Vineeth Venugopal

I am very passionate about harnessing the power of artificial intelligence in the Sciences, believing firmly in a future shaped by human-AI collaboration. In my role as a Postdoctoral Scholar at MIT, I specialize in data science, machine learning, and materials informatics, where my enthusiasm lies in dissecting complex systems to glean insights and data. This extends from my current focus on scientific literature and patent analysis. My expertise in Python, a range of machine learning algorithms, large language models and my background in engineering equips me with a unique blend of skills, perfectly suited for blending science with the advancements of artificial intelligence.

• Python based data science - Numpy, Pandas, Matplotlib
• Machine Learning - Scikitlearn, Pytorch, TensorFlow
• Large Language Models, Langchain, Streamlist, Flask
• C and C++
• CNNs, Reinforcement learning, Variational autoencoders, GANs, LSTMs
• Natural Language Processing - NLTK, genism, LSTM, Attention Models
• Mutivariate Statistics and Machine Learning (Kris Reyes, U at Buffalo, Fall, 2018)
• Quantum Computing - Qiskit, QC BQP algorithms
• Graphs and Graph Neural Networks using Networkx

• Organizing Committee Member, Neurips AI4Mat workshop, 2023
• Board of Directors, International House of Rhode Island - A nonprofit organization serving international visitors, particularly graduate students, in Rhode Island. Active volunteer, member of several committees etc.
• Technical Officer, Graduate Student Council at Brown - In charge of several email list serves, the main graduate student website etc. Also, an active participant in university level decision making processes affecting all graduate students

• A Knowledge Graph in Material Science, COMBI 2022, Colorado, Sep, 2022
• MatKG: The largest knowledge graph in Material Science, MRS 2022, Boston
• Spotlighted talk: A knowledge graph in Material Science, Neurips AI4Mat Workshop, New Orleans, 2022
• A novel method for knowledge discovery in graphs using Large Language Models, MRS Spring 2023, San Fransisco

• Knowledge Discovery in Material Science using Knowledge Graph Embeddings, In preparatio
• MatKG: A FAIR knowledge graph in Material Science.,Submitted to Nature Scientific Data
• Graph Analysis of concepts and relations in materials science, In preparations
• MatKG-2: Unveiling precise materials science ontology through autonomous committees of LLMS, AI4Mat workshop, Neurips 2023
• Understanding domain behavior of composite Hybrid films using band Excitation Piezo Force Microscope- A Big Data approach Vineeth Venugopal, Seunghyun Kim, Angus Kingon, In preparation
• MatKG: The largest knowledge graph in Material Science. Neurips AI4Mat workshop. 2022.
• Hybrid piezoelectric thick films of Lead Zirconate Titanate: Strain response and domain segregation Vineeth Venugopal, Seunghyun Kim, Angus Kingon, In preparation
• Unveiling the Glass Veil: Elucidating the Optical Properties in Glasses with Interpretable Machine Learning, Mohd Zaki; Vineeth Venugopal, Ph.D.; R. Ravinder; Suresh Bishnoi, Anoop Krishnan, Acta Materialia, under review.
• Looking Through Glass: Knowledge Discovery from Materials Science Literature using Natural Language Processing. Vineeth Venugopal, Saurabh Kumar, Mohamad Zaki, Anoop Krishnan, Patterns, 2, June 2020
• Artificial Intelligence and Machine Learning in Glass Science and Technology: 21 Challenges for the 21s Century. Ravinder, Vineeth Venugopal, Mohamad Zaki, Anoop Krishnan, Journal of Applied Glass Science, January 2020.
• A Picture is Worth a Thousand Words: Applying Natural Language Processing Tools for Creating a Quantum Materials Database Map. Vineeth Venugopal, Scott Broderick, Krishna Rajan, MRS Communications, September 2019.
• BiFeO3-doped (K0.5,Na0.5)(Mn0.005,Nb0.995)O3 ferroelectric thin film capacitors for high energy density storage applications Sung Sik Won, Masami Kawahara, Lindsay Kuhn, Vineeth Venugopal, Jiyeon Kwak, Ill Won Kim, Angus I. Kingon, and Seung-Hyun Kim . Appl. Phys. Lett. 110, 152901 (2017)
• Lead-free Mn-doped (K0.5,Na0.5)NbO3 piezoelectric thin films for MEMS-based vibrational energy harvester applications Sung Sik Won, Joonhee Lee, Vineeth Venugopal, Dong-Joo Kim, Jinkee Lee, Ill Won Kim, Angus I. Kingon, and Seung-Hyun Kim . Appl. Phys. Lett. 108, 232908 (2016)
• New ceramics materials for Microwave Dielectric Resonator Applications Selected for presentation at the International Conference on Electroceramics (ICE 2009) at Delhi (13 – 17 December 2009)
• “Synthesis, Characterization and Microwave properties of Sr(2-x)La 2 Mg (1+x)W2 O12 (x = 0,1) ceramics for Microwave Dielectric Resonator applications” Vineeth Venugopal, P.S. Anjana, Om Parkash, D Kumar and M.T Sebastian; Journal of American Ceramic Society , Vol 93, Issue 3. 4/4/2009

• Silicon Lasers: The Final Frontier, Photonics Focus, 01/07/2020
• The light way to 6G, Photonics Focus, 01/01/2021
• The prodigal Microchip, Photonics Focus, 01/05/2021
• The G-filter: A simple high-tech solution to India's water pollution, MRS Bulletin, 2019
• Lithium Ion batteries: Where did we come from, where do we go?, www.science.thewire.in, November, 2020
• Scientists have turned the structure of the coronavirus into music, Science, 03/04/2020
• Crystal microstructures inspire architecture 3D printed metamaterials, MRS Bulletin, 44, 4
• Bio Focus: Graphene microtransistors map brain activity, MRS Bulletin, 44, 3
• Bo Focus: Flexoelectricty found in bone, MRS Bulletin, 43, 4
• Universal Fragment descriptors predicts materials properties, MRS Bulletin, 42, 8
• Bayesian inference supersedes Reitveld technique in crystallographic structure refinement, MRS Bulletin, 41, 12
• Kirigami honeycomb material exhibits a Poisson's switch, MRS Bulletin, 41, 10
• Materials Fingerprints identified for informatics, MRS Bulletin, 40, 4