Chemistry Department

 

Yu-Shan Lin, Chair of Department of Chemistry


 

https://chem.tufts.edu/people/faculty/yu-shan-lin

 

Research/Areas of Interest

Theoretical and Computational Biophysical Chemistry. The YSL Group aims to elucidate the structures and functions of biomolecules by integrating the power of advanced computations with the elegance of chemical theory. Our focus is to develop and apply computational methodology to significant biological problems that are difficult to address experimentally. Two major research projects in the YSL Group are (1) to understand and design cyclic peptides with desired conformations to modulate protein–protein interactions and (2) to elucidate the structural and functional roles of post-translational modifications and non-natural amino acids on protein folding.



 

Education


 

  • PhD Chemistry, University of Wisconsin–Madison, Madison, United States, 2009
  • MS Chemistry, University of Wisconsin–Madison, Madison, United States, 2007
  • BS Chemistry, National Taiwan University, Taipei, Taiwan, 2004

 

Clay Bennett


 

https://chem.tufts.edu/people/faculty/clay-bennett


 

 

Research/Areas of Interest


 

Organic Synthesis, Carbohydrate Chemistry, Synthetic Methodology, Bioorganic Chemistry. Complex carbohydrates play critical roles in a number of biological processes including, protein folding, cellular adhesion and signaling. Despite their importance, very little is understood about the molecular basis of their activity. This is largely due to the fact that the only source of pure oligosaccharides is tedious multi-step synthesis, which can take months or even years to compete. Our research is focused on developing methodologies, based on asymmetric catalysis, to streamline complex oligosaccharide synthesis. Ultimately such methods will aid in the rapid and routine preparation of oligosaccharides for biophysical studies and drug discovery.


 

Education

  • PhD Organic Chemistry, University of Pennsylvania, Philadelphia, United States, 2005
  • BA (cum laude) ACS Chemistry, Connecticut College, New London, United States, 1999


 

Ira Caspari-Gnann


 

https://chem.tufts.edu/people/faculty/ira-caspari-gnann


 

Research/Areas of Interest

Chemistry and STEM Education. In order to understand how and why successful teaching and learning of chemistry at the university level works, the Caspari research group focuses on analyzing students', teaching assistants' (TA), learning assistants' (LA), and instructors' reasoning, interactions, and culture. The group collects video data of classroom practices and conducts qualitative research interviews with instructors, TAs, LAs, and students to better understand how certain interactions and ways of reasoning lead to student sense making and learning. While zooming in and investigating how students connect aspects of chemistry, the group also zooms out and investigates classroom culture and how individual interactions and personal experiences integrate into larger systems of teaching and learning. The group uses this fundamental research as a theoretical basis for implementing teaching innovations and designing training opportunities in order to promote supportive learning environments for students that value and encourage their unique ways of being, knowing and doing.

Education

  • PhD Chemistry, Justus Liebig University, Giessen, Germany, 2018
  • MEd Chemistry and Biology, Johannes Gutenberg University, Mainz, Germany, 2013
  • BEd Chemistry and Biology, Johannes Gutenberg University, Mainz, Germany, 2010


 

Krishna Kumar

https://chem.tufts.edu/people/faculty/krishna-kumar


 


 

Research/Areas of Interest


 

Bioorganic Chemistry and Chemical Biology: The research interests of the Kumar laboratory are centered on the (1) use of chemistry to design molecules to interrogate and illuminate fundamental mechanisms in biology, or be used as therapeutics; and (2) use of biology to "evolve" and "select" molecules that can perform chemistry in non-biological and medicinal settings.

These are some questions we are trying to answer: (i) Is it possible to design and mimic natural proteins and other biological macromolecules by use of building blocks that nature does not use – and whether such constructs can be endowed with properties that are not found in biology?; (ii) How did the first enzymes arise in the imagined Darwin's pond – is there a way to recreate this scenario and in the process develop a fundamentally new method to create enzymes?; (iii) Biology uses phase separation, that is, clustering of different compounds in confined locations – a process that is key in orchestrating the daily activities of a cell – can we find methods that can predictably dictate where molecules are located in a given environment and thereby direct the phenotype that is generated?; (iv) Can we rationally design small molecules and peptides that can function against antibiotic resistant bacteria that are threatening the most basic tenet of modern medicine?


