Satish Mahadevan Srinivasan | Machine Learning | Best Researcher Award

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Satish Mahadevan Srinivasan | Machine Learning | Best Researcher Award

Dr. Satish Mahadevan Srinivasan, Penn State Great Valley , United States.

Dr. Satish Mahadevan Srinivasan is a Tenured Associate Professor of Information Science at Penn State Great Valley, with expertise spanning data mining, machine learning, cybersecurity, and bioinformatics. With a Ph.D. in Information Technology from the University of Nebraska, his research contributions include class-specific motif discovery in protein classification and tools for metagenomic analysis. Dr. Srinivasan’s work merges cutting-edge technologies with practical applications, contributing to bioinformatics, distributed computing, and artificial intelligence. He has a rich academic and professional journey, publishing impactful research and developing transformative software tools. 🌐📊🔬

Publication Profiles

Googlescholar

Education and Experience

Education

  • 🎓 Ph.D. in Information Technology, University of Nebraska, 2010
  • 🎓 M.S. in Industrial Engineering & Management, IIT Kharagpur, 2005
  • 🎓 B.E. in Information Technology, Bharathidasan University, 2001

Experience

  • 📚 Tenured Associate Professor, Penn State Great Valley (2019–Present)
  • 📚 Assistant Professor, Penn State Great Valley (2013–2019)
  • 🔬 Postdoctoral Researcher, Computational Bioinformatics, UNMC (2011–2013)
  • 💻 Postdoctoral Research Assistant, Computer Science, University of Nebraska (2010–2011)
  • 🛠️ Project Assistant, IIT Kharagpur (2001–2005)

Suitability For The Award

Dr. Satish Mahadevan Srinivasan, a Tenured Associate Professor at Penn State, excels in interdisciplinary research spanning data mining, bioinformatics, machine learning, and cybersecurity. His groundbreaking tools like MetaID and Monarch have advanced microbial analysis and software engineering. With impactful publications, innovative solutions, and practical applications, Dr. Srinivasan exemplifies research excellence, making him highly deserving of the Best Researcher Award.

Professional Development

Dr. Srinivasan has developed innovative tools and frameworks, including MetaID for metagenomic studies and Monarch for transforming Java programs for embedded systems. His interdisciplinary research bridges machine learning, predictive analytics, and cybersecurity with bioinformatics, aiding microbial classification and software optimization. By integrating artificial intelligence and distributed computing, he has addressed complex challenges in data science, genomics, and engineering. His professional journey reflects a commitment to cutting-edge technology, impactful research, and knowledge dissemination through teaching and mentorship. 🌟🔍

Research Focus

Dr. Satish Mahadevan Srinivasan’s research focuses on leveraging advanced technologies to address complex problems in data science, bioinformatics, and cybersecurity. His work in data mining and machine learning aims to uncover patterns and develop predictive models for diverse applications. In bioinformatics, he has designed tools like MetaID for microbial classification and motif discovery in protein sequences, contributing to genomics and medical advancements. His expertise extends to cybersecurity, where he explores cryptographic techniques to enhance internet security, and distributed computing, optimizing system performance. Dr. Srinivasan’s interdisciplinary approach bridges artificial intelligence, predictive analytics, and software engineering to create impactful solutions. 🌐🔬📊

Awards and Honors

  • 🏆 Awarded research grants for innovative bioinformatics tools.
  • 📜 Recognized for contributions to cybersecurity and internet authentication.
  • 🌟 Acknowledged as a leading researcher in predictive analytics and machine learning.
  • 📊 Published in high-impact journals like BMC Bioinformatics and BMC Genomics.

Publication Top Notes

  • Effect of negation in sentences on sentiment analysis and polarity detection  – Cited by 93, 2021 📊📚
  • LocSigDB: A database of protein localization signals  – Cited by 49, 2015 🧬📖
  • K-means clustering and principal components analysis of microarray data of L1000 landmark genes– Cited by 46, 2020 🧪📊
  • Mining for class-specific motifs in protein sequence classification – Cited by 29, 2013 🔬📜
  • Web app security: A comparison and categorization of testing frameworks– Cited by 27, 2017 🔒🖥️
  • MetaID: A novel method for identification and quantification of metagenomic samples – Cited by 23, 2013 🌍🔍
  • Sensation seeking and impulsivity as predictors of high-risk sexual behaviours among international travellers – Cited by 21, 2019 ✈️🧠
  • Cybersecurity for AI systems: A survey – Cited by 20, 2023 🤖🔐

Ms. Priyanka | Neuromorphic Computing

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Ms. Priyanka : Leading Researcher in Neuromorphic Computing

