• Actively curated 4 state-of-the-art sEMG datasets, focusing on Activities of Daily Living (ADL), Fine- ADL, Fatigue detection, and Frequency-based ADL.
• Two years of hands-on expertise in processing biosignals and feature extraction.
• Strong skill set in machine learning and deep learning model development, with a particular emphasis on Fully Connected Neural Networks (FCNN).
• Co-Authored three conference papers and submitted at BIOSIGNALS 2024, ISPA 2023, Rome, APSIPA ASC 2023.
• Currently working on a fourth conference paper centered around frequency-based ADL and 3 journal papers addressing the in-depth analysis of ADL, Fine- ADL, and fatigue detection.
• Ongoing research involves a comprehensive analysis of various factors, including in-depth analyusis on measurement conditions, body and hand postures, LOSO and weight training techniques.

• Contributing to the advancement of state-of-the-art models for health-related NLP.
• Expertise in fine-tuning advanced Health-related Language Models (LLMs) using benchmarked datasets.
• Gained hands-on experience in Natural Language Inference (NLI), Semantic Textual Similarity (STS), and Text Generation techniques.
• Worked extensively with prominent models like BioGPT, BioBERT, Clinical RoBERTa, GPT-2, BioM Transformers, PubMedGPT-2, T5, and Clin-X.

• Identifying biomarkers for Alzheimer's disease through EEG Data Analysis.
• Employed Signal Processing techniques to extract relevant features from various brain waves.
• Utilizing Data Analytics to explore the extracted data and pinpoint potential biomarkers associated with Alzheimer's.

• Used Natural Language Processing (NLP) techniques to identify potential cancer biomarkers.
• Implemented NER algorithms to extract relevant information from existing research papers.

• Conducted thorough analysis of established Nanomagnetic Logic (NML) simulators, like ToPoliNano, MagCad, and NMLSim2.0.
• Designed and simulated simple circuits (Majority Gates, Full Adders) using these simulators for comprehensive analysis.
• Contributed to the field, by publishing the outcomes, shedding light on advancements and challenges in NML circuit simulations.

• Explored Network on Chip (NoC) architectures, including SPIN, Cliche, and Torus.
• Investigated router power modeling and utilization of NVM-based memory.
• Developed power and latency models for STT and SOT RAM technologies.