 

Education


 

  • PhD, Brown University, Providence, United States, 1996
  • BSc (Honours), St. Stephen's College, University of Delhi, Delhi, India, 1991


 

Charlie Mace

https://chem.tufts.edu/people/faculty/charlie-mace


 

 
 

Research/Areas of Interest


 

Bioanalytical and Materials Chemistry: To solve outstanding problems in global health, the Mace Lab applies a multidisciplinary approach combining aspects of analytical chemistry, materials science, and engineering. The primary goal of the Mace lab is to develop low cost, patient-centric technologies that can improve access to healthcare. To achieve this, the Mace Lab designs devices that improve the self-collection of blood and enable the diagnosis of diseases in resource-limited settings, and they are exploring ways the methods that are developed in the lab can used by others. Their main techniques leverage the properties of paper and other porous materials to integrate function into simple, affordable devices. unique to laboratories in Chemistry departments, his group specializes in handling human blood and saliva. Technologies developed in the Mace lab have made the leap to clinical sites in Africa, South America, and the US, owing to their network of clinical, academic, and industry collaborators. The Mace Lab has broad expertise in assay development and device prototyping, which they apply to evaluating the efficacy of candidate therapeutics, performing separations that lead to new measurements, and making field-deployable kits for point-of-care testing. They have additional expertise in instrument development, phase separation in systems of polymers, and microfluidics.


 

Education

  • PhD Biophysics, University of Rochester, Rochester, United States, 2008
  • MS Biophysics, University of Rochester, Rochester, United States, 2006
  • BS Physics, Le Moyne College, Syracuse, United States, 2003


 

Tufts Principal Investigators (PIs) 


 

ECE Department


 


 

Thomas Vandervelde, Chair of ECE Department


 

https://engineering.tufts.edu/ece/people/faculty/thomas-vandervelde


 


 

R esearch/Areas of Interest


 

Interaction of light with matter, physics of nanostructures and interfaces, metamaterials, material science, plasmonics, and surfactants, semiconductor photonics and electronics, epitaxial crystal growth, materials and devices for energy and infrared applications.


 

Vandervelde has extensive research experience in optoelectronics and photonics. He studies the interaction of light with matter and the physics of nanostructures (semiconductor photonics and electronics) and interfaces, with special interest in the area of energy materials.


 


 


 


 


 


 

Education


 

  • Ph.D., University of Virginia, Charlottesville, United States, 2004
  • M.A., University of Virginia, Charlottesville, United States, 2003
  • B.S., University of Massachusetts Amherst, Amherst Center, United States, 1999



 


 


 


 


 


 


 


 


 


 


 


 


 


 

Shuchin Aeron

https://engineering.tufts.edu/ece/people/faculty/shuchin-aeron


 

Research/Areas of Interest


 

data science, statistical signal processing, inverse problems, compressed sensing, information theory, convex optimization, machine learning, algorithms for geophysical signal processing, compressed sensing architectures and evaluation, video and image data acquisition and processing



 



 

Education

  • PhD, Boston University, Boston, United States, 2009
  • MS, Boston University, Boston, United States, 2004
  • B.Tech, Indian Institute of Technology, India, 2002
  • Post Doctoral Research Scientist, Schlumberger Doll Research, Cambridge, United States, 2011

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Marco Donato

https://engineering.tufts.edu/ece/people/faculty/marco-donato

 
 

Research/Areas of Interest


 

emerging technologies, non-volatile memories, SoC design, hardware for machine learning, noise modeling and reliability


 


 


 


 


 


 


 

Education


 

