Visit Our Open Source Projects

Associate Professor

http://sharif.edu/~matin/

Office: 119W West EE Bldg.

Phone: +98 (21) 66164307

Machine Learning

Big Data

Parallel and Distributed Computing

Embedded Systems

Assistant Professor

http://sina.sharif.edu/~saleh/

Office: 706 East EE Bldg.

Phone: +98 (21) 66164394

Machine Learning

Distributed Systems

Graphical Models

Causality

While every project has its unique aspects, in general our projects involve topics in one or both of the following two areas:

- CS & Math: Machine Learning, Big Data, Parallel and Distributed Algorithms, Graphical Models, Signal Processing

- Hardware: GPU, Cluster, Embedded Systems

The following practical skills are often helpful in many of our projects: C/C++, CUDA, OpenCL, Python, TensorFlow, PyTorch, Spark, Java, Android, Linux

Computer Vision

Machine Learning

Embedded Computer Vision

Computer Vision

Next Position: Tech Lead: Retina

GPGPU Acceleration for Graphical Model Learning

Computer Vision

Deep Learning for DSP Applications

Big Graph Acceleration on GPGPU

Deep Learning for DSP Applications

Next Position: Product Manager, Dorfak

Deep Reinforcement Learning for Graph Processing

Deep Learning for Localization

Signal Processing Acceleration on GPGPU

Machine Learning

Next Position: Product Manager, Retina

Machine Learning Acceleration on FPGA

Next Position: PhD, EE, EPFL

GPGPU Acceleration for Graphical Model Learning

Next Position: PhD, CS, U. of Toronto

Machine Learning

Signal Processing Acceleration on GPGPU

Next Position: PhD, CE, UCSD

Machine Learning for Biomedical Signal Processing

Next Position: PhD, EE, EPFL

Machine Learning in Graph Applications

Next Position: Balad Group, Cafebazar Co.

Deep Learning for Biomedical Signal Processing

Next Position: PhD, CS, EPFL

Deep Learning Acceleration on Android and Embedded Systems

Next Position: FanASA Co.

Deep Learning for Biomedical Signal Processing

Next Position: Product Manager, Tripinn Co.

FPGA-based Real-time Simulation

Next Position: PhD, CE, U. of Toronto

FPGA-based Real-time Simulation

Next Position: ZEI Co.

Image Processing

Next Position: PhD, CS, U. of Alberta

GPGPU Acceleration of Big Data Algorithms

Next Position: MS, CE, UBC

Deep Reinforcement Learning

Machine Learning on GPU

Next Position: MS, CS, TU Darmstadt

Machine Learning Acceleration on FPGA

Next Position: PhD, CE, North Carolina

Active Causal Discovery

Graph Matching

Next Position: PhD, CS, EPFL

Active Causal Discovery

Next Position: PhD, CS, EPFL

Causal Structure Learning in Time Series

Graph Matching

Next Position: PhD, CS, EPFL

Distributed Learning

Next Position: MS, CS, Waterloo

Machine Learning Acceleration on FPGA

Next Position: PhD, CS, Penn State

Machine Learning Acceleration on FPGA

Next Position: PhD, CE, UC Irvine

Deep Learning Acceleration on Android

Next Position: PhD, CS, Michigan Ann Arbor

Deep Learning Acceleration on Android

Next Position: PhD, CS, Michigan Ann Arbor

Computer Vision

Next Position: PhD, CS, UCLA

Graph Optimization Algorithms for Stream Processing

Next Position: PhD, University of Melbourne

(CE Dept.)

Graph Optimization Algorithms for Stream Processing

Next Position: PhD, CS, UPenn

Graph Optimization Algorithms for Stream Processing

Next Position: PhD, ECE, UT Austin

Parallel Computing

Next Position: Software Developer, Rahnema Co.

