About Me
Hi! I’m Arian, and I’m obsessed with turning complex data into awesome machine learning solutions. With four years of experience in finance and advertising under my belt, I’ve got a knack for building predictive models, wrangling data pipelines, and playing with the latest LLM magic. From my earlier adventures in IoT and deep reinforcement learning research to real-world projects in risk management, productivity tools, and ad targeting, I love the challenge of bringing ML ideas to life. Want to see what I’ve been up to? Check out my portfolio, Medium articles, or LinkedIn profile.
If you’re building cool stuff with data, let’s connect - you can find me on LinkedIn or shoot me an email at a.nasehzade@gmail.com!
Cheers!
Projects
A Deep Reinforcement Learning-Based Caching Strategy For IoT Networks With Transient Data
#TensorFlow #Keras #StableBaseline #DRL #openai #gym #A2C #PPO #numpy #pandas #matplotlib
This project, which led to a couple of publications, was my master’s thesis project. I have deployed a couple of DRL algorithms such as A2C and PPO to address the caching problem in IoT networks where files have a limited lifetime. We improved the cache hit rate and energy consumption of the network significantly.
Experiences
Research and Teaching Assitant
York University
Sep. 2019 - Present
Aside from the thesis project (mentioned above), I was the teaching assistant for multiple courses. I helped students to develop and debug Android applications using Java and XML for one semester. I also taught MATLAB programming and helped students with code debugging for another class.
Researcher
York University
Jan. 2019 - Sep. 2019
Before starting the M.Sc program, I had a research contract with my supervisor, Dr. Ping Wang. Since she hadn’t had any grad student at York University until then, we needed to develop a research road map for the team she was recruiting at the time. We find credible resources to study DRL. After doing an extensive literature review, we found a couple of interesting problems that we thought DRL could effectively address, such as caching in computer networks and routing in unmanned aerial vehicles (UAV) networks. We also briefly studied federated learning and its use cases, which later became the research area for our other group members.
Education
York University
M.Sc Computer Science
2019 - 2021
During the M.Sc program, I focused my studies on machine learning and data science. I took courses on machine learning theory, data mining, advance deep neural network, data visualization, and more. My thesis is about the application of Deep Reinforcement Learning in IoT networks.
Amirkabir University of Technology
M.Sc Digital Electronics
2016 - 2018
This program helped me to distance my studies from electrical engineering and pivot towards computer science. I took courses in bio-inspired artificial intelligence and statistical learning, which got me hooked on machine learning readings for the years to come.
University of Guilan
B.Sc Electrical Engineering - Electronics
2011 - 2016
I received my bachelor’s degree from the University of Guilan, in the beautiful city of Rasht, Iran. I did some TAship for electronics courses. For my final project, I designed an LED lamp driver and developed an android application to control the lamp’s brightness.
A Little More About Me
Alongside my interests in data science and machine learning, I often find myself busy with one of the followings in my free time:
- Doing some small investments and following business news (I love this one!)
- Gaming
- Binge-watching Netflix
- Binge-listening a podcast