch and any need for hard coding.
- Imported and exported data from/to four different sources: local, database, AWS S3 bucket, API (JSON).
- Launched and optimized an automated preprocess pipeline including data cleansing and reformatting clients' data. Capable of
handling 13 date formats. Enabled an automated system capable of handling new formats without adding extra code.
- Proposed a transfer learning (TL) method based on feature extraction
to predict jamming patterns in a communication network. Reduced the time complexity of
the primary model by 30 times.
- Realized a comprehensive XAI method comprising pattern recognition and
rule learning for network security. Improved the transparency of the model
compared to the benchmark explainable models by 17%, whilst having a 32\% less error rate.
- Leveraged an online actor-critic algorithm for access problems
in heterogeneous networks. Achieved a 95% throughput in the network
marked as the highest possible performance.
- Optimized the resource allocation system in distributed computer networks with
prioritized packets using ML/AI, which increased the throughput of the
wireless system by approximately 15%.
Education
- Finished in 5 semesters (1.6 years)
- Supervisor: Ping Wang.
- Number of Publications: 4.
- GPA: A+
- Project Supervisor: Vahid Pourahmadi.
- Publications: 1 journals, 1 conference paper, 1 thesis.
- GPA: 8.4 / 10
Hard Skills
Python C/C++ SQL Java R HTML
CSS JavaScript PHP C# MATLAB
Pandas Spark Apache Kafka Postgres SQL (PSQL) Regex Psycopg2
Boto3 AWS Wrangler Snowflake Shutil
LangChain LLAMA Index HuggingFace FAISS Chroma
Sci-kit Learn PyTorch Tensorflow Keras
BeautifulSoup4 OpenCV
Deep Reinforcement Learning Supervised Learning
Unsupervised Learning Statistical Learning Rule Learning
Random Forests Bootstrap Decision Trees K-means Clustering
Flask Gunicorn Click Typer simple-term-menu Click_Prompt argparse Sys
Matplotlib Latex Markdown Jupyter Notebook
Linux (Ubuntu, Kali, openSUSE) MacOS Microsoft Windows
Streamlit Kivy Qt Design Postman
Publications
- [J1] In progress (Accepted): S. B. Janiar, P. Wang, "Intelligent Anti-jamming based on Deep Reinforcement Learning and Transfer Learning," IEEE
Transactions on Vehicular Technology, 2023.
- [C1] In progress (Accepted): S. B. Janiar, P. Wang, "A transfer learning approach based on integrated feature extractor for anti-jamming in wireless
networks," IEEE MetaComm, 2023.
- [J2] In progress (Accepted): S. B. Janiar, Xian Lu, P. Wang, "Explainable Reinforcement Learning for Wireless Security at the Physical Layer: A Survey,"
IEEE Transactions on Wireless Communications, 2022.
- [J3] Barqi Janiar S, Pourahmadi V. Deep-reinforcement learning for fair distributed dynamic spectrum access in priority
buffered heterogeneous wireless networks. IET Commun. 2021;19. https://doi.org/10.1049/cmu2.12098
- [C2] S. B. Janiar and V. Pourahmadi, "Deep-Reinforcement Learning for Fair Distributed Dynamic Spectrum Access in Wireless Networks,"
2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC), 2021, pp. 1-4, doi:
10.1109/CCNC49032.2021.9369536.
- [Essay1] S. B. Janiar, A. Eckford, "The Theory and Applications of Coded Modulation in Digital Communications: A Survey", York University, Dec. 2021.
Awards and Achievements
- 2023, York University, Nominated for the university's best thesis of the year
- 2016, International Collegiate Programming Contest, ranked 5th.
- 2023, $8000 Scholarship, Research in Deep Reinforcement Learning Based Electric Vehicles Charging Management
in Smart Cities domain, York University.
- 2022, $4370 Fellowship Graduate Assistant, York University.
- 2021, $62,500 Scholarship, Master of Applied Science full-fund scholarship, York University.
- 517th / 162,879, The Coordinated Nationwide Test for electrical and computer engineering schools of Iran.
- 7th / 182, Amirkabir University electrical engineering bachelor's degree.
Selected Courses
- Deep Reinforcement Learning, S. Levine, UC Berkeley, 2019
- Machine Learning Theory, R. Urner, York University, 2021, Grade: A
- Information Theory and Channel Coding, A. Eckford, York University, 2021, Grade: A+
- Mobile Communications, UT Enguyan, York University, 2022, Grade: A
Languages
- English, fluent (without accent)
- Persian (Farsi), mother tongue
- Turkish, mother tongue
- French, Beginner
- Russian, Beginner
Interests
- I'm an ambidextrous! ✍
- Teaching: Currently I am teaching Python and C++ as a private tutor.
- FOREX: I have been actively trading on FOREX investment market 💲 since 2017 (6 years). I have taken several courses
to master technical and fundamental analysis 📉 to be able to predic the market price and make profit out of it.
My programming skills also help me write customized indicators and strategies on Meta Trader platform to
give me Buy / Sell signals.
- Reading: currently I am reading "Verity" by Colleen Hoover and "Masters and
Margarita" by Mikhail Bulgakov. I also enjoy comic books. The most recent
one I finished reading was "The Watchmen" (Yes, I have not watched the Marvel movie yet! 😄).
- Guitar 🎸
- Sports: Boxing 🥊 Biking 🚴 Working Out 🏋 Hiking 🏃.
- I enjoy learning new languages and currently I am trying to learn French as an hobbey.
- Video Games 🎮: I enjoy puzzle and strategic games. The most recent game I have been enjoying a lot and recommend you
trying is "Total War: Napoleon".