Teaching
- Data Feminism, KTH Royal Institute of Technology, Stockholm, Sweden [24]
- Operating Systems, KTH Royal Institute of Technology, Stockholm, Sweden [22-23]
- Data Intensive Computing, KTH Royal Institute of Technology, Stockholm, Sweden [16] [18-23]
- Scalable Machine Learning and Deep Learning, KTH Royal Institute of Technology, Stockholm, Sweden [18-21]
- Systems for Scalable Machine Learning, KTH Royal Institute of Technology, Stockholm, Sweden [20]
- Scalable Data Science and Distributed Machine Learning, WASP Graduate School AI-track, Stockholm, Sweden [20]
- Advanced Aareas in Distributed Systems, KTH Royal Institute of Technology, Stockholm, Sweden [19]
- Data Intensive Computing, Amirkabir University of Technology, Tehran, Iran [14] [15-16]
- Distributed Systems, Amirkabir University of Technology, Distance course, Tehran, Iran [15]
- Operating Systems, Amirkabir University of Technology, Tehran, Iran [14]
- Data Intensive Computing, Swedish Institute of Computer Science (SICS), Stockholm, Sweden [14]
- Lectures on P2P overlays given as a part of the course Distributed Computing, Peer-to-Peer and Grids, KTH Royal Institute of Technology, Stockholm, Sweden [08-12]
- Lectures on DHT given as a part of the course Network Algorithms, KTH Royal Institute of Technology, Stockholm, Sweden [08-09]
- GNU/Linux System Programming, Iran Network Information Center (NIC), Tehran, Iran [06]
- Operating Systems Lab (GNU/Linux Architecture and Programming), Amirkabir University of Technology, Tehran, Iran [01-06]
- Video Lectures on GNU/Linux, Tehran, Iran [05]
- Operating System, Azad University, Karaj, Iran [04]
- Linux Device Driver, MetNet Co., Tehran, Iran [04]
- Java Programming, MetNet Co., Tehran, Iran [04]
PhD Students
- Sara Karimi, KTH and King, Sweden (cosupervised with Sahar Asadi)
- Amirhossein Layegh, KTH, Sweden (cosupervised with Mihhail Matskin)
- Shirin Tahmasebi, KTH, Sweden (cosupervised with Mihhail Matskin)
- Sina Sheikholeslami, KTH, Sweden (cosupervised with Vladimir Vlassov)
- Fabian Schmidt, KTH, Sweden (cosupervised with Vladimir Vlassov)
Past PhD Students
Past Postdocs
Master Students
- Tangyujun Han, KTH, Sweden, 2024
Evaluation of Retrieval-Augmented Generation in Medical Question Answering Tasks [pdf] - Minchong Li, KTH, Sweden, 2024
Novel Effective Method for Large Language Model Compression [pdf] - Ezio Cristofoli, KTH, Sweden, 2023 (cosupervised with Francisco J. Pena)
Using Satellite Images and Deep Learning to Detect Water Hidden Under the Vegetation [pdf] - Yixiong Wang, KTH and Ericsson, Sweden, 2023 (cosupervised with Azin Ebrahimi)
Unlearn with Your Contribution: A Machine Unlearning Framework in Federated Learning [pdf] - Zekun Wang, KTH and CanaryBit AB, Sweden, 2023 (cosupervised with Roberto Guanciale and Nicolae Paladi)
Confidential Federated Learning with Homomorphic Encryption [pdf] - Disen Ling, KTH and KI, Sweden, 2023 (cosupervised with Magnus Boman)
Analyzing How Blended Emotions are Expressed using Machine Learning Methods [pdf] - Remo Scolati, KTH and RISE, Sweden, 2023 (cosupervised with Ian Marsh and Viktoria Fodor)
Measuring the Responsiveness of WebAssembly in Edge Network Applications [pdf] - Anna Sanchez Espunyes, KTH and Spotify, Sweden, 2022 (cosupervised with Ying Lie)
Machine Learning for Detecting Fraud in an API [pdf] - Antonios Mantzaris, KTH and RISE, Sweden, 2022
