Mentoring

Abhishek Joshi is a published researcher and accomplished professional currently pursuing a master’s degree in computer science at Texas A&M University-Corpus Christi. His background includes roles as a Senior Software Engineer at Kellton Tech Solutions Limited and as a Senior Software Engineer/Product Manager at Star World Digital, where he led impactful projects resulting in notable efficiency boosts and revenue growth. As a team lead at Manipal Institute of Technology, Abhishek focused on sustainable technology, notably contributing to a project on Electric Vehicle State of Charge determination. Noteworthy achievements include being a Grand Finalist in the Smart India Hackathon and securing All India Ranks in IEEE XTREME coding competitions. Visit his LinkedIn profile for more information.

Amit Kumar is an aspiring data scientist and research student at Texas A&M University, Corpus Christi, pursuing an MS in Computer Science. After earning his Computer Science degree from Mumbai University, Amit enhanced his skills at Tata Consultancy Services, reducing client costs significantly with innovative web application skills. He’s also pioneered a blockchain and peer-to-peer-based Decentralized Storage System, showcasing his commitment to data security. His current work spans machine learning, deep learning, computer vision, and natural language processing, aiming to merge his technical skills with research to impact data science meaningfully. Check his LinkedIn for more insights.

Shengkun Wang was a former master’s student at Virginia Tech with a robust finance background cultivated during his undergraduate studies. During our collaboration, Shengkun demonstrated exceptional ingenuity, authoring multiple papers that showcased his innovative approaches. Currently pursuing a Ph.D. in AI/ML at Virginia Tech under the guidance of Dr. Chang-Tien Lu, Shengkun’s passion is centered around exploring the vast potential of machine learning models for financial applications. His unique focus involves integrating both traditional financial data and real-time social media and news data. Shengkun has designed cutting-edge recurrent neural network-based and transformer-based models, offering innovative insights into the analysis, interpretation, and prediction of market movements. For more information, visit his LinkedIn profile.