25537 Parallel Programming and Architectures (click here)

25xxx Causal Inference

25540 Distributed Systems

25737 Introduction to Machine Learning

25755 Data Structures and Algorithm Design

25767 Object Oriented Programming

25739 Python Programming Laboratory

25719 Advanced Programming Laboratory

- Amir Amirinezhad, Saber Salehkaleybar, Matin Hashemi, "Active Learning of Causal Structures with Deep Reinforcement Learning", Neural Networks, Vol. 154, October 2022.
- Amir Ahangarzadeh, Matin Hashemi, S. Alireza Nezamalhosseini, "Accurate Modulation Classification Under Impaired Wireless Channels via Shallow Convolutional Neural Networks", Physical Communication, Vol. 53, August 2022.
- Mehdi Saeidi, Matin Hashemi, "Area-Efficient Partially-Pipelined Architecture for Fast-SSC Decoding of Polar Codes", IEEE ICEE, 2022.
- Saber Salehkaleybar, Arsalan Sharif-nassab, and S. Jamal Golestani, "One-Shot Federated Learning: Theoretical Limits and Algorithms to Achieve Them", Journal of Machine Learning Research (JMLR), 2021.
- Soheil Shahrouz, Saber Salehkaleybar, Matin Hashemi, "gIM: GPU Accelerated RIS-based Influence Maximization Algorithm", IEEE Transactions on Parallel and Distributed Systems (TPDS), Vol. 32, No. 10, October 2021.
- Sepehr Dehdashtian, Matin Hashemi, Saber Salehkaleybar, "Deep-Learning Based Blind Recognition of Channel Code Parameters over Candidate Sets under AWGN and Multi-Path Fading Conditions", IEEE Wireless Communications Letters (WCL), February 2021.
- M. Reza Heydari, Saber Salehkaleybar, Kun Zhang, "Adversarial Orthogonal Regression: Two non-Linear Regressions for Causal Inference", Neural Networks, 2021.
- Hamidreza Bandealinaeini, Saber Salehkaleybar, "Broadcast Distributed Voting Algorithm in Population Protocols", IET Signal Processing, 2021.
- Behrooz Zarebavani, Foad Jafarinejad, Matin Hashemi, Saber Salehkaleybar, "cuPC: CUDA-based Parallel PC Algorithm for Causal Structure Learning on GPU", IEEE Transactions on Parallel and Distributed Systems (TPDS), Vol. 31, No. 3, March 2020.
- Saeed Saadatnejad, Mohammadhosein Oveisi, Matin Hashemi, "LSTM-Based ECG Classification for Continuous Monitoring on Personal Wearable Devices", IEEE Journal of Biomedical and Health Informatics (JBHI), Vol. 24, No. 2, February 2020.
- Benyamin Ghojogh, Saber Salehkaleybar, " Distributed Voting for Beep Model", Signal Processing, 2020.
- Ali AhmadiTeshnizi, Saber Salehkaleybar, Negar Kiyavash, " LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments", International Conference on Machine Learning (ICML), 2020.
- Samira Malek, Saber Salehkaleybar, Arash Amini, " Multi Variable-layer Neural Networks for Decoding Linear Codes", IWCIT, 2020.
- Saber Salehkaleybar, Amiremad Ghassami, Negar Kiyavash, and Kun Zhang, "Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables", Journal of Machine Learning Research (JMLR), 2020.
- Arsalan Sharif-nassab, S. Salehklaeybar, and S. Jamal Golestani, " Bounds on Over-Parameterization for Guaranteed Existence of Descent Paths in Shallow ReLU Networks ", International Conference on Learning Representations (ICLR), 2020.
- Arsalan Sharif-nassab, Saber Salehkaleybar, and S. Jamal Golestani, "Order Optimal One-Shot Distributed Learning", Conference on Neural Information Processing Systems (NeurIPS), 2019.
- Alireza Amirshahi, Matin Hashemi, "ECG Classification Algorithm Based on STDP and R-STDP Neural Networks for Real-time Monitoring on Ultra Low-Power Personal Wearable Devices", IEEE Transactions on Biomedical Circuits and Systems (TBioCAS), Vol. 13, No. 6, December 2019.
- Ali Hadizadeh, Matin Hashemi, Mostafa Parniani, "A Novel Algorithm for Design and Hardware Implementation of FPGA-Based Real-Time Simulator for Electrical Machines in HIL Applications", Journal of Iranian Association of Electrical and Electronics Engineers (JIAEEE), Vol. 16, No. 3, September 2019.