Transformer-based Source Code Description Generation [pdf] - Axel Pettersson, KTH and Logical Clocks, Sweden, 2022 (cosupervised with Sina Sheikholeslami and Moritz Meister)
Resource-Efficient and Fast Point-in-Time Joins for Apache Spark [pdf] - Nathan Bosch, KTH and Ericsson, Sweden, 2022 (cosupervised with Serveh Shalmashi and Forough Yaghoubi)
Integrating Telecommunications-Specific Language Models into a Trouble Report Retrieval Approach [pdf] - Petrus Oskarsson, KTH and Amazon, Sweden, 2022
The Ability of Visual and Language Explainable Models to Resemble Domain Expertise [pdf] - Ralfs Zangis, KTH and Logical Clocks, Sweden, 2022 (cosupervised with Sina Sheikholeslami and Moritz Meister)
Scaling Apache Hudi by boosting query performance with RonDB as a Global Index [pdf] - Akhil Yerrapragada, KTH and RISE, Sweden, 2021 (cosupervised with Nicolae Paladi)
Distributed Robust Learning [pdf] - Angel Luis Gonzalez, KTH and RISE, Sweden, 2021 (cosupervised with Francisco J. Pena)
Transformer-based Multistage Architectures for Code Search [pdf] - Jaweriah Alvi, KTH and Peltarion, Sweden, 2021 (cosupervised with Karl Erliksson)
Explainable Multimodal Fusion [pdf] - Jón Rúnar Baldvinsson, KTH and Ericsson, Sweden, 2021 (cosupervised with Mårtin Björkman)
Rare Event Learning In URLLC Wireless Networking Environment Using GANs [pdf] - Marcus Hägglund, KTH and RISE, Sweden, 2021 (cosupervised with Martina Scolamiero and Francisco J. Pena)
Deep Learning Approaches for Clustering Source Code by Functionality [pdf] - Nuria Marzo Grimalt, KTH and Ericsson, Sweden, 2021 (cosupervised with Serveh Shalmashi and Forough Yaghoubi)
Natural Language Processing Model for Log Analysis to Retrieve Solutions For Troubleshooting Processes [pdf] - Omar Emilio Contreras Zaragoza, KTH and Peltarion, Sweden, 2021 (cosupervised with Karl Erliksson)
Explainable Antibiotics Prescriptions in NLP with Transformer Models [pdf] - Alessio Molinari, KTH and Logical Clocks, Sweden, 2020 (cosupervised with Sina Sheikholeslami)
Designing a Performant Ablation Study Framework for PyTorch [pdf] - Anna Martignano, KTH and Swedbank, Sweden, 2020 (cosupervised with Paris Carbone and Mehrdad Mamaghani)
Real-time Anomaly Detection on Financial Data [pdf] - Anushka Garg, KTH and Agilon Analytics, Sweden, 2020 (cosupervised with Sina Sheikholeslami)
Comparing Machine Learning Algorithms and Feature Selection Techniques to Predict Undesired Behavior in Business Processes and Study of AutoML Frameworks [pdf] - Aref Moradi, KTH and Klarna, Sweden, 2020 (cosupervised with Sina Sheikholeslami)
Combining Learned and Analytical Models for Predicting CO2e Emissions in Textile Products [pdf] - Bharathwaj Krishnaswami Sreedhar, KTH and Sony Europe B.V., Sweden, 2020 (cosupervised with Magnus Boman)
Bayesian Optimization for Neural Architecture Search using Graph Kernels [pdf] - Filip Finfando, KTH and SonarHome, Sweden, 2020 (cosupervised with Ying Lie)
Indoor Scene Verification [pdf] - Francesco Lorenzo, KTH and King, Sweden, 2020 (cosupervised with Tianze Wang and Sahar Asadi)
Improving Generalization in Reinforcement Learning using Skill-based Rewards [pdf] - Gongchang Chu, KTH and Arkus AI, Sweden, 2020 (cosupervised with Shatha Jaradat and Nasim Farahini)
Machine Learning for Automation of Chromosome based Genetic Diagnostics [pdf] - Marina Angelovska, KTH and bol.com, Sweden, 2020 (cosupervised with Sina Sheikholeslami)