  • B.Sc. in Electrical Engineering, Università di Roma La Sapienza, Rome, Italy, 2008
  • M.Sc. in Electrical Engineering, Università di Roma La Sapienza, Rome, Italy, 2010
  • Ph.D. in Electrical Sciences and Computer Engineering, Brown University, Providence, United States, 2016


 


 

Mark Hempstead


 

https://engineering.tufts.edu/ece/people/faculty/mark-hempstead


 

R esearch/Areas of Interest


 

computer architecture, computer systems, power-aware computing, embedded systems, mobile computing, computer systems for machine learning, workload characterization, quantum computing, learning sciences and computer systems for human subjects research



 



 



 

Education

  • Ph.D., Harvard University, Cambridge, United States
  • S.M., Harvard University, Cambridge, United States
  • B.S. Summa Cum Laude, Tufts University, Medford, United States



 

Usman Khan

https://engineering.tufts.edu/ece/people/faculty/usman-khan


 

R esearch/Areas of Interest


 

Optimization and Control, Machine Learning, Signal Processing, Graph Theory, Decentralized Algorithms


 


 


 


 


 


 


 


 

Education


 

  • Ph.D., Carnegie Mellon University, United States, 2009
  • M.S., University of Wisconsin–Madison, Madison, United States, 2004
  • B.S., University of Engineering and Technology Lahore, Lahore, Pakistan, 2002


 


 

Valencia Koomson


 

https://engineering.tufts.edu/ece/people/faculty/valencia-koomson


 

R esearch/Areas of Interest


 

Biomedical instrumentation, AI-powered wearable devices, biophotonics,

optoelectronic integrated systems, health informatics, human-centered

design, health equity research



 



 

Education

  • Ph.D., University of Cambridge, Cambridge, United Kingdom, 2003
  • M.Phil., University of Cambridge, United Kingdom, 2000
  • M.Eng., Massachusetts Institute of Technology, Cambridge, United States, 1999
  • B.S., Massachusetts Institute of Technology, Cambridge, United States, 1998



 

Yingjie Lao

https://engineering.tufts.edu/ece/people/faculty/yingjie-lao


 

R esearch/Areas of Interest


 

trusted AI, hardware security, electronic design automation, VLSI architectures for machine learning and emerging cryptographic systems, and AI for healthcare and biomedical applications.



 


 


 


 


 

Education


 

  • Doctor of Philosophy, University of Minnesota, Twin Cities, Minneapolis, United States, 2015
  • B.S., Zhejiang University, China, 2009,


 


 


 


 


 

Eric Miller


 

https://engineering.tufts.edu/ece/people/faculty/eric-miller


 


 

R esearch/Areas of Interest


 

Statistical- and physics-based signal and image modeling and processing, tomographic image formation and object characterization, and inverse problems. Applications explored include human performance assessment, materials science, airport security, medical imaging, environmental monitoring and remediation, unexploded ordnance remediation, and automatic target detection and classification.



 



 

Education

  • Ph.D in Electrical Engineering, Massachusetts Institute of Technology, Cambridge, United States, 1994
  • S.M. in Electrical Engineering, Massachusetts Institute of Technology, Cambridge, United States, 1992
  • S.B. in Electrical Engineering, Massachusetts Institute of Technology, Cambridge, United States, 1990



 

Aseema Mohanty

https://engineering.tufts.edu/ece/people/faculty/aseema-mohanty


 

R esearch/Areas of Interest


 

nanophotonics, optical beam shaping, neuroengineering, chip-scale imaging and microscopy, quantum information systems


 

Research Website: https://sites.tufts.edu/amohanty/


 


 


 


 


 

Education


 

  • Doctor of Philosophy, Cornell University, USA, 2017
  • Bachelor of Science, Mass Institute of Technology, USA, 2011

Karen Panetta


 

https://engineering.tufts.edu/ece/people/faculty/karen-panetta


 


 

R esearch/Areas of Interest


 

Signal processing; image processing; simulation modeling

Karen Panetta's research focuses on developing efficient algorithms for simulation, modeling, and signal and image processing for security and biomedical applications.



