Anjana Parwat Singh

Post-Doctoral Researcher (Ph.D. Candidate)
Department of Computer Science and Engineering
Indian Institute of Technology Hyderabad (IIT Hyderabad), India
Address: Room No. C-310, Academic Block C,
Indian Institute of Technology Hyderabad, India (502285)
Email: cs17resch11004 [at] iith [dot] ac [dot] in

About Me

Department of Computer Science and Engineering

Indian Institute of Technology Hyderabad

Dr. Sathya Peri

Department of Computer Science and Engineering

Indian Institute of Technology Hyderabad

University of Hyderabad (UoH)

Dr. Rajeev Wankar

Recent!

May 11, 2022: Paper titled "An Efficient Approach to Move Elements in a Distributed Geo-Replicated Tree" accepted at IEEE Cloud 2022 as a regular full paper.

May 07, 2022: Paper titled "A Self-Stabilizing Low Stretch Spanning Tree Construction" accepted at NETYS 2022 as a full paper.

April 09, 2022: Paper titled "OptSmart: A Space Efficient Optimistic Concurrent Execution of Smart Contracts" accepted at DAPD Journal 2022.

Mar 15, 2022: Short paper titled "An Efficient Approach to Move Elements in a Distributed Geo-Replicated Tree" accepted at CCGrid 2022 for poster presentaion.

Jan 25, 2022: Submitted my PhD thesis "Techniques for Efficient Parallel Execution of Smart Contracts in Blockchains".

Nov 28, 2021: Paper titled "DiPETrans: A Framework for Distributed Parallel Execution of Transactions of Blocks in Blockchain" accepted at CCPE 2021.

Nov 20, 2021: Short paper titled "Efficient Parallel Execution of Block Transactions in Blockchain" accepted at Middleware 2021 Doctoral Symposium.

Education

Doctor of Philosophy in Computer Science (July 2017 - January 2022) from Indian Institute of Technology Hyderabad, India. [Thesis Submitted].
Master of Technology in Computer Science, (July 2014 - September 2016) from University of Hyderabad, India, (8.71 CGPA) -- (83.88 %).
Bachelor of Technology in Computer Science, (July 2007 - April 2011) from Rajasthan Technical University, India, (63.89 %).