- Ali Hadizadeh, Matin Hashemi, Mohammad Labbaf, Mostafa Parniani, "A Matrix-Inversion Technique for FPGA-Based Real-time EMT Simulation of Power Converters", IEEE Transactions on Industrial Electronics (TIE), Vol. 66, No. 2, Feb. 2019.
- Amir Ghassami, Saber Salehkaleybar, Negar Kiyavash, Elias Bareinboim, "Budgeted Experiment Design for Causal Structure Learning", Proceedings of 35th International Conference on Machine Learning (ICML), July 2018.
- Matin Hashemi, Kamyar Mirzazad Barijough, Soheil Ghiasi, "Throughput-Driven Parallel Embedded Software Synthesis from Synchronous Dataflow Models: Caveats and Remedies", In "Model-Implementation Fidelity in Cyber Physical System Design", Edited by Christian Fabre, Anca Molnos, Springer, 2017, ISBN 978-3-319-47306-2.
- Amir Ghassami, Saber Salehkaleybar, Negar Kiyavash, Kun Zhang, " Learning Causal Structures Using Regression Invariance", Proceedings of 31st Conference on Neural Information Processing Systems (NIPS), December 2017.
- Saber Salehkaleybar, Jalal Etesami, Negar Kiyavash, Kun Zhang, " Learning Vector Autoregressive Models with Latent Processes", Proceedings of 32nd AAAI Conference on Artificial Intelligence (AAAI), February 2017.
- Saber Salehkaleybar, Jalal Etesami, Negar Kiyavash, " Identifying Nonlinear 1-Step Causal Influences in Presence of Latent Variables", Proceedings of International Symposium on Information Theory, 2017.
- Seyyed Salar Latifi Oskouei, Hossein Golestani, Matin Hashemi, Soheil Ghiasi, "CNNdroid: GPU-Accelerated Execution of Trained Deep Convolutional Neural Networks on Android", Proceedings of the ACM Multimedia Conference, Open Source Software Track, October 2016.
- Saber Salehkaleybar, Seyed Jamaloddin Golestani, " Token-based Function Computation with Memory", IEEE transactions on Parallel and Distributed Systems, Vol. 27, No. 6, June 2016.
- Saber Salehkaleybar, Seyed Jamaloddin Golestani, " Distributed Binary Majority Voting via Exponential Distribution", IET Signal Processing, Vol. 10, No. 5, June 2016.
- Saber Salehkaleybar, Mohammad Reza Pakravan, " A Periodic Jump-based Rendezvous Algorithm in Cognitive Radio Networks", Computer Communications, Vol. 79, April 2016.
- Saber Salehkaleybar, Arsalan Sharif-nassab, Seyed Jamaloddin Golestani, " Distributed Voting/Ranking with Optimal Number of States per Node", IEEE Transactions on Signal and Information Processing over Networks, Vol. 1, No. 4, December 2015.
- Kamyar Mirzazad Barijough, Matin Hashemi, Volodymyr Khibin, Soheil Ghiasi, "Implementation-Aware Model Analysis: The Case of Buffer-Throughput Tradeoff in Streaming Applications", Proceedings of the ACM SIGPLAN/SIGBED Conference on Languages, Compilers and Tools for Embedded Systems (LCTES), June 2015.
- Kamyar Mirzazad Barijough, Matin Hashemi, Volodymyr Khibin, Soheil Ghiasi, "Implementation-Aware Buffer-Throughput Tradeoff in Embedded Stream Applications", IEEE/ACM Design Automation and Test in Europe (DATE), Workshop on Model Implementation Fidelity, March 2015.
- Mohammad H. Foroozannejad, Matin Hashemi, Alireza Mahini, Bevan Baas, Soheil Ghiasi, "Time-Scalable Mapping for Circuit-Switched GALS Chip Multiprocessor Platforms", IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), Vol. 33, No. 5, May 2014.
- Matin Hashemi, Mohammad H. Foroozannejad, Soheil Ghiasi, "Throughput-Memory Footprint Trade-off in Synthesis of Streaming Software on Embedded Multiprocessors", ACM Transactions on Embedded Computing Systems (TECS), Vol. 13, No. 3, December 2013.
- Seyed Arash Majd, Saber Salehkaleybar, M. R. Pakravan, " Multi-user Opportunistic Spectrum Access with Channel Impairments", AEU International Journal of Electronics and Communications, Vol. 67, No. 11, November 2013.
- Saber Salehkaleybar, Seyed Jamaloddin Golestani, " Averaging Consensus over Erasure Channels via Local Synchronization", Proceedings of International Symposium on Information Theory, June 2013.