 



 

Education

  • Ph.D., Northeastern University, Boston, United States
  • M.S., Northeastern University, Boston, United States
  • B.S., Boston University, Boston, United States



 

Paul Simmonds

https://engineering.tufts.edu/ece/people/faculty/paul-simmonds


 

R esearch/Areas of Interest


 

Experimental development of novel semiconductor nanostructures for quantum information sciences.
Tailoring crystal symmetry and strain at the nanoscale to produce next generation optoelectronic devices.

AREAS OF RESEARCH EXPERTISE
• MBE growth, chamber maintenance, and system support.
• Low-temperature, high-field magnetoresistance quantized carrier/spin transport (quantum Hall
effects, Shubnikov-de Haas oscillations, 1D quantized conductance, 0.7 structure, etc.).
• Atomic force microscopy (AFM), transmission electron microscopy (TEM), X-ray diffraction (XRD)
and photoluminescence (PL), Raman spectroscopy, ellipsometry, Rutherford back scattering, etc.
• Cleanroom-based micro/nanofabrication including photo- and e-beam-lithography, metallization,
and device packaging


 

Education


 

  • Doctor of Philosophy, Univ of Cambridge, GBR, 2008
  • Master of Science, Univ of Essex, GBR, 2002
  • Bachelor of Science, Univ of Durham/England, GBR, 1999

Sameer Sonkusale


 

https://engineering.tufts.edu/ece/people/faculty/sameer-sonkusale


 

 
 

Research/Areas of Interest


 

Bioelectronics, Biomedical microdevices, Wearables, Ingestibles, Biomedical circuits and systems, micro and nano fabrication, lab-on-chip microsystems, global health and precision medicine, CMOS image sensors for scientific imaging, analog to information converters, analog computing, brain inspired machine learning, active metamaterial devices, circuits, and systems, terahertz devices and circuits.



 

Education

  • Ph.D., University of Pennsylvania, Philadelphia, United States, 2003
  • MS, University of Pennsylvania, Philadelphia, United States, 1999
  • BE (Honors), Birla Institute of Technology and Science, Pilani, India, 1996



 

Mai Vu

https://engineering.tufts.edu/ece/people/faculty/mai-vu


 

Research/Areas of Interest


 

machine learning, applied optimization, wireless communications and networks, 5G/6G systems and techniques


 


 

She leads Tufts LiNKS, the Laboratory for communIcations in NetworKed Systems, which conducts research in wireless systems, signal processing, and networked communications. She and her group have published extensively in the areas of 5G and beyond systems, machine learning in communications, millimeter-wave communications, cooperative and cognitive communications, MIMO capacity and pre-coding, and energy-efficient communications.


 


 

Education


 

  • Ph.D. in Electrical Engineering, Stanford University, United States, 2006
  • MS in Electrical Engineering, Stanford University, USA, 2006
  • M.S.E. in Electrical Engineering, University of Melbourne, Melbourne, Australia, 1999
  • B.E. in Computer Engineering, RMIT University, Australia, 1997


 


 

Tufts Principal Investigators (PIs) Mathematics Department


 

Todd Quinto 

https://math.tufts.edu/people/faculty/eric-quinto


 

R esearch/Areas of Interest


 

Tomography is an inverse problem, and the goal of tomography is to map the interior structure of objects using indirect data such as from X-rays. Integral geometry is the mathematics of averaging over curves and surfaces, and it is the pure math behind many problems in tomography. Integral geometry combines geometric intuition, harmonic analysis, and microlocal analysis (the analysis of singularities and what Fourier integral operators do to them). I have proven support theorems and properties of transforms integrating over hyperplanes, circles and spheres in Euclidean space and manifolds.