Content-based Recommender System for Detecting Complementary Products [pdf] - Milko Mitropolitsky, KTH, Sweden, 2020 (cosupervised with Zainab Abbas)
On the Impact of Graph Embedding on Device Placement [pdf] - Mohamed Hassan Hamza, KTH and Arkus AI, Sweden, 2020 (cosupervised with Ying Liu and Nasim Farahini)
Chromosome Classification using Machine Learning to enable Genetic Disorder Diagnostics [pdf] - Nabakumar Singh Khongbantabam, KTH and Fortum, Sweden, 2020 (cosupervised with Seif Haridi)
Development and Evaluation of an LSTM-VAE Based Anomaly Detection Pipeline for Battery Time-Series Measurements [pdf] - Pradyumna Krishna Kashyap, KTH and Logical Clocks, Sweden, 2020 (cosupervised with Jim Dowling)
Project-based Multi-tenant Container Registry For Hopsworks [pdf] - Vittorio M. E. Denti, KTH and Bontouch, Sweden, 2020 (cosupervised with Tianze Wang)
On The Effectiveness of β-VAEs for Image Classification and Clustering [pdf] - Andreas Elers, KTH and FOI, Sweden, 2019 (cosupervised with Farzad Kamrani)
Continual Imitation Learning: Enhancing Safe Data Set Aggregation with Elastic Weight Consolidation [pdf] - Davor Ljubenkov, KTH and MIT SCL, Sweden, 2019
Optimizing Bike Sharing System Flows using Graph Mining, Convolutional and Recurrent Neural Networks [pdf] - Benjamin Naoto Chiche, KTH and Microsoft France, Sweden, 2019
Video Classification with Memory and Computation-Efficient Convolutional Neural Network [pdf] - Andrea Nardelli, KTH and Spotify, Sweden, 2019
Sort Merge Buckets: Optimizing Repeated Skewed Joins in Dataflow [pdf] - Giorgio Ruffa, KTH and RaySearch, Sweden, 2019 (cosupervised with Fredrik Löfman)
Towards Unification of Organ Labeling in Radiation Therapy Using a Machine Learning Approach Based on 3D Geometries [pdf] - Tianze Wang, KTH, Sweden, 2019 (cosupervised with Christian Schulte)
Machine Learning for Constraint Programming [pdf] - Xinye Fu, KTH Royal Institute of Technology, Sweden, 2017
Building Evolutionary Clustering Algorithms on Spark [pdf] - Pradeep Peiris, KTH, Sweden, 2017
BigDataCube: Distributed Multidimensional Data Cube Over Apache Spark [pdf] - Adam Ulhir, KTH, Sweden, 2017
daGui: A DataFlow Graphical User Interface [pdf] - Alexander Östman, KTH, Sweden, 2017
Distributed Dominant Resource Fairness using Gradient Overlay [pdf] - Mohsen Hariri and Mahak Memar, KTH Royal Institute of Technology, Sweden, 2010
TuxStream: A Locality-Aware Hybrid Tree/Mesh Overlay For Peer-to-Peer Live Media Streaming [pdf]
Bachelor Students
- Rozhan Asadi and Albin Durfors, KTH, Sweden, 2024
Assessing Gender Bias in Large Language Model-Based Recommendation Systems [pdf] - Serkan Anar and Roy Liu, KTH, Sweden, 2024
Visualizing Social Sustainability: Use Case Linköping [pdf] - Ata Mazloomian, Amirkabir University of Technology, Iran, 2016
Measuring the Effectiveness of Different Vaccination Strategies to Prevent Disease Distribution in a P2P Network Using Gossip Algorithms [pdf] (in Farsi) - Vahid Pouryousef, Amirkabir University of Technology, Iran, 2016
Coloring Massive Graphs using GraphX [pdf] (in Farsi) - Reyhaneh Shahmohamadi, Amirkabir University of Technology, Iran, 2016
Anomaly Detection of Streaming Data Using Storm [pdf] (in Farsi) - Sina Sheikholeslami, Amirkabir University of Technology, Iran, 2016
SDMiner: A Tool for Mining Data Streams on top of Apache Spark [pdf] (in Farsi)