- Saber Salehkaleybar, Seyed Arash Majd, Mohammad Reza Pakravan, " Delay Analysis and Buffer Management for Random Access in Cognitive Radio Networks", Proceedings of Iran Workshop on Communication and Information Theory, May 2013.
- Matin Hashemi, Mohammad H. Foroozannejad, Christoph Etzel, Soheil Ghiasi, "FORMLESS: Scalable Utilization of Embedded Manycores in Streaming Applications", Proceedings of the ACM SIGPLAN/SIGBED Conference on Languages, Compilers and Tools for Embedded Systems (LCTES), pp. 71-78, June 2012.
- Mohammad H. Foroozannejad, Trevor Hodges, Matin Hashemi, Soheil Ghiasi, "Postscheduling Buffer Management Trade-offs in Streaming Software Synthesis", ACM Transactions on Design Automation of Electronic Systems (TODAES), Vol. 17, No. 3, June 2012.
- Matin Hashemi, Soheil Ghiasi, "Towards Scalable Utilization of Embedded Manycores in Throughput-Sensitive Applications", IEEE International High Level Design Validation and Test Workshop (HLDVT), pp. 110-115, November 2011 (invited).
- Saber Salehkaleybar, Seyed Arash Majd, Mohammad Reza Pakravan, " QoS Aware Joint Policies in Cognitive Radio Networks", Proceedings of International Wireless Communications and Mobile Computing Conference, July 2011.
- Soheil Ghiasi, Matin Hashemi, Volodymyr Khibin, Faisal Khan, "Puzzle Solver Accelerators Make Excellent Capstone Design Projects", IEEE International Conference on Microelectonics System Education (MSE), pp. 21-24, June 2011.
- Saber Salehkaleybar, Seyed Arash Majd, Mohammad Reza Pakravan, " An Upper Bound on the Throughput for Myopic Policy in Multi-channel Opportunistic Access", Proceedings of International Symposium on Telecommunications, December 2010.
- Mohammad H. Foroozannejad, Matin Hashemi, Trevor Hodges, Soheil Ghiasi, "Look Into Details: The Benefits of Fine-Grain Streaming Buffer Analysis", Proceedings of the ACM SIGPLAN/SIGBED Conference on Languages, Compilers and Tools for Embedded Systems (LCTES), pp. 27-36, April 2010.
- Matin Hashemi, Soheil Ghiasi, "Versatile Task Assignment for Heterogeneous Soft Dual-Processor Platforms", IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), Vol. 29, No. 3, March 2010.
- Matin Hashemi, Soheil Ghiasi, "Throughput-Driven Synthesis of Embedded Software for Pipelined Execution on Multicore Architectures", ACM Transactions on Embedded Computing Systems (TECS), Vol. 8, No. 2, January 2009.
- Po-Kuan Huang, Matin Hashemi, Soheil Ghiasi, "System-Level Performance Estimation for Application-Specific MPSoC Interconnect Synthesis", IEEE Symposium on Application Specific Processors (SASP), pp. 95-100, June 2008.
- Matin Hashemi, Soheil Ghiasi, "Exact and Approximate Task Assignment Algorithms for Pipelined Software Synthesis", Proceedings of the IEEE/ACM Design Automation and Test in Europe (DATE), pp. 746-751, March 2008.
- Po-Kuan Huang, Matin Hashemi, Soheil Ghiasi, "Joint Throughput and Energy Optimization for Pipelined Execution of Embedded Streaming Applications", Proceedings of the ACM SIGPLAN/SIGBED Conference on Languages, Compilers and Tools for Embedded Systems (LCTES), pp. 137-139, June 2007.

Accurate Modulation Classification Under Impaired Wireless Channels via Shallow Convolutional Neural Networks

GPU Accelerated RIS-based Influence Maximization Algorithm

Deep-Learning Based Blind Recognition of Channel Code Parameters over Candidate Sets under AWGN and Multi-Path Fading Conditions

CUDA-based Parallel PC Algorithm for Causal Structure Learning on GPU

ECG Classification Algorithm Based on STDP and R-STDP Neural Networks for Real-time Monitoring on Ultra Low-Power Personal Wearable Devices

LSTM-Based ECG Classification for Continuous Monitoring on Personal Wearable Devices

GPU-Accelerated Execution of Trained Deep Convolutional Neural Networks on Android

Synchronous Dataflow (SDF) Graph Benchmarks for Parallel Processing