Publications

Journal Papers

Anjana Parwat Singh, Sweta Kumari, Sathya Peri, Sachin Rathor, and Archit Somani, OptSmart: A Space Efficient Optimistic Concurrent Execution of Smart Contracts, Distributed and Parallel Databases (DAPD), Volume ?, No. ?, Pages: ?, ISSN: 1573-7578, Springer Nature Switzerland AG.
```
@article{Anjana2021OptSmart,
author  = {Parwat Singh Anjana and Sweta Kumari and Sathya Peri and Sachin Rathor and Archit Somani},
title     = {OptSmart: A Space Efficient Optimistic Concurrent Execution of Smart Contracts},
journal = {Distrib Parallel Databases},
volume = { },
year = {2022},
url = {https://link.springer.com/article/10.1007/s10619-022-07412-y},
biburl = {https://doi.org/10.1007/s10619-022-07412-y}
}
						
```
Popular blockchains such as Ethereum and several others execute complex transactions in the block through user-defined scripts known as smart contracts. Serial execution of smart contract transactions/atomic units (AUs) fails to harness the multiprocessing power offered by the prevalence of multi-core processors. By adding concurrency to the execution of AUs, we can achieve better efficiency and higher throughput. In this paper, we develop a concurrent miner that proposes a block by executing AUs concurrently using optimistic Software Transactional Memory systems (STMs). It efficiently captures independent AUs in the concurrent bin and dependent AUs in the block graph (BG). Later, we propose a concurrent validator that re-executes the same AUs concurrently and deterministically using the concurrent bin followed by the BG given by the miner to verify the block. We rigorously prove the correctness of concurrent execution of AUs. The performance benchmark shows that the average speedup for the optimized concurrent miner is 5.21×, while the maximum is 14.96× over the serial miner. The optimized validator obtains an average speedup of 8.61× to a maximum of 14.65× over the serial validator. The proposed miner outperforms 1.02× to 1.18×, while the proposed validator outperforms 1× to 4.46× over state-of-the-art concurrent miners and validators, respectively. Moreover, the proposed efficient BG saves an average of 2.29× more block space when compared with the state-of-the-art.
Shrey Baheti, Anjana Parwat Singh, Sathya Peri, and Yogesh Simmhan, DiPETrans: A Framework for Distributed Parallel Execution of Transactions of Blocks in Blockchain, Concurrency and Computation: Practice and Experience (CCPE), Volume 34, No. 10, Pages: e6804, ISSN: 1532-0634, Wiley Press, New York, USA. [*All authors contributed equally.]
```
@article{Baheti2019DiPETrans,
author = {Shrey Baheti and Parwat Singh Anjana and Sathya Peri and Yogesh Simmhan},
title = {DiPETrans: A Framework for Distributed Parallel Execution of Transactions of Blocks in Blockchain},
journal = {Concurrency and Computation: Practice and Experience},
volume = {n/a},
year = {2022},pages = {e6804},
doi = {https://doi.org/10.1002/cpe.6804},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.6804},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.6804}
}
						
```
Contemporary blockchain such as Bitcoin and Ethereum execute transactions serially by miners and validators and determine the Proof-of-Work (PoW). Such serial execution is unable to exploit modern multi-core resources efficiently, hence limiting the system throughput and increasing the transaction acceptance latency. The objective of this work is to increase the transaction throughput by introducing parallel transaction execution using a static analysis technique. We propose a framework DiPETrans for the distributed execution of the transactions in a block. Here, peers in the blockchain network form a community to execute the transactions and find the PoW parallelly, using a leader-follower approach. During mining, the leader statically analyzes the transactions, creates different groups (shards) of independent transactions, and distributes them to followers to execute them in parallel. After the transaction executes, the community's compute power is utilized to solve the PoW concurrently. When a block is successfully created, the leader broadcasts the proposed block to other peers in the network for validation. On receiving a block, validators re-execute the block transactions and accept the block if they reach the same state as shared by the miner. Validation can also be done as a community, in parallel, following the same leader-follower approach as mining. We report experiments using over 5 Million real transactions from the Ethereum blockchain and execute them using our DiPETrans framework to empirically validate the benefits of our techniques over traditional sequential execution. We achieve a maximum speedup of 2.2x for the miner and 2.0x for the validator, with 100 to 500 transactions per block. Further, we achieve a peak of 5x end-to-end block creation speedup using a parallel miner over a serial miner when using 6 machines in the community.