Because of the mentorship of Tufts physics professor and tomography pioneer, Allan Cormack (Tufts' only Nobel Laureate) I developed X-ray tomography algorithms for the nondestructive evaluation of large objects such as rocket bodies, and this motivated my research in limited data tomography

In limited data tomography problems, some tomographic data are missing. I developed a paradigm to describe which features of the object will be visible from limited tomographic data and which will be invisible (or difficult to reconstruct). I proved the paradigm using microlocal analysis. Often artifacts are added to tomographic reconstructions from limited data, and colleagues and I recently used microlocal analysis to prove the cause of these added artifacts and to predict where they will occur.

Collaborators and I have developed local algorithms for electron microscopy, emission tomography, Radar, Sonar, and ultrasound. In each case we use microlocal analysis to determine the strengths and weaknesses of the problem and to refine and improve the algorithms.

Kasso Okoudjou

https://math.tufts.edu/people/faculty/kasso-okoudjou

Research/Areas of Interest


 

Time-frequency analysis, pure, applied, and numerical harmonic analysis; analysis and differential equations on fractals and graphs. My research interests lie in pure, applied and numerical harmonic analysis, especially, wavelet analysis, frame theory, time-frequency analysis of pseudo-differential equations and its application to non-linear PDEs. I am also interested in (spectral) analysis on fractals and graphs and their applications to data sciences. I have growing interests in mathematics education, especially on issues related to active learning in lower level math courses and on broadening the participation of underrepresented minorities in undergraduate research in the mathematical sciences.



 

Education

  • PhD, Mathematics, Georgia Institute of Technology, Atlanta, United States, 2003
  • MS, Electrical Engineering, Georgia Institute of Technology, Atlanta, United States, 2003
  • Maitrise es Sciences Mathematiques, National University of Benin, Abomey-Calavi, Benin,1996ore Program

Fulton Gonzalez

https://math.tufts.edu/people/faculty/fulton-gonzalez


 


 

Research/Areas of Interest


 

Noncommutative harmonic analysis, representations of Lie groups, integral geometry, and Radon transforms


 

Principally, I study two subjects in pure mathematics: harmonic analysis and integral geometry. The first field has a long history, dating back to Leonhard Euler's work on Fourier series back in the 1740's. The second is almost equally old, with roots in the geometric probability methods used to solve Buffon's needle problem in 1777.

In harmonic analysis, we learn how to decompose phenomena, expressed mainly by functions, into simpler constituents, as determined by the geometry of the space in which the phenomena occur. Thus, for instance, a human voice or the sound a violin makes can be decomposed into "pure" tones in order to be analyzed more effectively. Likewise, a fingerprint or any other two-dimensional picture can often be decomposed into simpler constituent functions.

One application of this kind of analysis is that it allows us to remove the "noise" associated with measured data. Another application, which forms the subject of my research, involves the reconstruction of functions from indirect data, such as their averages over curves or surfaces. This subject, integral geometry, is a large and active area in mathematics. The archetypal problem in this subject is as follows: how does one reconstruct a function in the plane from its averages over lines in the plane? The solutions to problems like these have many applications, for example in medical imaging and sonar.

I decided to pursue math as a profession when I was in college; when I went to graduate school I didn't really have any idea about what I should be interested in until I took a fantastic course taught by the professor who became my Ph.D. thesis adviser. It was an introductory course on integral geometry, and it was taught with the right combination of rigor and geometric intuition that was very appealing to me. It also helped that the class had some really bright and talented students, with whom I could discuss the mathematics being taught, and who have now become some of the world's top experts in integral geometry and related fields.

The thing that fascinates me about integral geometry is that one needs to know "a little bit of everything" in order to do research on the subject. In conjunction with this, one finds research problems in it which requires the collaboration of mathematicians whose expertise lies in disparate fields. Thus my main research collaborator, a Japanese mathematician from Tsukuba University named Tomoyuki Kakehi, is an expert in partial differential equations, which I know very little about. Likewise, Kakehi knows very little Lie group theory, a mathematical area I am familiar with.


 


 

Education

  • PhD, Mathematics, Massachusetts Institute of Technology, United States, 1984
  • BS, Mathematics, Ateneo University, Philippines, 1976