Teaching

I have been actively involved in Teaching and Research Supervision activities. The details can be found on this page.

Teaching

Summer 2024: Data Intensive Computing (194.048)

Lecturer, Vienna University of Technology (TU Wien), Austria

  • The course aims to teach students how to: (i) assess and reduce the energy and environmental impact of large scale AI models, and (ii) apply and leverage AI techniques to tackle critical climate change problems.
  • I am responsible for developing course materials and delivering the lectures, designing and grading the practical assignments and exams.
Winter 2023: AI/ML in the Era of Climate Change (194.125)

Lecturer, Vienna University of Technology (TU Wien), Austria

  • The course aims to teach students how to: (i) assess and reduce the energy and environmental impact of large scale AI models, and (ii) apply and leverage AI techniques to tackle critical climate change problems.
  • I was responsible for developing course materials and delivering the lectures, designing and grading the practical assignments and exams.
Summer 2023: Data Intensive Computing (194.048)

Lecturer, Vienna University of Technology (TU Wien), Austria

  • The course covers topics on Big Data Processing with frameworks like MapReduce, Hadoop, Spark, and SparkMLLib.
  • Delivered lectures and evaluated the student assignmetns and exams.
  • Designed, and handled the three practical assignments on (i) text retrieval with Hadoop, (ii) text analysis and classification with Spark and SparkMLLib, and (iii) edge offloading with AWS.
Winter 2022: AI/ML in the Era of Climate Change (194.125)

Lecturer, Vienna University of Technology (TU Wien), Austria

  • I and Prof. Ivona Brandic created this new Master’s course at TU Wien.
  • The course aims to teach students how to: (i) assess and reduce the energy and environmental impact of large scale AI models, and (ii) apply and leverage AI techniques to tackle critical climate change problems.
  • Developed course syllabus, materials and delivered the lectures, evaluating the student assignments and exams.
  • Designed, implemented and handled two new practical assignments (i) exploring the tradeoffs between energy and performance with model quantization, a technique to reduce the size and complexity of neural networks, and (ii) applying deep learning models to weather forecasting using the LamaH-CE dataset.
Summer 2021: Energy-efficient Distributed Systems (194.049)

Lecturer, Vienna University of Technology (TU Wien), Austria

  • The course covers the foundations of sustainable computing, energy efficiency in cloud computing and edge computing systems, among others.
  • Delivered lectures, designed and handled the practical assignment on prediction driven workload management in cloud data centres.
2018-2021: Distributed Systems (COMP90015)

Head Tutor and Tutor, The University of Melbourne, Australia

  • Worked as Head tutor and tutor for multiple semesters (S1 2021, S1 2020, S2 2019, S2 2018).
  • As a tutor, I delivered the weekly coceptual and practical tutorials to the students.
  • As a head tutor, I was responsible for creating tutorial materials, and managing the team of six tutors.
  • Assisted lectures in creating new teaching materials and setup evaluation procedures.
2020-2021: Cloud Computing and Security (FIT5225)

Tutor, Monash University, Australia

  • I delivered the weekly conceptual and practical tutorials to the students.
  • I helped in designing new practial assignments.
  • I assisted lecturer in creating new teaching materials, quizzes, and setup evaluation procedures.
2020-2021: Internet Technologies (COMP90007)

Tutor, The University of Melbourne, Australia

  • I delivered the weekly conceptual and practical tutorials to the students.
Other Teaching Activities
  • Guest Lecture on Programming Abstractions in Cloud: From Mesage Passing to Platform as a Service in Internet Technologies course, UniMelb, Australia (2020S2 and 2021S1).

Research Supervision

  • Mr. Paul. J. Maliakel, PhD Thesis, Resource efficient ML Serving at Scale, TU Wien, Austria, 2024 - now.
  • Mr. Tharindu Bandara, PhD Thesis, Carbon-aware Resource Management in Edge-Cloud Systems, UniMelb, Australia (remote supervision along with Prof. Raj Buyya and Dr Maria Read), 2021 - now.
  • Mr. Paul. J. Maliakel, Master Thesis, Achieving Sustainable Federated Edge Analytics by Using Incomplete Data, TU Wien, Austria, 2023.
  • Ms. Viktorija Pruckovskaja, Master Thesis, Performance Analysis of Federated Learning Algorithms for Industrial use cases, TU Wien + AIT, Austria, November 2023.
  • Daniel Hofstätter, Semester Project, Symbolic Representation of Data on Edge, TU Wien, 2023.
  • Ms. Meerzhan Kanatbekova, Master Thesis, Symbolic Data Representation of Multi-Media Data on Edge, TU Wien, May 2022- November 2022.
  • Mr. Mayank Jha, Master Thesis, Statistical Characterization of a Cloud Data Center, TU Wien + University of L’aquila, Italy, Feb-2022 – November 2022.
  • Mr. Jakob Fahringer, Bachelor Thesis, Decentralized Monitoring in Edge, TU Wien, Feb - October 2022.
  • Mr. Shreshth Tuli, Semester project, RL-based Scheduling in Edge-Cloud, UniMelb, Australia, 2020.
  • Mr. Nipum Basumati, Semester project, RL-based Scheduling in Edge-Cloud, UniMelb, Australia, 2020.
  • Mr. Tahseen khan, Semester project, Workload Forecasting in Cloud, UniMelb, Australia, 2021.
  • Ms. Radhika Chhikara, Master Thesis, Parallel Processing of Power-BI Applications using Ankea, UniMelb, Australia, Jan 2019- June 2019.