Hey sup, I am a Blockchain and DeFi researcher at University of Southern California, Los Angeles. As you might have guessed from the location, frequent beach trips and drives along the Pacific coast are my thing. Currently, I am pursuing my PhD in Electrical and Computer Engineering along with Master’s in Financial Engineering from USC (finance is like my side hustle!). It also helps my DeFi research so.. Prior to this, I worked as a mitacs globalink research intern at York University, Toronto. Here i explored topics like deep learning algorithms for darknet characterization and behavioral profiling of malware attacks. Overall, I had a fantastic hands-on experience with several network security projects and simultaneously improved my computational and systems skills!!

My bachelor’s and master’s degree is from IIT Kharagpur, India. I majored in Electrical Engineering with a specialisation in ML, AI and its applications. I somehow (barely!) made it through the core circuity stuff but EE helped build my engineering mathematical foundation. I graduated with a 9.01 cgpa (phew!) out of 10 and department rank-2. During my undergrad research days, I explored reinforcement learning and bandit algorithms in non-stationary environment. Plus I peeked in the world of federated learning through my bachelor’s thesis. Prolly the reason I looked further into distributed computing and got hooked to blockchain. Also now integrating DeFi to my expertise!! (blame my try-out-new-things to stay happy mindset)

I am a budding expert in my research field constantly gaining delta knowledge everyday. Also, creating new niche areas for fellow researchers to get baffled on. Look below for more details on my interests and work! I love collaborations and networking with people academically!! Do reach out through my contacts for a discussion.

Gmail/LinkedIn/Github/Google Scholar

Research Interests

My current research looks into the following aspects of blockchain and cryptoeconomics:

• Tokenomics and Incentive Design: Analyzing the economic models underlying blockchain-based tokens plus focusing on incentive structures, governance mechanisms, and network effects. This includes designing token distribution schemes and studying their impact on user behavior and network sustainability.
• Consensus in Dynamic Networks: Focusing on the development of consensus mechanisms tailored for dynamic and heterogeneous blockchain environments. Researching protocols like HotStuff and Tendermint that can adjust to network changes and ensure robustness. Developing consensus algorithms that maintain consistency and recover efficiently from network partitions inspired by recent advancements in the Avalanche protocol.
• Micropayments in Decentralized Networks: Enhancing the efficiency and security of micropayments for frequent, low-value transactions. Implementing schemes like probabilistic payment channels that reduce transaction overhead while ensuring security. Improving the scalability and reliability of off-chain solutions such as the Lightning Network for Bitcoin and Raiden Network for Ethereum.

Publications

1. Moein Shafi, Arash Habibi Lashkari, and Hardhik Mohanty. “Unveiling malicious DNS behavior profiling and generating benchmark dataset through application layer traffic analysis.” Computers and Electrical Engineering 118 (2024): 109436.
2. Gaines Odom, Hardhik Mohanty, Ujjwal Guin, Bhaskar Krishnamachari “Blockchain-Enabled Whitelisting Mechanisms for Enhancing Security in 3D ICs.” Proceedings of the Great Lakes Symposium on VLSI (2024).
3. Zhenbang Feng, Hardhik Mohanty, and Bhaskar Krishnamachari. “Modeling and Analysis of Crypto-Backed Over-Collateralized Stable Derivatives in DeFi.” Frontiers in Blockchain (2024).
4. Hardhik Mohanty, Arousha Haghighian Roudsari, and Arash Habibi Lashkari. “Robust stacking ensemble model for darknet traffic classification under adversarial settings.” Computers & Security 120 (2022): 102830.
5. Gourab Ghatak, Hardhik Mohanty, and Aniq Ur Rahman. “Kolmogorov-Smirnov test-based actively-adaptive Thompson sampling for non-stationary bandits.” IEEE Transactions on Artificial Intelligence 3.1 (2021): 11-19.

Hopefully a lot more to come, stay tuned ;)