Conference Papers

Anjana Parwat Singh, Hagit Attiya, Sweta Kumari, Sathya Peri, and Archit Somani, Efficient Concurrent Execution of Smart Contracts in Blockchains using Object-based Transactional Memory, In 8th International Conference on Networked Systems (NETYS 2020), Marrakech, Morocco, June 2020.
```
@InProceedings{Anjana2020netysObjSC,
author="Anjana, Parwat Singh and Attiya, Hagit and Kumari, Sweta and Peri, Sathya and Somani, Archit",
title="Efficient Concurrent Execution of Smart Contracts in Blockchains Using Object-Based Transactional Memory",
booktitle="Networked Systems",
year="2021",
publisher="Springer International Publishing",
address="Cham",
pages="77--93",
isbn="978-3-030-67087-0"
}
						
```
Several popular blockchains such as Ethereum execute complex transactions through user-defined scripts. A block of the chain typically consists of multiple smart contract transactions (SCTs). To append a block into the blockchain, a miner executes these SCTs. On receiving this block, other nodes act as validators, who re-execute these SCTs as part of the consensus protocol to validate the block. In Ethereum and other blockchains that support cryptocurrencies, a miner gets an incentive every time such a valid block is successfully added to the blockchain. When executing SCTs sequentially, miners and validators fail to harness the power of multiprocessing offered by the prevalence of multi-core processors, thus degrading throughput. By leveraging multiple threads to execute SCTs, we can achieve better efficiency and higher throughput. Recently, Read-Write Software Transactional Memory Systems (RWSTMs) were used for concurrent execution of SCTs. It is known that Object-based STMs (OSTMs), using higher-level objects (such as hash-tables or lists), achieve better throughput as compared to RWSTMs. Even greater concurrency can be obtained using Multi-Version OSTMs (MVOSTMs), which maintain multiple versions for each shared data item as opposed to Single-Version OSTMs (SVOSTMs).
This paper proposes an efficient framework to execute SCTs concurrently based on object semantics, using optimistic SVOSTMs and MVOSTMs. In our framework, a multi-threaded miner constructs a Block Graph (BG), capturing the object-conflicts relations between SCTs, and stores it in the block. Later, validators re-execute the same SCTs concurrently and deterministically relying on this BG. A malicious miner can modify the BG to harm the blockchain, e.g., to cause double spending. To identify malicious miners, we propose Smart Multi-threaded Validator (SMV). Experimental analysis shows that proposed multi-threaded miner and validator achieve significant performance gains over state-of-the-art SCT execution framework.
Anjana Parwat Singh, Sweta Kumari, Sathya Peri, Sachin Rathor, and Archit Somani, An Efficient Framework for Optimistic Concurrent Execution of Smart Contracts, In 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processings (PDP 2019). Pavai, Italy, February 2019.
```
@INPROCEEDINGS{Anjana2019pdpEff,
author={Anjana, Parwat Singh and Kumari, Sweta and Peri, Sathya and Rathor, Sachin and Somani, Archit},
booktitle={2019 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)}, 
title={An Efficient Framework for Optimistic Concurrent Execution of Smart Contracts},
year={2019},
volume={},
number={},
pages={83-92},
doi={10.1109/EMPDP.2019.8671637}
}
						
```
Blockchain platforms such as Ethereum and several others execute complex transactions in blocks through user-defined scripts known as smart contracts. Normally, a block of the chain consists of multiple transactions of smart contracts which are added by a miner. To append a correct block into the blockchain, miners execute these transactions of smart contracts sequentially. Later the validators serially re-execute the smart contract transactions of the block. If the validators agree with the final state of the block as recorded by the miner, then the block is said to be validated. It is then added to the blockchain using a consensus protocol. In Ethereum and other blockchains that support cryptocurrencies, a miner gets an incentive every time such a valid block successfully added to the blockchain. In most of the current day blockchains the miners and validators execute the smart contract transactions serially. In the current era of multi-core processors, by employing the serial execution of the transactions, the miners and validators fail to utilize the cores properly and as a result, have poor throughput. By adding concurrency to smart contracts execution, we can achieve better efficiency and higher throughput. In this paper, we develop an efficient framework to execute the smart contract transactions concurrently using optimistic Software Transactional Memory systems (STMs). Miners execute smart contract transactions concurrently using multi-threading to generate the final state of blockchain. STM is used to take care of synchronization issues among the transactions and ensure atomicity. Now when the validators also execute the transactions (as a part of validation) concurrently using multi-threading, then the validators may get a different final state depending on the order of execution of conflicting transactions. To avoid this, the miners also generate a block graph of the transactions during the concurrent execution and store it in the block. This graph captures the conflict relations among the transactions and is generated concurrently as the transactions are executed by different threads. The miner proposes a block which consists of set of transactions, block graph, hash of the previous block, and final state of each shared data-objects. Later, the validators re-execute the same smart contract transactions concurrently and deterministically with the help of block graph given by the miner to verify the final state. If the validation is successful then proposed block appended into the blockchain and miner gets incentive otherwise discard the proposed block. We execute the smart contract transactions concurrently using Basic Time stamp Ordering (BTO) and Multi-Version Time stamp Ordering (MVTO) protocols as optimistic STMs. BTO and MVTO miner achieves 3.6x and 3.7x average speedups over serial miner respectively. Along with, BTO and MVTO validator outperform average 40.8x and 47.1x than serial validator respectively.
Anjana Parwat Singh, Priyanka Badiwal, Rajeev Wankar, Swaroop Kallakuri, and C. Raghavendra Rao, Cloud Service Provider Evaluation System using Fuzzy Rough Set Technique, In 13th IEEE International Conference on Service-Oriented System Engineering (SOSE 2019). San Francisco, California, April 2019.
```
@INPROCEEDINGS{Anjana2019soseEFRSCB,
author={Anjana, Parwat Singh and Badiwal, Priyanka and Wankar, Rajeev and Kallakuri, Swaroop and Rao, C. Raghavendra},
booktitle={2019 IEEE International Conference on Service-Oriented System Engineering (SOSE)},
title={Cloud Service Provider Evaluation System Using Fuzzy Rough Set Technique}, 
year={2019},
volume={},
number={},
pages={187-18709},
doi={10.1109/SOSE.2019.00033}
}
						
```
Cloud Service Provider (CSP) offers a wide variety of scalable, flexible, and cost-efficient services to users on demand and pay-per-utilization basis. However, vast diversity in available services leads to various challenges for a user to determine and select the best suitable service. Further, sometime user needs to hire required services from multiple service providers which leads to account, security, support, interface, and Service Level Agreements (SLAs) associated management difficulties. To avoid such problems having a Cloud Service Broker (CSB) which is aware of service offerings and user's Quality of Service (QoS) requirements will benefit both the service providers and users. We have proposed a cloud service brokerage architecture using fuzzy rough set technique, which facilitates ranking and selecting services, based on users QoS requirements and finally monitor the service execution. We have used fuzzy rough set technique for dimension reduction and weighted Euclidean distance to rank the service providers. To prioritize user QoS request, we suggest to use user assign weights. We also incorporate system assigned weights to give the relative importance to QoS attributes. We compared the proposed ranking technique with an existing technique based on the system response time. With the help of a case study, we have demonstrated the efficiency of the proposed technique. The case study experiment results show that the proposed approach is scalable, resilience, and produce better results with less searching time.
Anjana Parwat Singh, Rajeev Wankar, and C. Raghavendra Rao, Design of a Cloud Brokerage Architecture Using Fuzzy Rough Set Technique, In 11th Multi-disciplinary International Workshop on Artificial Intelligence (MIWAI 2017). Tungku, Brunei, November 2017.
```
@InProceedings{Anjana2017miwaiFRSCB,
author="Anjana, Parwat Singh and Wankar, Rajeev and Rao, C. Raghavendra",
title="Design of a Cloud Brokerage Architecture Using Fuzzy Rough Set Technique",
booktitle="Multi-disciplinary Trends in Artificial Intelligence",
year="2017",
publisher="Springer International Publishing",
address="Cham",
pages="54--68",
isbn="978-3-319-69456-6"
}
						
```
Cloud computing offers numerous services to the cloud consumers such as infrastructure, platform, software, etc. Due to the vast diversity in available cloud services from the user point of view, it leads to several challenges to rank and select the potential cloud service. One of the plausible solutions for the problem can be obtained with the use of Rough Set Theory (RST) and available in the literature. Unfortunately, Rough Set Theory cannot deal with numerical values. One of the classical solutions to this problem can be obtained by using Fuzzy Rough Set. To the best of our knowledge, there is no working Fuzzy-Rough Set based brokerage architecture available which is used for minimizing attributes, search space and for ranking the service providers. In this paper, we proposed a Fuzzy Rough Set based Cloud Brokerage (FRSCB) architecture, which is responsible for service selection based on consumers Quality of Service (QoS) request. We propose to use Fuzzy Rough Set Theory (FRST) to minimize the number of attributes and searching space. We also did the QoS attribute categorization to identify functional and non-functional requirements and behavior of the attributes (static/dynamic). Finally, we develop an algorithm that recommends potential cloud services to the cloud consumers.

