Physics and Astronomy

I am very passionate about teaching science and data science at all levels (graduate, undergraduate, K-12).

In Spring 2024, I will teach the PH451/PH551 Machine Learning course that I have developed at UA.

In Fall 2023, I have taught the PH561 Nuclear and Particle Physics course.

In Summer 2023, I have organized the first University of Alabama K-12 Teacher Coding Workshop. Given the success of the first workshop, 2024 will feature another more expanded workshop on this topic.

In Spring 2022, I simultaneously taught my PH451/PH551 Machine Learning course for undergraduate and graduate students at the University of Alabama and as a Fermilab LHC Physics Center course for ~125 remote participating high-energy physics students from US and International Institutions.

In Spring 2022, my Machine Learning course became a UA catalog course PH451/PH551 Machine Learning, with students from many UA departments and colleges enrolling in it.

In Spring 2021, I developed and taught a new PH482/PH582 Machine Learning course for undergraduate and graduate students at the University of Alabama.

The course is a mixture of foundational and applied ML and includes various elements of experiential learning. As part of the course, I incorporated mini ML-hackathons that were highlighted in a  Physics Today article on hackathons in physics.


In Fall 2020,  I taught General Physics 101 course at the University of Alabama.

As part of the course, I developed new learner-centered laboratory modules and introduced various active learning techniques for the virtual classroom environment.

In Spring 2020,  I taught the General Physics 101 course at the University of Alabama in the Studio format.


As part of the course I developed novel learner-centered laboratory modules and extended the use of active learning techniques in a studio-format classroom.

In the past I have taught the following courses:


This course was the basic introduction to astronomy with laboratories inside and outside (with the use of telescopes). I have helped update the laboratory manual and introduced two new labs to the existing course.

This was an introduction to methods of experimental physics course, covering basics of experimentation and data analysis, error analysis and presentation of results.


Data Science

In addition to my UA Machine Learning course, I frequently teach mini lecture-courses on machine learning, covering the following subjects: fundamentals of machine-learning and classification theory, basic and advanced machine-learning methods, deep learning, feature extraction, unsupervised learning, anomaly detection, generative modeling, physics-inspired machine learning and quantum machine learning.

In the Spring semesters (2021, 2022, 2023, 2024), I have taught my Machine Learning course at the University of Alabama



In Summer 2024, I will teach machine learning lectures at the 11th International Deep Learning School (DeepLearn2024) in Porto, Portugal. I will also organize a special hackathon for the school participants.




In Summer 2023, I have taught quantum machine learning lectures at the Korea Institute of Advanced Study (KIAS) AI in High-Energy Physics Summer School


In Spring 2023, I have taught machine learning lectures at the 9th International Deep Learning School (DeepLearn2023) in Bari, Italy.



In January 2021, I planned to give invited lectures at the 4th International Deep Learning School (DeepLearn2021) in Milan, Italy which got postponed to Summer 2021 and moved to Las Palmas de Gran Canaria.


In 2019, I presented lectures at the 3rd International Summer School of Deep Learning (DeepLearn2019) in Warsaw, Poland.



I also taught a special Machine Learning Workshop at University of Puerto Rico and presented lectures and tutorials at the INFN School of Statistics (INFN2019) in Paestum, Italy.









  • Mini-course on data science to Sanofi Pasteur at in Lyon, France in March 2017
    • I was invited to teach a data science course (on behalf of CERN) to data science and statistics specialists from a global pharmaceutical company Sanofi Pasteur specializing in vaccine production
    • News article about the course


Image: https://indico.cern.ch/event/395374/images/6097-affiche_V6_Data_Science__LHC_2015-2.jpg


K-12 Teachers and Project CODER

As part of project CODER, I have organized four workshops targeting high school teachers in the use of interactive technology to introduce computer science and data analysis into classroom activities.

During the workshops we worked with the dozens of K-12 teachers on integrating programming and data analysis into classroom activities and taught concepts of particle physics to be introduced at an appropriate level to the students.

As part of the project I also organized the Open Data Working Group for the high school teacher program at CERN. This group of teachers also created classroom activities based on Project CODER to be used in their classrooms.

We have received overwhelmingly positive feedback from the K-12 teachers, and the project is currently adopted by one of the major school districts in the Orlando, Florida area.


K-12 Students

As part of project CODER, I have worked with five high school students on learning the basics of programming and how to analyze open particle physics data  from the CMS experiment. The students and K12 teachers benefited from mutual interaction that helped shape and improve the materials that eventually made it into the K-12 classrooms.