Senior Postdoctoral Associates

rafal Rafał Krzysztoń. I am interested in single-cell responses to internal and external signals and in emerging mechanisms governing collective cell behavior. In my endeavors, I use methods of synthetic and quantitative biology (i.e. controlled microenvironments, synthetic gene networks, microfluidics, nanomaterials and quantitative microscopy), complementing standard biological assays. Together with Prof. Dr. Balázsi, we develop gene regulation systems allowing to explore and control cancer metastasis and to counteract viral infection. By monitoring the single-cell expression of disease-related genes and correlating it with phenotype profiles (e.g. cell motility) we aim to gain quantitative insights into emergence and dynamics of those complex pathologies. (Balázsi lab)
anupam Anupam Banerjee. I work on the integration of Elastic Network Models (ENMs) into various biological systems, aiming to provide a more comprehensive understanding of the intricate relationship between the structural characteristics and functional properties of biomolecules. My research interests primarily revolve around the advancement of protein engineering frameworks, designed to measure and assess the consequences of diverse modifications on a protein's structural dynamics and functional attributes. Through an interdisciplinary approach, I contribute to shedding light on critical biological mechanisms, aiding in the development of novel therapeutic strategies and a deeper understanding of complex disease processes. (Bahar lab)

Postdoctoral Associates

sridip Sridip Parui. The broad area of my research is the prediction of structures of biomolecules and the underlying pathways such as protein folding and conformational transitions. Knowing the three-dimensional structure and the related pathways is important for understanding biomolecular function. I believe MELD, which efficiently integrates external information with physics-based modeling, can serve these purposes. (Dill lab)
rostam Rostam Razban applies tools from statistical mechanics to elucidate underlying forces in biological phenomena, such as “Why do proteins evolve differently?”, “What causes cells to age?” and “How do brain networks transition?” Emphasis is placed on developing biophysical models for which mathematical equations with experimentally measured parameters can be derived. (Dill lab | Bahar lab | Mujica-Parodi lab)
Lakshmanji Verma. I am interested in molecular-level motions of chemical, physical, and biophysical systems in solvents which manifest interesting microscopic phenomena such as phase separation, aggregation, and nucleation that eventually dictate macroscopic behaviors. My current work focuses on the development of a statistical mechanical water model which will significantly reduce the time and computational cost required to simulate complex phenomena (e.g. protein-ligand complexation dynamics). (Dill lab)
ying jen yang2 Ying-Jen Yang. Thermodynamic/energetic principles can be formulated for stochastic dynamical models of complex systems. These principles include fluctuation-dissipation relations, the landscape theory in stochastic thermodynamics, and the statistical thermodynamics of entropic forces. They are formulated purely from time symmetries and the limit theorems of stochastic models in the ideal data infinitus limit and are thus universal. I am generally interested in developing these theories and applying them to solve problems in cellular biology, neuroscience, and evolution biology. (Dill lab)
anthony Anthony Bogetti. I am interested in developing methods for more efficient molecular dynamics simulations that enable more ambitious applications. During my PhD at the University of Pittsburgh in the lab of Lillian Chong, I worked on the weighted ensemble method, which uses splitting and merging to achieve more efficient sampling. I was a core developer of the WESTPA software package for weighted ensemble simulations. As a postdoc jointly in the labs of Ken Dill and Ivet Bahar, I am now interested in how the MELD sampling strategy, possibly combined with ENM methods, can further enhance molecular dynamics simulations and enable even more ambitious applications. (Dill lab | Bahar lab)
xiaoweibogetti2 Xiaowei Bogetti. I attained my PhD in the lab of Sunil Saxena at the University of Pittsburgh, where I worked on electron paramagnetic resonance spectroscopy and molecular dynamics simulations. As a postdoctoral researcher in the lab of Ivet Bahar, I am interested in integrating experimental data into computational modeling to achieve a more complete understanding of protein dynamics and interactions. (Bahar lab)
Xin photo Laufer Xin Cao. I am interested in the development of geometric methods to study the structure-function relationship of molecules. By using geometry methods, we have developed a robust numerical algorithm for the solutions of inverse kinematics problems arising in molecular structure studies, and a numerical method to compute the molecular surface areas and volumes which are playing significant roles in the solvation of molecules. My current work focuses on the applications of the methods to the quantitative evaluation of molecular interactions and to the efficient exploration of molecular shape spaces, such as macrocycles, loop regions in proteins, and RNAs. (Coutsias lab)
Yiming Wan Yiming WanI have a deep-seated interest in the confluence of synthetic biology and cancer biology. My ambition is to seamlessly intertwine these two domains, aiming to produce groundbreaking, quantitative insights into phenotypic landscapes in cancer models. While pursuing my PhD at Stony Brook University under the expert guidance of Dr. Gabor Balázsi, our team harnessed these synthetic biological tools to forge a novel quantitative understanding of a pivotal cancer metastasis regulator, BACH1. Our discoveries revealed that BACH1 regulates cancer invasion in a non-monotonic fashion while consistently inhibiting cell proliferation. As I transition into my postdoctoral role in the Balázsi lab, my vision is to craft cutting-edge, multi-functional cellular platforms. These platforms, boasting expanded dimensions and capabilities, will be instrumental in delving deeper into the quantitative nuances of cancer models and serve as the foundation for safe and efficacious therapeutic interventions. (Balázsi lab)

Senior Research Scientists

marycheng Mary Hongying Cheng. I have extensive background in developing, implementing and applying multi-scale computational methods and tools for molecular dynamics simulations, elastic network modeling, and kinetic modeling. Additionally, I am experienced in druggability simulations and docking simulations, pharmacology modeling and virtual screening, and quantitative systems pharmacology modeling. My research areas include i) protein function and dynamics; ii) modulation of protein function by regulatory proteins, drugs, and membrane lipids; iii) computer- aided drug discovery; iv) assembly/clustering of protein complexes and multimers; v) protein glycosylation and ubiquitination; and vi) ion permeation characteristics and charge selectivity in receptor channels. I have more than 20 years’ experience in modeling and simulating a wide range of biological proteins, including neurotransmitter transporters, G protein coupled receptors (GPCRs), voltage- and ligand-gated ion channels, and kinases, as well as their interactions with drugs, psychostimulants or antidepressants, lipids, and regulatory proteins. (Bahar lab)

Research Scientists

JiYoung JiYoung Lee. My major area is computational pharmacology, computer-aided drug discovery and development, simulations of protein-protein and protein-ligand interactions applied to membrane proteins. I have been working on allosteric modulation, activation and desensitization of membrane proteins and the development of the interface Pharmmaker for pharmacophore modeling coupled to druggability simulations using DruGUI. (Bahar lab)

Laufer Junior Fellows

D Padhorny Dzmitry Padhorny. I work on novel approaches on modeling the biomolecular interactome across the scales, from improving the methodology for modeling the basic binary protein complex to analysis of whole-cell protein/metabolite interactions networks. Currently focused on pushing the limits on the size of the systems we can meaningfully simulate. (Kozakov lab)