Posters/Short Papers

Anjana Parwat Singh, Efficient Parallel Execution of Block Transactions in Blockchain, Proceedings of the 22nd International Middleware Conference: Doctoral Symposium (Middleware 2021), Quebec city, Canada, December 2021.
```
@inproceedings{AnjanaParBlockMiddleware2021,
author = {Anjana, Parwat Singh},
title = {Efficient Parallel Execution of Block Transactions in Blockchain},
year = {2021},
isbn = {9781450391559},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3491087.3493676},
doi = {10.1145/3491087.3493676},
booktitle = {Proceedings of the 22nd International Middleware Conference: Doctoral Symposium},
pages = {8–11},
numpages = {4},
location = {Qu\'{e}bec city, Canada},
series = {Middleware '21}
}						
```
Miners and validators in current blockchains serially execute block transactions. Such serial execution cannot efficiently utilize modern multi-core resources, consequently hampering system throughput. We propose three approaches to improve blockchain throughput by introducing parallel execution of block transactions. We present a static analysis-based DiPETrans approach that groups the block transactions into independent shards and executes them parallelly in a distributed fashion using a leader-follower method. DiPETrans is empirically evaluated with 5 million actual transactions from the Ethereum blockchain.
Since static analysis fails to identify the conflicts precisely, we introduce OptSmart to exploit multi-processing on a multi-core system to improve throughput further. Miners and validators use multiple threads to parallelly execute smart contract transactions (SCTs) in a block. A miner concurrently executes SCTs using optimistic read-write software transactional memory systems (RWSTMs) and saves the non-conflicting SCTs in the concurrent bin and conflicting SCTs in the block graph (BG). Later, validators re-execute SCTs deterministically in parallel to validate the block by using information appended by the concurrent miner.
In terms of throughput, optimistic object-based STMs (OSTMs) with higher-level objects are known to outperform RWSTMs. We propose ObjSC approach based on optimistic OSTM, and a counter-based smart multi-threaded validator (SMV) that efficiently detects and rejects malicious blocks proposed by the malicious miners. The simulation result shows that the proposed approaches outperform existing approaches.
Anjana Parwat Singh, Hagit Attiya, Sweta Kumari, Sathya Peri, and Archit Somani, Efficient Concurrent Execution of Smart Contracts in Blockchains using Object-based Transactional Memory, Accepted as a Short Paper for Presentation in 15th Academic Research and Careers for Students Symposium (ARCS 2021), Coimbatore, India, February 2021.