Ms. Priyanka, Rajkiya Engineering College, India

👨‍🏫 Ms. Priyanka, a dedicated researcher and educator, is currently immersed in the realm of electronics and semiconductor technology, pursuing a Ph.D. in the Department of Electronics Engineering at NIT Patna. With a Master’s degree in Technology from NIT Rourkela and a Bachelor’s degree from Ajay Kumar Garg Engineering College, Ms. Priyanka boasts an impressive academic journey. With over 6 years of teaching experience, Ms. Priyanka has become a respected figure in the field, holding various positions such as Cultural and Literary Club Coordinator and serving as a Girl Hostel Warden at REC Mainpuri. Notably, Ms. Priyanka has excelled as a Library In-charge for the Department of Applied Sciences and Humanities and as Lab Incharge for Electronics, ADE, Communication, and Microprocessor Lab at Rajkiya Engineering College, Mainpuri. 🎓🔬

🌟 In addition to academic and administrative roles, Ms. Priyanka has received numerous accolades, including the prestigious Best Young Scientist Award at the “17th International Conference on Optics, Lasers & Photonics” in 2021. With a passion for knowledge dissemination, Dr. [Name] has been recognized as a distinguished speaker at five international conferences and has earned NPTEL Online Certifications in CMOS Digital VLSI Design, Fundamentals of Semiconductor Devices, and Microelectronics Devices To Circuits. This accomplished individual also holds a Translator Certificate from IIT Delhi for translating course files into Hindi. The recipient of the Institute Medal for Branch Topper at NIT Rourkela, Ms. Priyanka continues to contribute significantly to the fields of Leaky Integrate and Fire Neuron, Neuromorphic Computing, VLSI Design, and more. 🎓💡🔬

Profiles : Scopus 

🏆 Awards:

  • 🔬 Best Young Scientist Award in “17th International Conference on Optics, Lasers & Photonics” (June 26-27, 2021)
  • 🌍 Best Speaker Award for completing 5 International conferences
  • 💬 NPTEL Translator Certificate (Hindi) by IIT Delhi for Electrical Machines course (2020)
  • 💻 NPTEL Online Certification (Elite+Silver: Top 1%) in CMOS Digital VLSI Design (Feb-April 2019)
  • 🏆 NPTEL Online Certification (Elite+Silver: Top 1%) in Fundamentals of Semiconductor Devices (Jan-April 2019)
  • 🌐 NPTEL Online Certification (Elite+Silver) in Microelectronics Devices To Circuits (July-Oct 2019)
  • 🎓 Institute Medal for Branch Topper at NIT Rourkela (Jan 21, 2017)
  • 🥇 Certificate of Excellence for Holding First Position in M.Tech in Electrical Engineering at NIT Rourkela (Jan 21, 2017)

🌐 Research Interests : 📖

  • 🔍 Leaky Integrate and Fire Neuron
  • 💻 Neuromorphic Computing
  • 🔬 Nano Electronics
  • 🛠️ VLSI Design
  • 📏 Semiconductor Devices
  • ⚙️ Microelectronics
  • ☀️ Perovskite Solar Cells
  • 🚇 Tunnel Field Effect Transistors (TFET)
  • 🔄 Ferro TFET
  • 🚫 Junctionless and Doping-less MOS Devices
  • 🔄 Charge Plasma Bipolar Devices
  • 🔧 FinFETs

📚 Publication Impact and Citations:

Scopus Metrics:

  • 📝 Publications: 31 documents indexed in Scopus.
  • 📊 Citations: A total of 88 citations for his publications, reflecting the widespread impact and recognition of Ms. Priyanka’s research within the academic community.
Publications ( Top Note ) :

1.  Emulation of Neuro-mimetic Dynamics via GaSb/Si Heterojunction V-DGTFET Leaky-Integrate-Fire Silicon Neuron

2.  Analysis of full reference quality metrics for image transmission over a MIMO OWC channel under varying turbulent conditions

3.  Design and Simulation-Based Analysis of Triple Metal Gate with Ferroelectric-SiGe Heterojunction Based Vertical TFET for Performance Enhancement

4.  Simulation Study of Linearly Graded Binary Metal Alloy Pα Q1-α Gate TFET Device for Realization of Boolean Functions

5.  Quality assessment for terrestrial digital video broadcast over optical wireless communication-passive optical network under moderately turbulent regime with spatial diversity

6.  Design of electro-optic Mach–Zehnder interferometer based all-optical binary half adder and half subtractor

7.  Modeling of intensity fluctuations in the turbid underwater wireless optical communication links

8.  Performance estimation of image transmission in indoor visible light communication system based on variable pulse position modulation

9.  Statistical channel model to characterize turbulence-induced fluctuations in the underwater wireless optical communication links

10.  Modeling of laser beam deviation and estimation of link outage due to the presence of air bubbles in the underwater wireless optical communication system