MSRG

Middleware Systems Research Group at @UofTEngineering department of @ECEUofT under Professor @Arno_Jacobsen.

[Shashank @sh1sh1nk]

🚀 Excited to share our latest work on decentralized sequencers for rollups! Offers a deep analysis of the challenges, trade-offs, and potential solutions in this emerging technology. Check it out: https://t.co/5nuozINjsO
@convoluted_code @the_matter_labs @MSRG_Org

[MSRG @MSRG_Org]

MSRG's annual end-of-summer BBQ was this past week 🍔🌽🍉! Wishing everyone a happy new semester!

[MSRG @MSRG_Org]

Congratulations to our summer student, Nick!

[CQIQC @CQIQC_Toronto]

⚡️CQIQC Undergrad Summer Research Recipient Nick Taylor presented his work on #quantum machine learning at @UofTDSI's SUDS Showcase & @uoftengineering's UnERD

🏆He was one of the top-voted posters at the SUDS Showcase!

Read more: https://t.co/BeEZFdsUD8

[CQIQC @CQIQC_Toronto]

We collaborated with IBM to help bridge the 'Academia-Industry gap' alongside PINQ2 and SOSCIP.

This conference brought 80 people to #uoft, from students and industry leaders, to discuss #quantumcomputing research opportunities💡

Read more: https://t.co/G8RLqv0YU8

[MSRG @MSRG_Org]

⚛️ We had a great time at @CQIQC_Toronto's #QuantumComputing Research conference, co-organized with @IBMQuantum, @SOSCIP_Research and #PINQ2!

Thank you to all the presenters & organizers.

[MSRG @MSRG_Org]

a CRDT based collaborative circuit diagram editor, and a Forest fire detection tool using computer vision algorithms through drone cameras! (2/2)

[MSRG @MSRG_Org]

Congratulations to all the 4th-year undergraduate students who completed their Capstone Design Projects at the @uoftengineering 2023 Design Fair! This year, MSRG’s projects included a writing robot powered by AI (1/2)

[MSRG @MSRG_Org]

⭐��� We are Now Hiring for a Postdoctoral Position!

Exploring #Quantum #Machine #Learning Advantage for Molecular Property Predictions at @eceuoft / @chemuoft (@UofT).

Please see attached image for more information.

Apply here ➡️ https://t.co/FwzOMOrP1F

[MSRG @MSRG_Org]

The integration makes V-Guard achieve consensus seamlessly under changing members while producing an immutable ledger of data transactions with their membership profiles. Check out the paper at: https://t.co/8Wg7wpaBb7

[MSRG @MSRG_Org]

Check out our latest work on consensus algorithms: the VGuard project!

V-Guard proposes a high-performance BFT algorithm that operates under dynamically changing memberships, targeting the problem of vehicles' arbitrary connectivity on the roads.

https://t.co/DSkSwj8MWK

[MSRG @MSRG_Org]

In the event of membership changes, traditional BFT algorithms must stop ongoing consensus and update system configurations, thereby suffering from severe performance degradation. In contrast, V-Guard integrates the consensus of membership management into data transactions.

[MSRG @MSRG_Org]

@UofTDSI SUDS Research Program at @UofT !
See below for more info. ⬇️ Applications close Jan 23 2023.

#ResearchOpportunity #QuantumChemistry #DeepLearning #QuantumMachineLearning #ResearchOpportunity

[MSRG @MSRG_Org]

🚨 Call for student researchers for @UofTDSI SUDS Research Program! 🖥️

Project: Bridging the gap between quantum chemistry and deep learning

https://t.co/1NoMkv0K5O

Apply by Jan 23 2023

#QuantumChemistry #DeepLearning #QuantumMachineLearning #ResearchOpportunity

[MSRG @MSRG_Org]

Applications are still open for the @UofTDSI SUDS Research Program at @UofT !
See below for more info. ⬇️

#ResearchOpportunity #QuantumMachineLearning #QuantumComputing #MachineLearning!

[MSRG @MSRG_Org]

⭐️ Call for student researchers for @UofTDSI SUDS Research Program! 🖥️

Project: Development of quantum machine learning methods for chemical property predictions

https://t.co/1NoMkv0K5O

Apply by Jan 23 2023

#QuantumMachineLearning #QuantumComputing #MachineLearning #Research

[MSRG @MSRG_Org]

Training DL models like neural networks requires millions of data points to attain good generalization. This is hindering the development of DL models for chemistry as the generation of large training data using accurate QM methodologies has an infeasible computational cost.

[MSRG @MSRG_Org]

🚨 Call for student researchers for @UofTDSI SUDS Research Program! 🖥️

Project: Bridging the gap between quantum chemistry and deep learning

https://t.co/1NoMkv0K5O

Apply by Jan 23 2023

#QuantumChemistry #DeepLearning #QuantumMachineLearning #ResearchOpportunity

[MSRG @MSRG_Org]

Deep learning (DL) can potentially substitute traditionally used expensive quantum mechanical (QM) methodologies in chemistry to predict various chemical properties by offering to generate fast and accurate mathematical models better suited to everyday computers.

[MSRG @MSRG_Org]

Chemical property predictions using quantum machine Learning is a highly relevant topic at the intersection of machine learning, quantum algorithms, and chemistry. This project will focus on how chemical properties can be predicted with the help of quantum computers.

[MSRG @MSRG_Org]

⭐️ Call for student researchers for @UofTDSI SUDS Research Program! 🖥️

Project: Development of quantum machine learning methods for chemical property predictions

https://t.co/1NoMkv0K5O

Apply by Jan 23 2023

#QuantumMachineLearning #QuantumComputing #MachineLearning #Research

[MSRG @MSRG_Org]

We had a great afternoon with Professor Patrick Hung's research group from @ontariotech_u, sharing research on trustworthy #AI, #MachineLearning, #robotic dogs, accessible #VirtualReality, #CloudComputing, #ConsensusAlgorithms and more!

[MSRG @MSRG_Org]

We welcome Pouya Kananian to the MSRG team!

Pouya is a Ph.D. student at @UofT under the supervision of Professor @arno_jacobsen. His research interests include #distributed #systems, #machine #learning, and #quantum #computing.