Several popular blockchains such as Ethereum execute complex transactions through user-defined scripts. A block of the chain typically consists of multiple smart contract transactions (SCTs). To append a block into the blockchain, a miner executes these SCTs. On receiving this block, other nodes act as validators, who re-execute these SCTs as part of the consensus protocol to validate the block. In Ethereum and other blockchains that support cryptocurrencies, a miner gets an incentive every time such a valid block is successfully added to the blockchain. When executing SCTs sequentially, miners and validators fail to harness the power of multiprocessing offered by the prevalence of multi-core processors, thus degrading throughput. By leveraging multiple threads to execute SCTs, we can achieve better efficiency and higher throughput. Recently, Read-Write Software Transactional Memory Systems (RWSTMs) were used for concurrent execution of SCTs. It is known that Object-based STMs (OSTMs), using higher-level objects (such as hash-tables or lists), achieve better throughput than RWSTMs.
This paper proposes an efficient framework to execute SCTs concurrently based on object semantics, using optimistic SVOSTMs. In our framework, a multi-threaded miner constructs a Block Graph (BG), capturing the object-conflicts relations between SCTs, and stores it in the block. Later, validators re-execute the same SCTs concurrently and deterministically relying on this BG. A malicious miner can modify the BG to harm the blockchain, e.g., to cause double spending. To identify malicious miners, we propose Smart Multi-threaded Validator (SMV). Experimental analysis shows that proposed multi-threaded miner and validator achieve significant performance gains over state-of-the-art SCT execution framework.
Prashansa Agrawal, Anjana Parwat Singh, and Sathya Peri, DeHiDe: Deep Learning-based Hybrid Model to Detect Fake News using Blockchain, In 22nd International Conference on Distributed Computing and Networking (ICDCN 2021). Nara, Japan, January 2021.
```
@inproceedings{Agrawal2021icdcnDeHiDe,
author = {Agrawal, Prashansa and Anjana, Parwat Singh and Peri, Sathya},
title = {DeHiDe: Deep Learning-Based Hybrid Model to Detect Fake News Using Blockchain*},
year = {2021},
isbn = {9781450389334},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3427796.3430003},
doi = {10.1145/3427796.3430003},
booktitle = {International Conference on Distributed Computing and Networking 2021},
pages = {245–246},
numpages = {2},
location = {Nara, Japan},
series = {ICDCN '21}
}
						
```
The surge in the spread of immensely powerful deep-fakes, pseudo-news, misleading information, lies, propaganda, and false facts, frequently known as fake news, raised questions concerning social media’s influence in today’s fast-moving society. It is challenging to overcome fake news in traditional centralized systems. Blockchain technology can help in contending with such problems. A novel idea of DeHiDe: Deep Learning-based Hybrid Model to Detect Fake News using Blockchain is presented in this paper. DeHiDe is a blockchain-based framework for legitimate news sharing by filtering out the fake news. It combines the benefit of blockchain with an intelligent deep learning model to reinforce robustness and accuracy in combating fake news’s hurdle.
Anjana Parwat Singh, Sweta Kumari, Sathya Peri, Sachin Rathor, and Archit Somani, Entitling Concurrency to Smart Contracts using Optimistic Transactional Memory, In 20th International Conference on Distributed Computing and Networking (ICDCN 2019). Bangalore, India, January 2019. Recipient of ICDCN 2019 Best Poster Award.
```
@inproceedings{Anjana2019icdcnEff,
author = {Anjana, Parwat Singh and Kumari, Sweta and Peri, Sathya and Rathor, Sachin and Somani, Archit},
title = {Entitling Concurrency to Smart Contracts Using Optimistic Transactional Memory},
year = {2019},
isbn = {9781450360944},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3288599.3299723},
doi = {10.1145/3288599.3299723},
booktitle = {Proceedings of the 20th International Conference on Distributed Computing and Networking},
pages = {508},
numpages = {1},
location = {Bangalore, India},
series = {ICDCN '19}
}
						
```
It is commonly believed that blockchain is a revolutionary technology for doing business on the Internet. Blockchain is a decentralized, distributed database or ledger of records. It ensures that the records are tamper-proof but publicly readable. Blockchain platforms such as Ethereum and several others execute complex transactions in blocks through user-defined scripts known as smart contracts. Normally, a block of the chain consists of multiple transactions of smart contracts which are added by a miner. To append a correct block into the blockchain, miners execute these transactions of smart contracts sequentially. Later the validators serially re-execute the smart contract transactions of the block. If the validators agree with final state of the blocks as recorded by the miner, then the block is said to be valid and added to the blockchain using a consensus protocol.

Unpublished Manuscripts

Priyanka Badiwal, Anjana Parwat Singh, Rajeev Wankar, and C. Raghavendra Rao, DRONA: A Data-driven Randomized Algorithm for Complex Optimization Problems.

Ongoing Projects

OptNest: Optimistic Concurrent Execution of Nested Transactions in Blockchain
DeHiDe: Deep Learning-based Hybrid Model to Detect Fake News using Blockchain
BDIDS: A Blockchain-based Distributed Intrusion Detection System for IoT Networks

Research Association

I am very fortunate to work with:

Prof. Sathya Peri, Indian Institute of Technology Hyderabad, India.
Prof. Rajeev Wankar, University of Hyderabad, India.
Prof. C. Raghavendra Rao, University of Hyderabad, India.
Dr. Archit Somani, Technion, Israel.
Dr. Sweta Kumari, Technion, Israel.

Achievements and Services

Achievements

Awarded Institute Postdoctoral Fellowship for 6 months (Feburary 2022 to July 2022) at IIT Hyderabad.
Won Best Poster Award at Doctoral Symposium Abstracts at ICDCN 2019 for poster on Entitling Concurrency to Smart Contracts Using Optimistic Transactional Memory.
Qualified UGC NET India - December 2015 for Lectureship, [Score Card].
Qualified GATE India for four consecutive years from 2014 to 2017, and awarded GATE scholarship for pursuing M.Tech. (2014 - 2016).

Services

Gave a talk on Ethereum Blockchain and Smart Contracts during Teqip Workshop on Blockchain Technologies at IIT Hyderabad from December 16th - 20th, 2019.
Co-organized the Teqip Workshop on Blockchain Technologies at IIT Hyderabad from December 16th - 20th, 2019.
Student Placement Coordinator at the School of Computer and Information Sciences of University of Hyderabad from July 2015 - July 2016.
Coordinator for Works Application Co., Ltd. placement drive in Hyderabad from October 18th - 19th, 2015.

(Sub)Reviewer for the Conferences/Journals

Teaching Assistant

CS5320: Distributed Computing, IIT Hyderabad. Spring 2021, 2020, Autumn 2018.
CS1303: Introduction to Programming Languages, IIT Hyderabad. Autumn 2019.
CS5280: Concurrency Control in Transactional System, IIT Hyderabad. Autumn 2021, 2019.
CS5300: Parallel and Concurrent Programming, IIT Hyderabad. Autumn 2020, Spring 2019.
CS3523: Operating System 2, IIT Hyderabad. Spring 2019, 2018.
CS5530: Basics of BlockChains: Distributed Computing Perspective, IIT Hyderabad. Autumn 2018.
CS3510: Operating System 1, IIT Hyderabad. Autumn 2018, Autumn 2017.
CS2323: Computer Architecture, IIT Hyderabad. Autumn 2017.
CS773: Grid and Cloud Computing, SCIS, University of Hyderabad. Autumn 2016.
CS751: Parallel Computing, SCIS, University of Hyderabad. Spring 2015.